Oberhahn records 633 monthly visits with -70.9% month-over-month growth and Free Trial, Paid, Contact for Pricing pricing. Openlayer records 48,415 monthly visits with -6.4% growth and Freemium, Contact for Pricing pricing.
Know exactly what your AI spend bought.
AI governance, testing, and observability for regulated enterprises
| Dimension / Metric | | |
|---|---|---|
| Official Domain | oberhahn.com | openlayer.com |
| Pricing Model | Free Trial, Paid, Contact for Pricing | Freemium, Contact for Pricing |
| Monthly Visits | 633 (633) | 48.42K (48,415) |
| MoM Traffic Delta | -1.54K (-70.9%) | -3.3K (-6.4%) |
| Primary Market & Share | 🇵🇰 Pakistan (90.7%) | 🇺🇸 United States (44.1%) |
| Direct Visits / mo | 259 | 25.94K |
| User Rating | 4.2 | 4.4 |
| Supported Platforms | Website | Website |
Know exactly what your AI spend bought.
Connect coding assistants, agents, trackers and orchestration layers once, then watch every usage event flow into a single normalized ledger with no manual reconciliation.
See projected month-end spend, cost per session, spend per user, context-window use and an efficiency score, broken out by the source driving each dollar.
Every session links to real Linear, Jira or GitHub issues, so you can read cost per estimate point and see what shipped versus what sank.
Oberhahn flags oversized models, cache misses, runaway sessions and duplicate workflows, each ranked by the spend it affects so you know what to investigate first.
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.
Unified observability, security and incident response for cloud-scale engineering teams
Unified observability, security and incident response for cloud-scale engineering teams
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
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
AI workforce analytics that turn monitoring data into productivity and cost decisions.
AI workforce analytics that turn monitoring data into productivity and cost decisions.
AI value measurement platform connecting AI spend to real business outcomes
AI value measurement platform connecting AI spend to real business outcomes
SpecialistThe control plane for trusted enterprise agents and models
SpecialistThe 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
