Production SRE
for AI agents
RouteIQ detects failures, diagnoses agent behavior, and automatically intervenes before bad runs become customer incidents. One OpenTelemetry endpoint. Every framework, every cloud, every model. It helps you see what your agents are doing, why they're doing it, and when they start drifting.
OpenAI · Anthropic · LangGraph · CrewAI · OpenTelemetry
Agents online
38/ 41
3 in maintenance window
Task completion
89.7%n=14,228 · 24h
Open drift signals
2
↗ checking research-v3
Spend MTD
$2,684.31
on track for ~$3.9k
| Agent | Completion | Status | $/task |
|---|---|---|---|
| checkout-v2.3 | 93.1% | ● ok | $0.213 |
| support-en-eu | 96.4% | ● ok | $0.087 |
| research-v3(canary) | 77.9% | ● watch | $1.842 |
| fraud-pre-auth | 88.4% | ● slo breach | $0.610 |
| contracts-extract | 94.2% | ● ok | $0.341 |
drift on research-v3 surfaced 11m ago · likely retrieval index v2.4 (deployed 03:42 UTC)
The gap in the stack
Teams can trace agents.
Few can run them reliably.
Most teams have evals, traces, dashboards, and prompt experiments. That helps during development, but production failures happen in a different layer.
- Agents loop, drift from goals, and silently fail after looking healthy in logs.
- Per-call error rates hide compounding failure across reasoning steps.
- Hallucination spikes go undetected for weeks.
- Prompt and model drift silently degrade quality.
- Token spend balloons inside reasoning loops nobody can see.
- Compliance teams can't audit decisions that already happened.
Existing observability answers:
- Which prompt or tool call happened?
- How long did this run take?
- Which runs failed?
RouteIQ answers:
- Will this agent miss its reliability SLO?
- Did the agent drift from the user goal?
- Which handoff broke the workflow?
- Retry, downgrade autonomy, or escalate?
How it works
Agents send telemetry once.
Everything else stays in your VPC.
Agent SDK sends to the RouteIQ ingest gateway. ClickHouse and the dashboard run inside your network — giving you org-scoped insights without data leaving your infrastructure.
ingest.routeiq.dev
HTTPS · gRPC · OTel
ClickHouse
otel_traces · logs
Define “good”
SLOs: task success, p95, cost, hallucination rate
Dashboard
Get answers, not just data.
When something drifts, RouteIQ surfaces the reasoning context behind the anomaly.
but“tool X failed on 43% of calls with customer PII after prompt v1.4 Tuesday”
import routeiq routeiq.configure(agent_id="support-agent", endpoint="https://ingest.routeiq.dev") @routeiq.instrument async def run_agent(query: str) → str: ...
Platform
Three layers of production agent reliability
Agent Reliability Control Plane
Monitor agent systems against reliability, latency, safety, and cost objectives. Trigger fallbacks, approvals, rollbacks, and escalations before incidents spread.
- Task success, latency, cost SLOs
- Real-time anomaly detection
- Fallback orchestration
- Version canaries
State Debugger
Inspect how an agent's plan, memory, and constraints changed at every step. Diagnose loops, stale context, and reasoning-to-action mismatches.
- State diff timeline
- Goal drift analysis
- Memory lineage
- Root cause scoring
Multi-Agent Reliability
Understand coordination across delegation chains and handoff boundaries. Surface context loss, ping-pong loops, deadlocks, and role violations.
- Handoff completeness metrics
- Agent interaction graph
- Role boundary enforcement
- Deadlock detection
Use cases
For teams running agents in production
Customer Support Agents
Detect silent resolution failures, escalating loops, and policy breaches before they degrade customer experience.
Internal Copilots
Track tool misuse, no-progress runs, and risky actions across workflows that touch business systems.
Research & Analysis
Monitor retrieval quality, plan drift, stale memory, and model regressions across long-running tasks.
Enterprise Automation
Apply approval gates, rollback controls, and policy-aware intervention where governance requirements are strict.
Run AI agents with
production-grade reliability
Move from observability to operational control. Detect failures earlier, debug faster, and ship with the safeguards production demands.
- Works with LangGraph, OpenAI Agents SDK, CrewAI, and custom runtimes
- 3-line SDK integration — no infra changes required
- ClickHouse and dashboard run inside your VPC
- Multicloud — AWS, Azure, GCP, on-prem
- Reply within one business day