Your agents work in the demo.
Prove they work in production.
Enterprise AI adoption stalls between proof-of-concept and production. Halios gives engineering leaders the evaluation data to prove reliability, measure business impact, and move agents from pilot to production across every team, vendor, and use case.
Illustrative fleet view
You approved 12 agent projects.
How many are live?
Demo-to-production gap
Agents that perform well in controlled demos often fail against the entropy and edge cases of real enterprise data environments.
Agent sprawl without visibility
Disconnected teams building with different frameworks lead to a fragmented stack with no centralized way to assess risk or quality.
No way to measure ROI
Without standard evaluation metrics, it's impossible to prove that AI agents are delivering actual business value beyond novelty.
The infrastructure to move
every agent past the pilot phase.
One evaluation layer. Every model. Every framework.
Seamless integration with the tools your engineering teams are already using today.
Models & Platforms
Frameworks & Orchestration
The AI performance data your
leadership team actually wants.
For Engineering Leaders
Empower your developers with granular trace analysis, automated regression testing, and objective benchmarks. Remove the guesswork from the release cycle.
- Root cause analysis of hallucinations
- Custom evaluator functions in Python/JS
- Framework-agnostic tracing for multi-agent workflows
For Product & Finance
Gain confidence in AI rollout with board-ready scorecards on safety, accuracy, and ROI. Bridge the gap between technical teams and leadership.
- ROI and token-efficiency dashboards
- Safety & Bias compliance reporting
- Comparative performance over time
Enterprise-grade deployment. No data leaves your perimeter.
Halios deploys as a containerized service inside your infrastructure, VPC, private cloud, or on-prem. All evaluation runs locally, so no agent traffic, customer data, or business logic leaves your environment.