Hue
Hue provides a platform for building and evaluating AI agents through simulated APIs and stateful test environments that mirror production systems. The platform captures real production requests and replays them in reconstructed environments, allowing developers to run updated agents against realistic scenarios and observe how they make new decisions. Hue offers observability into agent traces, model calls, and tool activity, with evaluation scoring to compare performance across agent versions over time.
- Developer Tools
- Artificial Intelligence
- AI Agents
- Software Only
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Teams building AI agents struggle to test them reliably because production environments are complex, dynamic, and difficult to recreate. Without realistic test conditions, developers cannot confidently compare agent versions, catch regressions, or ensure their agents handle the edge cases encountered in real user requests.
Solution
Hue provides a platform for building and evaluating AI agents through simulated APIs and stateful test environments that mirror production systems. The platform captures real production requests and replays them in reconstructed environments, allowing developers to run updated agents against realistic scenarios and observe how they make new decisions. Hue offers observability into agent traces, model calls, and tool activity, with evaluation scoring to compare performance across agent versions over time. The platform supports agent replays, where a case from production is recreated and an updated agent runs against it, enabling teams to test changes against the work that gave rise to them.
Target Audience
Primary customers are engineering teams building AI agents for production use, particularly those developing agents for enterprise workflows, legal tasks, and AI operations who need reliable testing and evaluation infrastructure.
Features
- Simulated APIs and MCPs that match production systems, including edge cases
- Stateful environments where each run gets its own world that keeps every change, with easy reset and customization
- Observability into real requests, model calls, and tool activity with trace visualization
- Evaluation scoring to compare performance across agent versions with scores tracked over time
- Agent replays that reconstruct production environments for testing updated agents
- SOC 2 Type II, ISO 27001, and HIPAA compliance with control over traces and context
- Keys scoped per project and organization for security management
- OpenTelemetry trace support via OTLP, allowing integration with existing instrumentation
- Language-agnostic SDKs for tracing model calls and tool use in most programming languages