AI labs are paying real money to license real-world source code and git history. Pangea.ai works with a specialist licensing partner so agencies in our network can turn the codebases sitting idle after delivery into revenue, with zero upfront cost and almost no effort. Our partner values your code, handles the legal, finds the buyers, and sells. You're paid every time your code is licensed, not just once.
These are the standing rates in the agreement: a straight payout per million tokens, on every sale, changeable only on 30 days' notice and never on a deal already done. Connect Git to see an estimate for each repo in minutes, at no cost.
Programme figures as of November 2026. Averages are to date, not a guarantee for any one repository.
The market is moving quickly: models are getting stronger, and labs need increasingly complex datasets to improve them. Here's what that means for your repositories.
The labs no longer accept AI-written code. Code written from 2025 onward is flagged "Low likelihood of licensing" at first, but you can provide context and verifiable evidence for review to make it eligible.
Add tickets, docs, chats and other work data linked to your repositories. Experimental, with no quote or payment promised yet. More below.
Once you sign and your repositories pass eligibility checks, they go straight to the labs for evaluation, not in scheduled batches. Check each repository's status; batch information appears once a lab confirms and finalises a purchase.
Full detail, including how flagged repos are reviewed, is on the Eligibility tab.
Tickets, docs and chat from the work behind the code. Export from the tools your team already uses and drop the file into the Operational data tab. Most exports take minutes.
Tickets and tasks · Docs and design · Chat and email · Customer support · Sales and CRM · AI assistants
Open your Pangea.ai link and sign one combined agreement: confidentiality and licence in one document, one signature.
Connect GitHub, GitLab, or Bitbucket and pick only the repos you want to license. Nothing else is touched.
Our partner analyzes, values, and sells to buyers. You're paid every time it's licensed, not just once.
Frontier AI labs train and evaluate their coding models against genuine production code: the source and the git history behind it, how features were built, how bugs were fixed, how a project evolved over time. That kind of verified, real-world code is what's in short supply, and demand for it is high right now. The projects your agency has already delivered are exactly that.
Genuine, verified production code is the ingredient labs are short on, and it can't be synthesised.
Buyers are actively acquiring real-world codebases to train and test their models, and that appetite is growing.
Commits, tickets, and fixes carry real signal, so you're paid for the history too, not just the final source.
A quick, illustrative ballpark, nothing more. Your real, per-repo number comes in minutes once you connect Git. Final value depends on analysis of your repos and buyer demand.
Drag to estimate from repo count. Know your token counts? Enter them instead.
Licences are non-exclusive by default, so the same code can sell to more than one lab, and you're paid each time, not once.
For code written from 2025 onward, explain how it was built and why it's valuable.
If you have it. There's no guarantee, but it can add value to the same codebase.
Idle, or waiting on a payment before adding more? Add them now. As the labs' requirements tighten, licensing will only get harder.
Know a friend or colleague with private code? Share your referral link while the window is open.
Licences are non-exclusive and you keep the IP. Review and final licensing can take a few weeks, so it may look quiet, but a lot is happening behind the scenes: our partner is preparing and packaging repositories so they can be licensed as widely as possible.
Open your Pangea.ai referral link, connect Git, and see what your repos are worth, no commitment.
What makes a codebase a fit for licensing, and what rules one out, so you know before you submit. The short version is the checklist on the Overview tab.
On this tab: What rules a repo out·Self-check·Low likelihood·Where you're based·Valuation and ownership·Grade
Eligibility is separate from grade. A repository can be perfectly eligible and still score poorly; the grade affects what it sells for, not whether it can be taken.
Buyers pay specifically for code that isn't already in a public training corpus, so anything ever published, including as an npm or PyPI package, is worth nothing to them, whatever it scores.
Forks, renamed open source, copies of public templates, WordPress sites, themes and plugins, AI-written code and repos with no licensable source code aren't accepted. Every eligible repo goes to the labs once you've signed.
Our partner declines repositories for any of these reasons:
| Reason | What it means |
|---|---|
| Publicly readable today | The repository page loads for a signed-out visitor. This is by far the most common reason. |
| Public at some point in the past | The Internet Archive holds a crawl of the repository page. Their crawler isn't logged in, so a snapshot proves it was public on that date. Making it private now doesn't undo this. |
| A fork of someone else's project, or renamed open source | The upstream code isn't yours to license, and it's already public. |
| Published as a package | Shipped on npm, PyPI or similar. The source is already distributed. |
| A copy | The same code submitted twice, or a public template with little new code on top. A starter is fine when most of the code and commits are yours. |
| A WordPress site, theme or plugin | Not accepted for licensing. |
| No licensable source code | Datasets, data dumps, generated output, or a repository that's mostly vendored libraries and build files. |
| AI-written code | Our partner doesn't accept code written by AI, and the labs are strict about it. Code written by people before 2025 is the strongest fit. A repo is marked Not eligible if it's mostly AI-written, including by your own answer on the context form. |
| Ask | Why it matters |
|---|---|
| Is the code private, and has it always been? | If any of it was ever on a public repository, published as a package, or forked from an upstream project, it isn't licensable. |
| Did your team write it? | Code written by people before 2025 is the strongest fit. AI-written code isn't accepted, and nor are WordPress sites, themes and plugins. A first commit in 2025 or later is flagged Low likelihood until you provide verifiable context. |
| Is it the full repository? | Connect it straight from GitHub, GitLab or Bitbucket, with its pull requests, code review, issues and tests kept on the host. A flattened copy or single-commit upload loses most of its value. Code on your own machine? Push the existing git repository with its history, not a fresh copy. |
| Do you own it outright? | If a client owns or co-owns it, you need the client's written OK before you submit it. |
| Is it real application code? | Repos with no licensable source code are declined, and repos that are mostly assets, archives or vendored dependencies value far lower than their size suggests. |
| Do you know what open-source you depend on? | Particularly anything copyleft. |
Labs favour original code with meaningful development history. A repo whose first commit is in 2025 or later shows "Low likelihood of licensing", with its first commit date and a Provide context button. It isn't presented to the labs, and stays out of your totals, until it's cleared.
