Scale AI that performs in production.
Openlayer gives every team a consistent way to evaluate quality, compare versions, monitor live behavior, and improve performance across models, agents, RAG, and traditional ML.
See how it works7%
of organizations have fully scaled AI across the enterprise
Source: McKinsey’s 2025 State of AI Global Survey
79%
of enterprises exceeded their AI budgets in the past year
Source: DoiT, AI Spending Survey 2026
79%
of production AI agents still rely primarily on human evaluation
Source: Measuring Agents in Production, 2025
One quality standard across every AI team.
Standardize qualityacross teams
Give every team consistent tests, thresholds, and release criteria across LLM, RAG, agent, and traditional ML projects. Start with 175+ ready-to-use evaluations or define standards for your own use cases.
Compareevery version
Measure changes to models, prompts, data, retrieval, and tools against the same baseline. See the tradeoffs across quality, safety, latency, and cost before deciding what to release or scale.
Track performanceand cost
Monitor quality, drift, latency, token usage, and spend across every connected project. See which systems are improving, which are slipping, and which are consuming more budget without producing better results.
Create evidenceas you work
Keep evaluations, approvals, production monitoring, and system changes in one traceable record. Give governance teams continuously updated evidence without adding another process for delivery teams.
Results you can build on.
100%
of releases evaluated against a defined quality standard
100%
of production requests evaluated continuously
100%
of AI spend attributed to a system, project, or team
175+
ready-to-use evaluations for AI quality, safety, and performance
Built for the standards your organization follows.
EU AI Act
ISO/IEC 42001
NIST AI RMF
OSFI E-23
+ More
“Openlayer gives us one view of quality, performance, and cost across every version, so we can make better decisions about what to scale.”
Daniel Chyan, CTO, Jericho Security
Scale what works.
Know which AI systems are delivering value, then expand them with quality, cost, and risk continuously measured.









