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CodeAlive

Hundreds of repos, one searchable knowledge graph

AI agents only see the file they're editing. CodeAlive links hundreds of repos into one knowledge graph so the agent pulls the right interface from the right service.

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Agents only see what's in the current window

  • Modern systems are split across hundreds of repositories (microservices, libraries, schemas).
  • AI coding agents only see the code in the current window.
  • "How do I consume this domain event?" requires looking at a different repo.
  • Interfaces and contracts drift because agents guess instead of checking the source.
  • Reusing logic is impossible if the agent doesn't know it exists in common-utils.

All your repos, one graph the agent can query

CodeAlive indexes all your repos into one graph. When an agent needs a protobuf definition or a domain event from another service, it pulls the actual file from CodeAlive instead of guessing.

Cross-repo context, on demand

Domain Event Tracing

"I'm publishing OrderCreated in order-service. Show me how shipping-service consumes it."

Shared Contracts

Fetch current TypeScript interfaces or Protocol Buffers from a central schema repo.

Library Discovery

"Do we have a standard way to handle retries?" Found in the platform-lib repo, not reinvented.

Zero Hallucination

Agents import actual existing classes instead of inventing new ones.

Contract Awareness

When modifying an API, the agent sees who calls it across all other repos.

Consistent Patterns

"Use the logging pattern defined in core-infra." Agents follow real conventions.

From a prompt to correctly wired code

  1. 1

    Developer asks

    "Create a listener for UserRegistered event."

  2. 2

    Agent retrieves

    Pulls the UserRegistered definition from user-domain repo via CodeAlive.

  3. 3

    Agent generates

    Writes consumer code using the exact fields and types from the external repo.

  4. 4

    Agent extends

    Looks up the email-service client SDK in platform-clients and generates the correct call.

What changes for your agents and your team

  • Agents call real interfaces and consume real event shapes instead of guessing.
  • Agents pick the right pattern instead of inventing a new one.
  • Agents and humans work in one query interface across all repos.

What multi-repo intelligence looks like

Graph visualization of a domain event flowing across multiple microservice repositories
Multi-repo dependency graph showing event flow.
AI agent chat showing retrieval of an external file from a different repository
AI agent retrieving a file from a different repo.
Notification overlay showing which external references the agent pulled into context
"Context Retrieved" notification showing external references.

Cross-repo context, on every agent call

Agents (and humans) see the full system, not one file at a time.

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