Provide context opens a short form: how the repo was developed, what engineering is behind it, how it's been used, and anything verifiable. It opens with every flagged repo already ticked, so one form covers all of them. Once you've sent it, the repo shows "Context submitted" while it's reviewed.
| Status | What it means |
|---|---|
| Eligible | Verifiable proof clears it: an older repo or Git host the code came from, dated contracts or invoices, or an app-store or website launch before 2025. Code that genuinely started in 2025 or later can clear on its contributors and pull-request history. |
| Low likelihood | The default for a flagged repo. It stays here if the context gives nothing verifiable, because answers alone are self-reported. |
| Not eligible | Mostly AI-written (your own answer counts), or another hard failure such as public code. |
Answer accurately: misrepresented answers can get codebases removed and the account suspended. A cleared repo goes to the labs like any other, though a lab may still pass on it.
If the code is already in a git repository on your machine, push that repository to GitHub, GitLab or Bitbucket with its history. The original commit dates come with it, so it's judged on when it really started. Don't copy the files into a new repository: that resets every date to the upload day. Code that was never in git can't show when it was written, so it shows Low likelihood of licensing; Provide context with something checkable to clear it.
Most surprises have a fix on your side.
Click Provide context and include something checkable: an older repo, dated contracts or invoices, or a launch before 2025.
It was probably copied into a fresh repository. Push the original git repository with its history instead.
Vendored libraries, build output and data dumps don't count. Connect the full repository from your Git host, with its history.
Priced, but not in front of the labs yet. Sign the agreement and it turns Counted.
There's one regional restriction. Because of sanctions, our partner can't work with code owners resident in Russia, and can't pay them, whatever country their bank account is in. There's no other regional restriction.
Reference detail. Open what you need.
Value is calculated from two numbers: the source code at the current head of the repository, and the additional code that exists only in its git history. Both count only real source and code-adjacent files.
| Counted | Not counted |
|---|---|
| Application source in any mainstream language, plus shell scripts, SQL, schema files (GraphQL, Protobuf) and web styles. Markup, data, config and docs (YAML, TOML, JSON, XML, Markdown and similar) count up to 10× the code beside them. Lockfiles and minified files in normal source folders stay, as does third-party code copied straight into source folders. | Vendored dependencies (node_modules, vendor and similar), build output and caches, generated files, compiled binaries, archives, Office documents, IDE state and data dumps. These are also stripped from every commit of the copy our partner delivers. |
This matters more than it sounds. A repository can look substantial on disk and value low because most of its weight is a vendored library, a committed build output, or a large archive. None of that is code a buyer can train on, so none of it is counted as source. Third-party code copied straight into your source folders does stay in, under its own licence, so disclose it in the open-source & third-party field below.
There's one proportion rule worth knowing. Markup, data, config and docs count up to 10× the code beside them: enough that a well-documented, well-configured project is paid for that work, without a repository of mostly data pricing like a repository of mostly code.
Ownership remains with the code repository owner uploading the repository. They must confirm that they own the code, or otherwise have the legal right to license it, and we rely on that confirmation and the warranty in the signed agreement.
We do not require supporting documents upfront and cannot independently verify ownership simply because someone has access to a repository. If the uploader confirms contractually that the code is theirs and can be licensed, we accept that representation and proceed accordingly.
Where the code belongs to a client, is jointly owned, or includes another party’s intellectual property, the uploader must have permission to license it. Client-owned code needs the client's written OK before it's submitted. In practice, supporting documents are usually only asked for if a buyer’s due diligence calls for them, though §5 of the agreement lets our partner request redacted chain-of-title documentation (IP assignments, asset purchase agreements, prior licences) on reasonable request at any point, and you can redact whatever isn’t needed to confirm ownership.
Every repository has an "Open-source & third-party disclosure" field in the product. It's required before a repository is approved for listing, and it gates listing rather than signature, so it never holds up signing an agreement.
What matters most is copyleft, GPL, AGPL and LGPL especially. AI buyers warrant hard against it, and an undisclosed copyleft dependency can unwind a deal after it has closed. Anything works as a format: type it into the box, or attach an SBOM (CycloneDX or SPDX), a lockfile, or a CSV listing component, version, licence, and whether attribution, source-disclosure, copyleft or redistribution obligations apply.
A low grade never makes a codebase ineligible. Once you've signed, every eligible repo goes to the labs right after analysis, whatever its grade. A higher grade makes a repo more attractive to the labs; it isn't a threshold. The labs choose what to license, so not every repo will be chosen. See How We Grade for what the grade looks at.
Submit repos as they are. You don't need to rebuild or clean anything first: our partner works on a separate copy and never pushes changes to your repositories.
The full flow, step by step. Brought to you by Pangea.ai, in partnership with Our partner.
Pangea.ai works with a specialist licensing partner to help the agencies in our network turn code that is otherwise gathering dust into revenue. AI labs and other buyers are actively paying to license real-world source code, and our partner handles the entire sale. This guide walks you through the whole flow: open your Pangea.ai link, sign one short agreement, connect your Git providers, pick the repos you want to license, and add a little context for each one. Our partner's team reviews and sells from there, and you are paid every time your code is licensed, not just once.
