1. Ingest
Connect engineering systems and ingest normalized events continuously.
Context infrastructure for engineering orgs
Time-aware context for incidents, changes, and AI-driven workflows
Weavera reconstructs a live knowledge graph from code, deployments, cloud resources, logs, and metrics so every investigation starts from the right context.
Built for teams that run production systems with AI in the loop.
How it works
2. Project
Build time-aware entities and relationships into a queryable graph model.
3. Reason
Use APIs and agents to investigate incidents and plan changes with context.
Context graph, not another silo
External tools remain source of truth. Weavera ingests events, models relationships over time, and exposes high-signal context to operators and AI.
Built for real engineering flow
From incidents to architecture refactors, Weavera points to the right runtime, deployment, commit, and timeline instantly.
Design principles
- Event-sourced core with time-aware projections
- Connector-first ingestion across engineering systems
- AI-first query surface for real operational context
What teams use Weavera for
Incident response with context
Correlate deployments, infra changes, and observability signals in one timeline before opening every tool.
Architecture change confidence
Reason about service relationships and active environments with current state and historical evolution.
AI agent effectiveness
Give coding agents the missing org context so they investigate and implement with less drift and fewer tokens.
What Weavera is and is not
Is
A context layer that connects code, deployments, infra, and observability history into a queryable, time-aware graph.
Is not
A replacement for your observability stack, incident manager, or code search tools. It orchestrates context across them.
Request a live walkthrough
We will tailor the session to your current toolchain and show how Weavera can reduce time-to-understanding for incidents and architecture decisions.