Fragmented tools
Each CLI, IDE, and local model reports usage differently, or not at all.

AI observability for every team
Observagent unifies logs, metrics, and traces from every agent, model, and integration, so you see cost, performance, and reliability before your customers do.
Why it matters
Teams deploy coding agents, assistants, and local models faster than they can answer basic questions about their behavior.
Each CLI, IDE, and local model reports usage differently, or not at all.
Token spend, quota, and model usage stay hidden until the invoice arrives.
No shared view shows which team, project, or agent drives usage and errors.
Failed requests and slow responses are hard to trace without a shared view of agent activity.
One operational view
Cost and quota
Follow estimated model cost, token mix, cache use, and quota pace before spending becomes a surprise.
Recommended action
Reduce broad context, route routine requests efficiently, and fix failing plugin loops.
The platform
OTLP logs, metrics, and traces over HTTPS from any OpenTelemetry source.
Resolve users, agents, sessions, models, projects, and departments automatically.
Connect tokens, cost, quota, and cache use to the work that generated them.
Keep each customer in an isolated database with content capture off by default.
One export protocol
More than nine integrations feed one normalized OpenTelemetry pipeline.
Trust
Operational visibility should not require giving up control of your data.
Every customer receives a separate database, not a shared table filtered by row.
Prompts, responses, and messages are removed before storage unless you enable them.
Email and password authentication includes TOTP multi-factor protection.
Privacy, deletion requests, and data processing procedures are built into operations.