As you select repos, you'll see the estimated value of each one and a running total, so you know what a repo is worth before you submit it. Repos flagged Low likelihood of licensing aren't included in your total until they're cleared. Each repo also shows Estimate (priced, not yet in front of the labs) or Counted (in front of the labs, or licensed); see the FAQ. The rates above are your payout: the amount paid to you per million tokens, not a share you need to discount. And because a codebase can be licensed more than once, you're paid this on every sale, not just the first.
These figures are estimates only, not guaranteed payouts. Token counts and final value are subject to our partner's analysis, which determines what is counted and may exclude files or data. Final value also depends on buyer demand.
| Action | Where |
|---|---|
| Get started | pangea.ai/code-licensing/agency |
| Open the licensing flow | Sidebar → Code Licensing |
| Sign / download the agreement | Code Licensing → Codebase Agreement card |
| Add more repos later | Code Licensing → Submit for Analysis |
| Edit any field | Expand a repo → type in the field → auto-saves |
| Questions | Reach out to your Pangea.ai contact |
Every codebase you submit is graded against a fixed rubric, so you can see where it stands. The grade makes a repo more or less attractive to the labs; it isn't a threshold.
Every eligible repo goes to the labs once you've signed, whatever its grade. A higher grade makes it more attractive to the labs; it isn't a bar to clear, and there's no remediation work on your side.
A model reads the cleaned copy of each repository and scores four things: architecture, tests, documentation and history. Grading does not build or run the repository.
You submit the repo as it is. There's no fix list and no engineering time to budget for, and your repositories are never written to.
Before the rubric, buyers screen for a handful of numbers that only a real, team-built project tends to carry.
Rough thresholds, not hard gates. Smaller and solo repos are presented too, and what each lab wants shifts month to month, so the best move is to have more of your work in the catalogue, not to pre-filter it.
Roughly in the order they ask them.
Built for a company, a client or a product, with real users. SaaS platforms, backends, internal tools and full applications beat tutorials, templates and experiments. The bigger and more complete the system, the better.
A whole project, not snippets: source with its tests, docs, configuration and dependencies. Context is what teaches a model how software fits together.
Years of commits, branches, merged pull requests and fixes. History shows the before and after of every change, which is exactly what coding models train on.
Clean architecture, real tests, CI, consistent practice, meaningful commit messages, written by your team. AI-written code isn't accepted.
Code the public datasets do not contain: enterprise systems, specialised industries, less common languages, legacy stacks and multi-service architectures. Rarity is the one dimension that cannot be manufactured after the fact.
If the base is public, models have already trained on it; only original work carries value. Forks of other projects aren't accepted at all.
Coursework, templates and scaffolding are the most duplicated code on earth.
Generated files, vendored dependencies, build output and binaries don't count as source, so bloat doesn't help.
One contributor and a few commits gives a buyer less to learn from, however clean the code. Still submitted, still presented, just worth less.
A repo that is mostly someone else's open source is someone else's code. Where it's copied into your source folders it stays in the count under its own licence, so disclose it.
A language model reads the cleaned copy of the repository and scores it against a fixed rubric covering architecture, tests, documentation and history, then gives it a letter grade. It sees the repository name, rubric statistics and the files it chooses to open. Grading does not build or run the repository.
| Dimension | What we look for | What lifts it |
|---|---|---|
| Architecture | Clear layering, deliberate error handling, validated input, config injected not hardcoded. | Business logic separated from I/O and HTTP, input validated at boundaries, and errors handled deliberately rather than swallowed. |
| Tests | Real tests over real behaviour, run in CI, not snapshots or assertion-free stubs. | A test runner covering the core logic with real assertions, wired into CI. Roughly one test file per ten source files is a healthy shape. |
| Documentation | A README a new engineer can clone and run from today. | A README covering install, run, test, config and architecture, with a .env.example and a Dockerfile so setup is reproducible. |
| History | Conventional commits, tagged releases, an active repo, more than one real contributor. | Meaningful commit messages, tagged releases, and a repository that shows real activity over time. |
An estimate is instant: you can run the counter from your own terminal, or see one per repo the moment you connect Git. The rest are planning ranges, not deadlines. While a lab reviews, our partner works with it to prove the repo's training signal, and your dashboard shows where each repo sits.
There's a downloadable estimator you can run against any repository on your own machine, before connecting anything or signing anything. It uses the same counting rules and standing rates as the platform, and nothing leaves your machine. Ask your Pangea.ai contact for the script.
Point it at several repositories, or a folder of them, for a row per repo and a total. It prices at the standing rates ($100 per million source tokens, $40 per million git-history tokens) and prints an estimate at those rates, not an offer. It also prints the counting rule it applied and, under each repo, the text it left out, so a number that looks small explains itself. The platform applies the same rules after you submit.
Submit what you own and leave the rest. Most repos are prepared in minutes, the grade tells you and the buyer what's there, and once you've signed, every eligible repo goes to the labs whatever its grade. There's no fix list to work through and no engineering time to budget for. The only work on your side is choosing which repositories to include.
Everything agencies ask, answered. Pangea.ai, in partnership with Our partner.
The five questions we hear most. Everything else is grouped below.
A single agreement covering two things: (1) confidentiality between you and our partner, and (2) a non-exclusive licence for our partner to access, package, market, license and sell your codebases to buyers. You sign once; our partner has already countersigned. It's governed by Delaware law, with any dispute heard in the Delaware courts.
Your signature is also your standing authorisation for each individual non-exclusive buyer licence our partner grants (§13.3), so no per-deal signature is needed. Two things do need your separate written agreement: an exclusive licence to one buyer, and any deal that would restrict the rights you keep under §6.2 (§13.4).
