Openlayer records 48,415 monthly visits with -6.4% month-over-month growth and Freemium, Contact for Pricing pricing. VERN AI records 509 monthly visits with -75.9% growth and Contact for Pricing pricing.
AI governance, testing, and observability for regulated enterprises
The control layer for conversational and agentic AI
| Dimension / Metric | | |
|---|---|---|
| Official Domain | openlayer.com | vernai.com |
| Pricing Model | Freemium, Contact for Pricing | Contact for Pricing |
| Monthly Visits | 48.42K (48,415) | 509 (509) |
| MoM Traffic Delta | -3.3K (-6.4%) | -1.61K (-75.9%) |
| Primary Market & Share | 🇺🇸 United States (44.1%) | 🇺🇸 United States (100%) |
| Direct Visits / mo | 25.94K | 200 |
| User Rating | 4.4 | 4.2 |
| Supported Platforms | Website | Website |
AI governance, testing, and observability for regulated enterprises
Dozens of pre-built evaluations cover quality, safety, security, and performance, with LLM-as-a-judge scorers, session-level metrics, and support for writing your own custom tests against your own data.
Import a repository and run evaluation suites automatically on every change, benchmark each iteration, and block releases when a metric regresses beyond the threshold you define.
Trace every request through multi-step agent workflows, including tool calls and retriever steps, with token counts, latency, cost per request, alerting integrations, and subpopulation analysis.
Register each AI system with an owner, purpose, data sensitivity, and risk tier, score inherent risk across multiple dimensions, and move systems through staged approval gates before they reach production.
The control layer for conversational and agentic AI
Define the policies an AI must follow and have them enforced at runtime rather than hoped for in a prompt.
Detect frustration, hesitation, risk and changing intent so an agent adapts instead of replying on autopilot.
Constrain which tools and actions an autonomous agent may take, and when it must escalate instead.
Record which policy governed each interaction, why an action was allowed, and what triggered an intervention.
Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI
Free / Open-sourceAgent observability, evaluation, and continuous improvement for production AI
SpecialistAttack-led AI security testing and red teaming
SpecialistAttack-led AI security testing and red teaming
Enterprise agentic AI platform for service, workforce and process automation
Free / Open-sourceBuild, simulate, evaluate and monitor self-improving AI agents
Free / Open-sourceBuild, simulate, evaluate and monitor self-improving AI agents
Free / Open-sourceEvaluate, monitor, and govern your AI applications in production
Free / Open-sourceEvaluate, monitor, and govern your AI applications in production
SpecialistThe collaboration layer for AI engineering teams
SpecialistThe collaboration layer for AI engineering teams
Standardize LLM evaluation, observability, and red teaming across your whole org
Standardize LLM evaluation, observability, and red teaming across your whole org
Enterprise AI agent platform for building and running business agents
Enterprise AI agent platform for building and running business agents
Decision infrastructure for governed enterprise AI agents
Decision infrastructure for governed enterprise AI agents
The control plane for trusted enterprise agents and models
The control plane for trusted enterprise agents and models
Full-stack observability with an AI SRE agent that fixes issues
Full-stack observability with an AI SRE agent that fixes issues
Enterprise AI governance platform for agents, models, and vendors
