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AI-native source control

The GitHub alternative built for the agent era.

Every incumbent is racing to add AI. Copilot, agents, AI review, all bolted onto the same substrate they have always had: files, diffs, and pull requests. KinLab changes the substrate itself. Your code becomes a living semantic graph, not files and diffs with AI on top. Review, governance, and provenance finally understand the code.

The incumbents bolt AI onto files and diffs.

GitHub, and the AI tools orbiting it, are layering Copilot, coding agents, and AI review onto a model designed for humans hand-editing text: files, line-based diffs, and pull requests. It is a remarkable layer on a substrate that has no idea what a function, a type, or a contract is. The intelligence is bolted on. The foundation never changed.

AI on top of a text substrate

Every AI feature on a file-and-diff platform has to re-derive structure from text on demand, because the platform stores blobs and trees, not meaning. That is a ceiling no amount of model quality lifts.

Built for humans typing, not agents reasoning

Pull requests, line comments, and commit history assume a person edits and a person reviews. When agents write most of the code, the unit of work shifts from lines to entities, and the old substrate cannot express it.

The substrate difference

KinLab stores your code as a semantic graph. The functions, types, and contracts, and the relationships between them, are the canonical truth, with files and diffs as views derived from it. Once the substrate understands your code, everything built on it does too: review reads impact, agents get structural context, and provenance attaches to the entity that changed. This is the one thing an incumbent cannot retrofit, because it is the foundation, not a feature.

KinLab vs GitHub, by substrate

The differences are not features stacked side by side. They fall out of what the platform fundamentally stores.

Review unit
Impact across the graph: changed entities, their dependents, contracts, and tests.
A text diff. Added and removed lines in a file window.
Agent access
A governed, shared code graph: scoped intents, coordination, provenance per change.
No native graph for agents; tools bolt onto files, diffs, and the API.
Provenance
Per-entity. Who or which agent changed each function, type, and contract, and why.
Per-commit. Authorship attaches to a commit, not to the unit of meaning.
Substrate
A semantic graph of entities and relationships, the source of truth.
Files and diffs. The same blob-and-tree model, with AI layered on top.
Licensing
Open-core. An Apache-2.0 Kin substrate underneath the hosted control plane.
Proprietary platform; the AI layer is a closed paid add-on.

It coexists with Git. It is not a rip-and-replace.

"Alternative" does not mean "throw away your history on day one." KinLab runs alongside your existing .git. The graph is built from and stays reconciled with your repository, so you adopt the semantic substrate without abandoning the workflows, remotes, and history your team already depends on. The open Kin tooling is the on-ramp. The migration is incremental, not a cliff.

Cross-repo and org-wide blast-radius analysis is on the roadmap. We describe it as the vision, not a shipped metric.

Pre-release · early access by request

Change the substrate, not just the tooling.

KinLab is the hosted, AI-native source-control and collaboration platform built on the open-core Kin substrate. Early access is granted by request while the platform matures.

Explore the open core, read the reproducible proof, or browse the Kin ecosystem.