You can read the full Codebase Agreement before you sign; ask your Pangea.ai contact for a copy.
Most repos are prepared in minutes; very large histories or a busy queue take longer. Once you've signed, each repo is presented to the labs right after analysis, and while a lab reviews, usually 4 to 12 weeks, our partner works with it to prove the repo's training signal. Repos flagged Low likelihood of licensing aren't presented until they're cleared. These are planning ranges, not deadlines.
From there it depends on buyer demand, so there's no guaranteed timeline. Once a deal lands, the lab raises a PO on roughly 60-day terms and you're paid Net 15 after the funds clear. Your dashboard moves the moment there's news, and we'll keep you posted on status.
Its first commit is in 2025 or later. Labs favour original code with meaningful development history, so a recent first commit is an initial signal, not a final decision. Until it's cleared, the repo isn't presented to the labs and stays out of your totals.
Click Provide context next to it and answer a few questions about how it was developed, the engineering behind it and how it's been used, plus anything verifiable. The form opens with every flagged repo already ticked, so one form covers all of them. It's marked Eligible if there's verifiable proof, such as an older repo or Git host the code came from, dated contracts or invoices, or an app-store or website launch before 2025; code that genuinely started in 2025 or later can clear on its contributors and pull-request history. It stays at Low likelihood if nothing verifiable is given, and it's marked Not eligible if it's mostly AI-written, including by your own answer.
Answer accurately: misrepresented answers can get codebases removed and the account suspended. A cleared repo goes to the labs like any other, though a lab may still pass on it.
Counted means the repo is in front of the labs, or already licensed. Estimate means it's been analysed and priced but isn't in front of the labs yet, almost always because the agreement hasn't been signed. It turns Counted as soon as you sign.
Both figures are estimates, not guaranteed payouts. These statuses are separate from which files are counted toward the valuation, covered on the Eligibility tab.
They're used only to analyse, grade and value them. Our partner claims no licence to them and treats them as Confidential Information under §3 of the Codebase Agreement, as if you had signed. Nothing goes to the labs or anyone else until you sign.
If you decide not to go ahead, the stored copy is deleted and our partner confirms the deletion in writing. Once you sign, the Codebase Agreement governs.
Frontier AI labs are paying real money for real-world codebases to train their coding models. Pangea.ai works with a specialist licensing partner, who handles valuation, legal, and the sale end to end, so agencies in our network can turn dormant code into revenue. You're paid for every codebase that sells, with no upfront fee.
Frontier AI labs train and evaluate their coding models against genuine production code: the source and the git history behind it, how features were built, how bugs were fixed, how a project evolved over time. That kind of verified, real-world code is what's in short supply, and demand for it is high right now. The projects your agency has already delivered are exactly that, and because the history carries value too, you're paid for it, not just the final source.
Frontier AI labs and similar data buyers, all under confidentiality. Our partner packages and sells to them, so you never deal with the buyer directly, and specific buyers aren't disclosed.
Buyers license codebases to train, fine-tune, evaluate and benchmark their coding models, and to research and improve those models and the systems around them. They can modify the code and create derivative works for that work.
Our partner sets the terms of each buyer licence and negotiates them per deal (§6.3, §7.1), so the precise scope of any one licence is a commercial matter between our partner and that buyer, and its terms are confidential. Worth knowing: once a deal has closed, a buyer licence is perpetual and irrevocable on its own terms, and it isn't something you can revoke or unwind afterwards (§6.1, §7.3). Your warranties are passed through to buyers in substance, and they rely on them (§7.2).
You sign the agreement, connect GitHub, GitLab, or Bitbucket, and select the private repos you want assessed. Our partner checks, values, and grades each one. Once you've signed, every eligible repo is scrubbed, counted and presented to the labs right after analysis, whatever its grade. The labs choose what to license, so not every repo will be chosen. If a lab makes an offer, our partner concludes it on your behalf under the standing authorisation in §13.3, at the standing rates, and notifies you that your codebase is in a deal. The lab then raises a PO, typically on 60-day payment terms, and you're paid on Net 15 once the funds reach our partner.
Nothing on your side. While a lab reviews, usually 4 to 12 weeks, our partner works with it to prove the repo's training signal. These are planning ranges, not deadlines, and your dashboard shows where each repo sits.
A higher grade makes a repo more attractive to the labs, but it isn't a threshold, and the labs choose what to license, so not every repo will be chosen. What each lab wants shifts month to month.
Yes. You keep ownership, keep using the code, and keep shipping it to clients. You grant our partner a non-exclusive licence to access, package, market, license and sell the codebase to buyers, and you keep ownership of the code itself throughout (§6.2, §6.4). The licence is irrevocable while the agreement runs, and the one way to take a codebase off the table for future deals is the withdrawal right in §10.2 (see "Can we change our mind or pull a codebase?").
Two things sit outside that. If our partner acquires a codebase for its own account, or takes a licence to it for its own use, the position changes. See "Licence vs. buyout" below.
No. The licence you grant our partner is non-exclusive (§6.1), and §6.2 preserves your right to license, sell or transfer the codebase as a standalone asset yourself. In practice most agencies route everything through our partner, since that's where the buyer relationships and the packaging work sit.
There is one limit worth knowing. Under §11 you can't go around our partner to close a deal with a buyer our partner introduced you to, during the agreement or for twelve months after it ends, unless you can show you were already in documented discussions with that buyer beforehand. If you do, our partner is owed the full payment it would have earned. Buyers you found yourself are unaffected.
