trace.ai gives you real-time visibility into every LLM call — tokens, cost, latency, anomaly scores, and AI-powered root cause analysis. Two lines of code to get started.
// Before const anthropic = new Anthropic() // After — that's literally it const tracer = new Tracer({ apiKey }) const anthropic = tracer.wrapAnthropic(new Anthropic()) // Every call is now traced ✦
< 1ms
Overhead per call
4-layer
Anomaly scoring
Real-time
Dashboard updates
1-click
AI root cause analysis
From raw token counts to intelligent anomaly detection — trace.ai covers the full observability stack for LLM-powered products.
Every LLM call captured instantly — tokens, latency, cost, model, prompt, and output. Streamed live to your dashboard.
Detects hard failures, format violations, output shape mismatches, and numeric anomalies. Scored, ranked, and explained.
One click runs claude-sonnet-4-6 over your entire run. It reads every step and tells you exactly what went wrong and why.
Per-step and per-run cost breakdown. Spot regressions before they hit your bill. Track model distribution over time.
Critical anomalies fire to your Slack channel and your Sentry project — with full context, scores, and step details.
Isolate projects, teams, and environments. Each key routes to its own dashboard with its own alert configuration.
Hallucinations, malformed JSON, token accounting mismatches, output shape drift — these don't throw exceptions. They silently corrupt your pipeline. trace.ai's scoring engine catches them before your users do.
Hard failures
Status errors, missing output, token ghosts
Format violations
JSON contract broken, unexpected output type
Shape fingerprinting
Output structure doesn't match what the prompt asked for
Numeric anomalies
Latency spikes, cost outliers, token ratio drift
The pipeline failed in generate-response, but the root cause originated in parse-request — malformed JSON output propagated silently through enrich-context and caused a null-reference crash downstream.
trace.ai alerts fit into the tools your team already uses. Set them up in under a minute from your project settings.
Webhook integration
Paste your Slack Incoming Webhook URL and get instant alerts when a step errors or your error rate crosses a threshold — right in your team channel.
DSN integration
Add your project's Sentry DSN and anomalies fire directly into your Sentry issues feed — with full context, condition codes, and scores attached as tags.
Both integrations are configured per-project in Settings → Integrations. No code changes needed.
No agents, no config files, no infra to manage.
npm install @trace-ai/sdk
const anthropic = tracer.wrapAnthropic(new Anthropic())
// Every call now appears in // trace.ai in real time