Build AI quality into every release.
Test every change, catch regressions before release, trace failures in production, and improve the next version without stitching together more tools.
See how it works87%
of developers are concerned about the accuracy of AI agents
Source: 2025 Stack Overflow Developer Survey
47%
of organizations using AI have experienced negative consequences
Source: McKinsey’s 2025 State of AI Global Survey
74%
of production AI agents still rely primarily on human evaluation
Source: Pan et al., Measuring Agents in Production, 2025
One engineering workflow across development and production.
Connect to the stackyou already use
Send data through Openlayer SDKs, framework integrations, the Gateway, CLI, or REST API. Add Openlayer to your existing development and production workflows without rebuilding them.
Test every changebefore release
Evaluate changes to models, prompts, data, and agent behavior against defined thresholds. Compare versions and use test results as a release gate before production.
Trace every stepin production
See prompts, retrieval, model calls, tool calls, outputs, latency, token usage, and cost across a session. Find where a failure started without piecing together separate logs.
Improve withproduction feedback
Keep tests running against live traffic, receive alerts when quality drops, and turn failed production sessions into regression tests for the next release.
Quality you can ship.
6x
increase in deployment frequency
+53%
increase in engineering throughput
100%
regressions caught before production
67%
reduction in time to resolve AI failures
“Without Openlayer, we'd be blind to how our LLM outputs behave at scale. It's saved us months of engineering time and given us a repeatable way to keep phishing simulations reliable and realistic.”
Daniel Chyan, CTO, Jericho Security