Yes. You keep the right to use, modify, and operate the codebase internally, and to keep using, maintaining, supporting, and deploying it for your existing and ongoing client engagements (§6.2). Nothing in the licence touches your own use of the code.
One thing to be aware of on our partner's side: to market and deliver a codebase, our partner may refine, correct, annotate and modify its own copy, and prepare packaged, redacted or white-labelled versions for sale (§6.1(a), §8). Your repositories are never written to; that work happens on our partner's copy.
The agreement already covers it. Under §12.2 you can assign the agreement to a successor in a merger, acquisition, or sale of substantially all assets, without our partner's consent; §10.1 then lets that successor terminate on 30 days' notice. So an acquirer can exit, and inherits nothing it can't walk away from. (Our partner can assign the agreement without your consent, and can sublicense and use subcontractors to exercise its rights.)
The licence travels with the agreement on a change of control, and ends whenever the successor chooses to terminate, on the same 30 days that applies to both sides. Two things survive that regardless: any buyer licence already granted, and anything our partner has licensed or acquired for its own account under §6.5.
On buyer licences specifically: one already granted survives on its own terms in every scenario, change of control or not. Where a buyer has licensed a codebase to train a model, that model is theirs. A deal already in the pipeline at the moment of the change of control can also still complete, and you're paid on it (§10.3).
Your side of the bargain is the ownership warranties, and they carry real weight, so it's worth reading §5 and §9 before you sign rather than after.
§5 asks you to warrant eight things about each codebase you submit: that you own it or hold sufficient rights to license it; that every founder, employee and contractor who touched it has assigned their IP to you; that no client or third party holds a conflicting right or is owed payment on a sale; that no third-party consent is needed; that it complies with its open-source and third-party licence terms, with no undisclosed copyleft or source-disclosure obligation; that it contains no malware; that it contains no personal data, third-party trade secrets, credentials or API keys except as disclosed; and that neither you nor it is caught by export controls or sanctions. Those warranties are treated as re-made every time one of your codebases goes into a deal (§13.9), you have a continuing duty to tell our partner promptly if any of them stops being accurate, and on reasonable request you'll provide redacted supporting documents (IP assignments, asset purchase agreements, prior licences) to evidence chain of title.
If a warranty turns out to be wrong, you indemnify our partner and, where warranties were passed through, its buyers, for the resulting claims and costs. On an infringement claim you'd be asked, at our partner's option and your expense, to secure the rights, replace or modify the affected code, or accept its removal and refund payments already received on affected licences (§9.3).
The asymmetry is worth naming. Your indemnity under §9.1 is not capped. Our partner's liability to you is: consequential and indirect losses are excluded, and its total liability is limited to what it actually paid you in the twelve months before the claim (§9.4). The platform, and every valuation, grade, score, token count and estimate on it, is provided as is (§9.5).
In practice this is why the guidance throughout is to submit only code you fully own, disclose your open-source position honestly, and flag anything client-owned or jointly owned early. The warranties are the part of this agreement with teeth.
There are four:
The dividing line: for standard non-exclusive deals, our partner handles and concludes the commercial terms on your behalf without coming back to you. For an exclusive deal or an outright acquisition, nothing happens without your signature.
So far, repos have averaged 3.2 licences each. That's an average to date, not a promise: it varies with the quality, size, domain, history and buyer demand for a codebase, and no repo is guaranteed a number of licences. The standard model is non-exclusive, so the same repo can be licensed to multiple labs and paid for several times. Labs occasionally want exclusivity on a codebase, which pays a premium; you keep ownership either way.
Anything dormant or deprecated that you own: projects that have wound down, been rebuilt from scratch, or are simply sitting unused. Commit history, tickets, and documentation all add value.
In practice that means dormant client work you fully own, internal tools, and projects you rebuilt and left behind. Team-built repos with real history (multiple contributors, pull requests, tests) are worth the most. Skip client-owned IP you don't have the rights to license, anything that is or was public (including published packages), forks and renamed open source, copies of public templates, WordPress sites, themes and plugins, AI-written code, and single-file scripts.
Not sure about a repo? Submit it. Grading is free and private, nothing enters the pipeline unless you submit it, and nothing goes to the labs until you sign. Choosing what to submit is where your control sits.
Two things, and both have a dedicated field in the submission flow: (1) any open-source or third-party components, especially copyleft (GPL/AGPL/LGPL), which buyers warrant hard against; and (2) whether the repo has ever been public. That one is an eligibility check rather than a pricing input: buyers pay specifically for code that isn't already in a public training set, so a repo that is or was public can't be licensed, and flagging it early saves you submitting something that will be declined. Type or paste these in, or attach an SBOM. This gates listing, not signing; you can sign first and fill it in as you connect repos.
Yes. Only submit code you fully own, with no client claim, NDA restriction, or contributor owed payment on it. Client-owned code needs the client's written OK before it's submitted. You pick exactly which repos are included, and the ownership warranties you make are set out in §5 of your agreement: eight of them, re-made each time a codebase goes into a deal, and backed by an uncapped indemnity. See "What are we on the hook for if something goes wrong?" above before you submit.
No. Our partner scans and scrubs secrets and personal data from its own copy of the source and the full git history, and pseudonymises contributor identities before buyer delivery. You don't need to rebuild or manually anonymise anything, and your repositories are never written to.
So submit what you own as it is. The source is what's valued, and stripping code out yourself only lowers the number.
One thing to keep in mind: §5 of the agreement still asks you to warrant that a codebase contains no personal data, third-party trade secrets, credentials or API keys except as expressly disclosed. The scrubbing pass is our partner's process, not a substitute for that warranty, so if you know something sensitive is in there, disclose it rather than relying on the pass to catch it.
