AgentOps
Run AI agents in production with telemetry, regression evals, and guardrails. We add observability, prompt versioning, and one-click rollbacks before launch.
Service overview
Reply within 1 business day
Our process for agentops
A fixed four-step path from first call to production — with weekly demos and a hard launch date.
Discovery & data audit
We map your use case, evaluate data readiness, and define success metrics and guardrails up front.
Deliverable
Feasibility report & eval plan
Model & pipeline design
We architect the retrieval, model, and orchestration layers with cost, latency, and safety in mind.
Deliverable
Architecture & prompt/eval harness
Build, evaluate & harden
We build with a regression eval suite, add guardrails against prompt injection and PII leaks, and tune quality.
Deliverable
Tested system & eval dashboard
Deploy & monitor
We ship to production with telemetry, cost controls, and one-click rollback, then hand over full ownership.
Deliverable
Live system, docs & handover
See where your project fits.
Book your systems auditOperating agents in production
Building an agent demo is easy; keeping it running in production is hard. We provide the infrastructure needed to manage autonomous systems reliably—observability, evaluation, and safety—allowing teams to deploy agents with the same confidence as standard services.
- Telemetry: Full instrumentation for tool calls, token use, latency, and cost. We integrate with OpenTelemetry to provide clear visibility into every agent run.
- Evaluation: Regression tests for every deployment. We compare agent trajectories and outputs across model versions to ensure performance doesn't degrade.
- Guardrails: Safety layers that prevent prompt injection, restrict tool access, and filter PII. We include deterministic rules to escalate to human review when an agent is unsure.
- Lifecycle management: Tools for prompt versioning, reproducible runs, and one-click rollbacks. We treat agent logic as core infrastructure.
Operational standards
We instrument every agent before it goes live. No system is deployed without a monitoring dashboard, a rollback strategy, and passing regression tests.
- Observability: Track latency, cost, and success rates for every tool and agent, with full logs for auditing.
- Reliability: Support for canary and shadow deployments with automatic rollbacks if performance drops.
- Safety: Enforce strict policies, rate limits, and tool sandboxing to keep operations secure.
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Learn moreReady to build agentops?
Every project starts with a clear scope and a fixed timeline. Tell us what you're building and we'll reply within one business day.