Built AI Agent in a weekend.
Shipped it to production.
Now what?
→ Did it take the right action?
→ Did it miss a step it shouldn't have?
→ Should you have shipped it at all?
The tools that got you here weren't built for what comes next.
No spam. First to know when we launch.
Define success before your devs touch code. Turn fuzzy requirements into testable contracts your whole team can read.
We translate metrics into business impact. "1 in 6 responses will be wrong. Do we ship?" Now you can actually answer that.
Automated gates catch quality degradation in minutes — not after a customer complains in production.
A guided flow that helps you extract ground truth from domain experts. Turn a fuzzy feature idea into a production-ready eval suite — no engineering degree required.
Run evals locally or as a CI/CD deployment gate. No forking, no bloat — just a quality gate that fits your existing workflow.
Validate ground truth, review edge cases, and compare agent versions side-by-side — without touching the terminal. Built for PMs who need to see, not just trust.
Instrument once. Get diagnostic traces in development and full observability in production. The feedback loop is built in — not bolted on.
Your evaluation logic belongs in your repository. Sigmaflo uses a simple YAML schema that lives alongside your agent code — versioned, shared, and readable by everyone.
# agent_eval.yaml metrics: - name: action_correctness type: binary_classification thresholds: precision: 0.95 recall: 0.80 quality_gate: strategy: hold_on_fail report_verbosity: business on_fail: block_deploy: true notify: ["[email protected]"]