No. Buyers pay specifically for code that isn't already in a public training set, so a repository that is public today is an automatic decline, and so is one that was public at any point in the past, even if it's private now. An Internet Archive crawl of the repo page proves it was public on that date, and making it private afterwards doesn't undo that.
Forks of someone else's project, renamed open source, and code already published as a package (npm, PyPI or similar) are out for the same reason. Our partner also declines WordPress sites, themes and plugins, copies (the same code twice, or a public template with little new code on top), repos with no licensable source code, and AI-written code. Everything else you own and kept private is fair game. See the Eligibility tab for the full list.
One. Because of sanctions, our partner can't work with code owners resident in Russia, and can't pay them, whatever country their bank account is in. There's no other regional restriction.
It still goes to the labs. Once you've signed, every eligible repo is presented right after analysis, whatever its grade. A higher grade makes a repo more attractive to the labs; it isn't a threshold. You don't need to fix anything first, and your repositories are never written to.
It's the work data behind the code: tickets, docs, chats, support and CRM records, and AI assistant exports, linked to your repositories. Export it from the tools your team already uses, such as Jira, Linear, Notion, Confluence, Slack, Zendesk and HubSpot, and drop the file into the Operational data tab. Most exports take minutes.
Operational data is in beta. Names, emails and keys are scrubbed, files are deleted once read, and you review every link to a repository. It's being surfaced to the labs, with no quote, valuation or promise of payment yet, but it could add value to the same codebase.
See the full list of supported tools and export formats in Operational data on the Overview tab.
Yes, and it costs real money. History is priced in full and often carries the larger half of the value, so a squashed, shallow, single-commit or freshly re-initialised copy throws those tokens away. Connect the original repository straight from GitHub, GitLab or Bitbucket, with its pull requests, review, issues and tests kept on the host. If the code lives on your own machine in git, push that repository with its history; copying the files into a new repository resets every commit date to the upload day.
Yes. There's a downloadable estimator you can run against any repository on your own machine, before you connect a provider or sign anything. It uses the same counting rules and standing rates as the platform, and your code stays on your machine. Your Pangea.ai contact can send you the command.
It prices at the standing rates and prints an estimate, not an offer. Pass several repos, or a folder of them, for a row per repo and a total; it also prints the counting rule and the text it left out under each one, so a small number explains itself.
GitHub, GitLab, and Bitbucket; you can connect more than one.
As little as you want to give, and read-only. You choose which repositories: connecting GitHub installs our partner's app on the repos you select, with read-only access to code, metadata, pull requests and issues in those repositories. Connecting makes repositories available to pick; only the ones you submit are copied for analysis. You can change that list, or remove our partner entirely, from your GitHub settings at any time.
Our partner scrubs, values and grades its copy of what you submit, and never writes to your repositories. Nothing you don't select is touched. The same applies on GitLab and Bitbucket: access is scoped to the repos you pick, and revocable at your provider any time.
A few minutes to connect and see estimates. You can submit several repos at once and add more any time.
First, a low grade isn't a rejection: every eligible repo goes to the labs once you've signed, whatever its grade. Nor is a "Low likelihood of licensing" flag: context with something verifiable can clear it. An outright decline is a different thing: a repo that is or was public, a published package, a fork or renamed open source, a copy, a WordPress site, theme or plugin, AI-written code, a repo with no licensable source code, or client-owned or third-party code you don't have the rights to license. A decline never affects your other submissions, and where reasonable our partner explains the reason.
Two things to be straight about. Our partner is under no obligation to accept, list, market or sell any codebase, and can decline, defer, remove or discontinue one at its own discretion (§4, §13.10). There's no minimum number of deals, no minimum revenue and no guaranteed listing period. It can also suspend or remove a codebase immediately where it reasonably judges there's an infringement, malware, undisclosed personal data or credentials, a legal, security or reputational risk, or a third-party claim; you get prompt notice and, where practicable, a chance to fix it.
Our partner does. The NDA and licence are one combined agreement, already countersigned; you sign once, and can download your copy any time.
You can also read it before you sign anything: ask your Pangea.ai contact for a copy of the current Codebase Agreement and send it to whoever needs to review it. The signing page shows the same document, and your signed copy sits on that page afterwards.
Yes. Your team joins under one organization, everyone connects their own Git accounts, and repos and payouts roll up in one place. No duplicate accounts needed.
Our partner doesn't pre-filter by grade: once you've signed, every eligible repo goes to the labs, and the labs choose what to license. Repos flagged "Low likelihood of licensing" wait until they're cleared. Each repo is graded first. A model reads the cleaned copy and scores architecture, tests, documentation and history against a fixed rubric, then gives it a letter grade. A higher grade makes a repo more attractive; it isn't a threshold. A repo is never built or run to be graded.
Valuation counts genuine source code at the current head plus useful code in the git history. Markup, data, config and docs count up to 10× the code beside them. Generated files, vendored dependencies, build output, binaries, archives and data dumps don't count as source, so padding a repo doesn't lift its number. Third-party code copied straight into your source folders stays in, under its own licence, so disclose it.
The whole repo is assessed as one codebase, including its genuine source and full git history. If several people contributed to the same project, their combined work and history are assessed together. Team-built projects are generally more attractive to labs than solo ones, because they carry richer collaboration signals: multiple contributors, pull requests, reviews, bug fixes, and a more meaningful development history. Individual repos can still be submitted, but genuine team projects are more likely to attract buyer interest. If important code lives only on separate, unmerged branches, confirm with your Pangea.ai contact how those branches will be handled before submitting.
