Garlic: Repository Intelligence for AI Engineering Systems.
Specialize AI systems on your architecture, workflows, patterns, and engineering practices — so they behave less like generic copilots and more like engineers who understand your actual systems.
Architecture intelligence
Garlic, traversing a real engineering organization.
Watch Garlic extract repository intelligence — mapping services, contracts, dependencies, and ownership — and assemble a context pack ready for AI consumption.
Simulated visualization · representative of how Garlic constructs repository intelligence.
Core capabilities
Eight layers of repository intelligence.
Garlic doesn't just index code — it learns how your engineering organization actually works, and turns that into grounded context for AI systems.
Why generic AI fails
Generic AI doesn't know your systems.
Foundation models are trained on the public internet — not on your monorepo, your service contracts, your deploy rituals, or your team's hard-won conventions. That gap is where AI engineering systems fail.
Generic AI systems lack…
- Repository understanding — they treat your code like any other
- Architectural context — they miss service boundaries and contracts
- Engineering conventions — they default to generic patterns
- Workflow awareness — they don't know your release rituals
- Historical reasoning — they can't see why decisions were made
Continuous repository intelligence
- Specialized on your architecture, not the public corpus
- Grounded in real service boundaries, contracts, and dependencies
- Aware of your team's conventions, naming, and structural patterns
- Maps test, release, and deploy workflows your team actually follows
- Continuously refreshed as your codebase evolves
Garlic solves this through continuous repository intelligence generation — turning your codebase into structured context that AI systems can actually reason over.
Example intelligence outputs
Structured intelligence, ready for AI consumption.
Every Garlic-indexed repository produces a layered set of intelligence artifacts — each consumable by ARES, Hive, and other AI engineering systems.
Enterprise positioning
Your engineering organization already contains institutional intelligence. Garlic makes it usable by AI systems.
Large codebases
Built for codebases at the scale where general-purpose AI tools collapse. Millions of LOC, indexed and stayed-in-sync.
Monorepos
Maps boundaries inside the monorepo — services, libraries, contracts — without losing the connections between them.
Distributed architectures
Reasons across service contracts, async edges, and cross-repo dependencies — the parts that break when AI guesses.
Engineering onboarding
Compresses the time it takes a new engineer — or a new AI agent — to become productive in your codebase.
AI reliability
Grounded context dramatically reduces hallucinations and architectural drift in AI-generated changes.
Context scaling
Designed for orgs where useful context is far larger than any model's window — without lossy summarization.
Integrations
Wired into your AI and engineering stack.
Garlic is the intelligence layer underneath Momentum AI's engineering products — and plugs into the systems your team already runs.
Garlic exposes intelligence as structured artifacts — consumable by ARES (IDE), Hive (workflows), and any AI system your team builds on top of Momentum AI.
Private preview
Turn your repository into engineering intelligence.
Garlic is in private preview with enterprises specializing AI systems on their own architectures. Request a demo, or come talk to us.