Tetrix — Unified Knowledge Map of Your System for AI
Your entire system unified for AI.
Tetrix connects code, services, and infrastructure into a unified knowledge map of your system. AI queries it for full visibility.
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API V3 Migration
If we deprecate the v2 Auth payload in @company-web/nuxt-marketing-site, what downstream services in @platform/remix-auth-service will break?
12:32 PM
Traversing
- Locating [V2 Auth payload] in pre-mapped global graph
- Traversing API contracts across service boundaries
- Cross-referencing live infrastructure state for remix-auth-service
- Simulating deprecation impact
- Injecting absolute architectural context
Context boundaries established
Deprecating the v2 Auth payload in @company-web/nuxt-marketing-site will cause 3 critical breaking changes in @platform/remix-auth-service.
Direct Impact:
- SessionMiddleware.ts: Will fail at session validation. It explicitly requires the
device_idfield unique to the v2 payload structure. - POST /api/auth/refresh: The route handler's Zod schema strictly validates against the v2 token shape. It will begin throwing 400 Bad Request errors for all marketing site traffic.
Indirect Impact (Blast Radius):
- AuditLogger.ts: Will silently fail. It maps the v2 payload's
session_stringdirectly to the Postgresuser_loginsschema.
Required Migration:
Before deprecating the payload on the client, you must update the Zod validation schema in @platform/remix-auth-service to accept the v3 payload and ensure AuditLogger.ts can parse the new token structure.
A knowledge infrastructure
Modern software systems are too big and distributed for AI.
Tetrix maps the fragmented layers into a persistent context.
- Universal context
- Architectural awareness
- Deterministic map
- Five retrieval paths
Every source type. One searchable ecosystem.
Natively ingest source code, infrastructure, engineering standards, and every artifact your team produces. No connectors, no manual syncing — Tetrix indexes your full system automatically.
Code and infrastructure in the same reasoning path.
AI sees beyond code files. Cloud resources, service topologies, and Kubernetes configurations mapped alongside your codebase — so every answer reflects your actual architecture.
Pre-mapped at index time, not on every query.
Every function, class, and dependency is structurally parsed into a persistent knowledge graph. Relationships are pre-mapped at index time through a deterministic process — no inference, no drift.
Comprehensive context for every answer.
Every query routes through five retrieval paths simultaneously: code search, symbol traversal, dependency trees, semantic matching, and blast-radius analysis.
How to use this knowledge map?
Use your system knowledge anywhere.
Deep Research
Execute multi-hop reasoning across your entire architecture. Specialized agents traverse your deterministic graph to map dependencies and blast radius.
What you can now ask
Questions you couldn't ask before, your tools answer it now with Tetrix.
- What services will break if I change this API endpoint? (Cross-repo analysis)
- Show me all places this function is called across our codebase. (Impact analysis)
- What's the performance impact of this database query change? (Migration impact)
- Which teams own the code that depends on this service? (Ownership mapping)
- Is this deprecated API still being called anywhere in production? (Dead code detection)
- What changed in this service that could explain the latency spike? (Root cause analysis)
- How do I safely roll back this infrastructure change? (Rollback planning)