Only the repos you choose. Repos you don't pick are never copied, and you can revoke access at your provider any time.
What you do submit can be seen by our partner and the service providers involved in preparing it, and by prospective buyers under written confidentiality obligations. A model reads the code during grading. This is confidential licensing, not publishing your repository as open source.
The agreement also permits disclosure to a defined set of others: affiliates and sublicensees, infrastructure and data-room providers, financing sources in a corporate transaction, and vetted prospective buyers, each bound by confidentiality at least as protective as your own. The Code Handling & Security tab sets out the full list.
Yes. Both sides are under mutual confidentiality; access is limited to people with a need to know who are bound by equivalent terms, and our partner won't expose your code publicly except as needed to market or deliver it to a buyer under confidentiality or licence. Confidentiality obligations run for five years from disclosure (longer for trade secrets, which stay protected as long as they remain trade secrets). If either side becomes aware of unauthorised access or disclosure, it must notify the other in writing within 72 hours and cooperate on investigating and remediating it.
The existence and terms of the relationship aren't disclosed publicly without your consent, and any buyer is bound by a confidentiality obligation or licence before seeing the code. The scrubbing pass also pseudonymises contributor identities across the code and the git history, so the commit trail doesn't carry your team's names to a lab.
Yes, on two levels. In the product, you can remove any codebase yourself, at any point before it's licensed; it hard-deletes the stored copy, with no notice needed. Contractually, §10.2 gives you a withdrawal right on 30 days' written notice, and either party can end the whole agreement on 30 days' notice (§10.1).
What withdrawal doesn't reach, so there are no surprises: a buyer licence already granted; an active, documented buyer transaction or negotiation already in progress when you give notice, or that starts during the 30 days (a "Pipeline Transaction"); our partner's right to keep administering licences already out there; and anything our partner has licensed or acquired for its own account under §6.5. For 90 days after termination or withdrawal (the "Tail Period"), our partner can still close those pipeline deals, and you're paid on them on the normal terms. During that window you agree not to approach the buyers involved directly (§10.3).
On written request, our partner returns or destroys your codebase and related confidential information. That's subject to what it must keep by law, what sits in routine archival or backup, what it needs to honour buyer licences already granted, and anything under §6.5, all of which stays covered by the confidentiality terms (§10.5). In practice, on request our partner deletes every stored copy of the code and confirms in writing. No separate backups of code are kept; what remains is the repository record in the database's rolling backups until they expire, and a short removal record (name, grade, value, reason, date).
Access is read-only and limited to the repositories you select. Our partner works on a separate copy: it scans and scrubs secrets and personal data from that copy of the source and git history, removes vendored dependencies, build output, compiled packages and archives from every commit, and pseudonymises contributor identities before buyer delivery. A model reads the cleaned copy to grade it against a fixed rubric; grading never builds or runs the code.
Code travels over HTTPS and is encrypted at rest. Prospective buyers see it only under written confidentiality obligations, and any licence is on the terms our partner agrees with them. See the Security tab for the detail.
Yes, it can stay completely non-public. The relationship, your identity as the code owner, and the commercial terms aren't disclosed publicly, and buyers are bound by confidentiality before they receive any code. You keep ownership under a standard licence and can carry on using, modifying, and deploying the code. If the codebase or the company behind it is later sold, existing licences may need to be disclosed privately during legal due diligence, but they never have to be announced publicly.
The rates are written into the agreement itself. §13.2 sets standing rates of $100 per million source tokens and $40 per million git-history tokens, and states that's the basis on which our partner expects to pay for a standard non-exclusive licence. Our partner can change them on 30 days' notice, and a change never affects a licence already granted; a deal is paid at the rate in force when it was granted.
Two honest caveats. The standing rates are not a fixed price, a minimum, or a guarantee for any particular deal: where a transaction's terms differ from a standard non-exclusive licence, our partner may set a different amount, acting reasonably and in good faith, and will tell you that amount at or before payment. And the token count the rate is applied to is determined by our partner's own analysis (§4), which decides what's counted and what's excluded.
There is no per-deal sign-off on a standard licence. Your signature on the agreement is standing authorisation for each non-exclusive buyer licence our partner grants (§13.3); you're notified on the platform or by email when one of your codebases is included in a deal (§13.9). A separate signed confirmation is required only for an exclusive licence, a deal that would restrict the rights you keep under §6.2, or (at our partner's option) a deal priced off the standing rates (§13.4). Your control over whether a codebase is offered at all is the withdrawal right in §10.2.
Payment is owed once a deal closes: the buyer licence is signed and our partner has the first cleared, non-refundable funds in hand (§13.5). It's paid out of what our partner actually receives for that deal and never more than that. If a buyer's payment is later refunded, charged back or clawed back, our partner can recover the proportionate amount from future payments, and it can net off anything you owe it under the agreement.
There's no upfront fee: connecting, submitting and grading cost nothing, and there's no obligation to submit anything. The standing rates are the basis for your payout, not a buyer price from which a platform commission is deducted. Pangea.ai is compensated separately by our partner, so nothing comes out of your payout for us. Receiving-bank or currency-conversion fees and taxes are yours.
You're paid on Net 15 terms: within 15 days of our partner receiving payment from the buyer. Labs typically raise a PO on around 60-day terms, so that's the wait before funds reach our partner; once they do, your Net 15 clock starts. Where a buyer pays in instalments, a proportionate part of your payment accrues as each one lands. Payout details go in your dashboard, and you're paid in US dollars by ACH or wire to the account you designate and verify there.
Two practical conditions. Our partner needs your tax documentation on file (a W-9, or a W-8BEN / W-8BEN-E if you're outside the US) along with a verified payout account, and can hold payment until both are in place (§13.7). Where law requires tax to be withheld, it's withheld and remitted, and you get the form showing it. Receiving-bank and currency-conversion charges are yours. Payment is made to your business as income.
Your dashboard carries a record for every buyer licence covering one of your codebases: the codebases included, the licence type, the amount you're paid, and the date paid (§13.8), plus funnel status and your total earned.
Two things are outside it. The buyer's identity and the terms of their licence are confidential, and you're not entitled to an accounting of what our partner received from the buyer, so the record shows your payment, not the deal's economics. Where a single deal covers codebases from more than one owner, or is priced as one figure across several codebases, the consideration is split across them in proportion to their total token counts (§13.5).
How our partner handles a codebase you submit for licensing: where it goes, who can see it, what is and isn't done with it, and how it's removed. This sits on top of the protections in your signed agreement: mutual confidentiality, a non-exclusive licence, and return or destruction on request.
Secrets and personal data are scrubbed from our partner's own copy of the code and the full git history, and contributor identities pseudonymised before buyer delivery. Your repositories are never written to.
Grading does not build or run the repository. It reads the cleaned copy against a fixed rubric, nothing more.
A language model reads the cleaned copy to score it against a fixed rubric, reached through model routing providers.
Code is transferred over HTTPS and stored in cloud object storage, encrypted at rest by the storage provider. The raw pull-request capture and the pseudonym key are also encrypted by our partner (AES-256-GCM).
The GitHub App has read-only access to code, metadata, pull requests and issues in the repositories you select, and does not write to them. Repositories you don't select aren't accessed. Revoking access in your GitHub settings stops future access but doesn't recall copies or licences already granted.
Your code can be seen by our partner and the service providers involved in preparing it, and by prospective buyers under written confidentiality obligations. A model reads the code during grading. This is confidential licensing, not publishing your repository as open source. The existence and terms of your relationship with our partner are not disclosed publicly without your consent.
The agreement draws the circle slightly wider than the internal team, and it's worth knowing where it lands. Beyond staff and contractors with a need to know, §3.3 permits disclosure to our partner's affiliates and sublicensees; to financing sources and potential acquirers or investors in connection with a corporate transaction; to platform and infrastructure providers; to bona fide prospective buyers, limited to the minimum reasonably necessary and only once they are under a written confidentiality obligation or licence; and to data rooms, repository access tools and secure file-sharing providers, solely to provide those services. In every case they must be bound by confidentiality obligations at least as protective as your own. §3.7 also lets either side's people use general ideas, concepts and know-how retained in their unaided memory, which does not extend to reproducing source code or documentation.
Scrubbing. Our partner scans and scrubs secrets and personal data from its copy of the source and git history, and pseudonymises contributor identities before buyer delivery. The scrub also removes vendored dependencies, build output, compiled packages and archives from every commit. You don't need to rebuild or manually anonymise a repo, and our partner never pushes changes to your repositories.
The sequence runs: an exposure check; a copy; the original stored separately and never delivered; cleaning; counting and grading on the cleaned copy; delivery packages built from it. Detection reads the original, using three secret scanners, a model check that sees each candidate with its value masked, and a personal-data detector.
Grading. A language model reads the cleaned copy, reached through model routing providers, and scores it against a fixed rubric. It sees the repository name, rubric statistics and files it chooses to open, up to 600 lines each. Smaller steps, such as the description and industry label, send excerpts like the first 3,000 characters of the README, also from the cleaned copy. Grading does not build or run the repository.
If you upload operational data (tickets, docs, chats and other work data linked to your repositories), names, emails and keys are scrubbed, files are deleted once read, and you review every link to a repository. It's experimental: it's being surfaced to the labs, with no quote, valuation or promise of payment yet.
Repositories you don't select are never copied. For a repo you submit, the code is held in cloud object storage in Eastern North America, and the repository record (statistics, grade, descriptions, file paths) in a managed database. Analysis runs in isolated cloud containers, the largest repos on our partner's own machine, and the working copy is deleted at the end of each run. Because a codebase can be licensed to more than one buyer, accepted submissions stay in the pipeline while they're listed.
Before you sign, your repos are used only to analyse, grade and value them, and are treated as Confidential Information under §3 of the Codebase Agreement, as if signed. Nothing goes to the labs or anyone else until you sign. If you don't go ahead, the stored copy is deleted and our partner confirms the deletion in writing.
You stay in control the entire time. You can hard-delete any codebase yourself, in the product, at any point before it's licensed. On request, our partner deletes every stored copy of the code (original, cleaned copy, delivery packages and pull-request records) and confirms in writing. Storage isn't versioned and no separate backups of code are kept; what remains is the repository record in the database's rolling backups until they expire, and a short removal record (name, grade, value, reason, date).
Signed repos can be withdrawn from future listing on 30 days' written notice. Existing buyer licences continue, and documented deals already in progress may still close during the 90-day tail period. Withdrawal doesn't recall code already licensed or undo our partner's own paid licence or acquisition. Contractually, return or destruction on written request excepts what our partner must keep by law, what sits in routine archival or backup, what it needs to administer buyer licences already granted, and anything it has licensed or acquired under §6.5.
Our partner describes the providers involved by category.
| Purpose | Provider type |
|---|---|
| Source connection | GitHub, GitLab or Bitbucket, for the repos you select only |
| Code storage | Cloud object storage in Eastern North America, encrypted at rest |
| Repository record | Managed database (statistics, grade, descriptions, file paths) |
| Analysis | Isolated cloud containers; the largest repos on our partner's own machine |
| Grading | Language models reached through model routing providers |