Enprompta launches AI eval and observability platform for production apps

Enprompta positions itself as a unified platform for observability, evaluation, and prompt management in production AI systems. The core value proposition centers on three workflows: watching what an AI application does in production, automatically catching low-quality answers before users encounter them, and updating prompts live without redeploying code.

On the observability side, Enprompta traces every LLM call and captures execution traces, latency, token usage, cost attribution, and error logs. Setup is minimal—teams can set two environment variables to go live—and the platform integrates with OpenTelemetry, allowing teams already using that standard to repoint their exporter without introducing a new SDK or lock-in. This design appeals to engineering teams that want minimal friction to adopt monitoring.

For evaluation, Enprompta offers automated scoring using either simple rule-based checks or an AI grader (sometimes called LLM-as-judge). These checks run both in continuous integration before release and continuously on production traffic, allowing teams to catch regressions before they reach users. The platform also supports agentic and trajectory checks for multi-step agent systems, reflecting the growing complexity of AI applications.

The prompt iteration feature is distinctive: a versioned prompt registry lets teams version, branch, and update prompts at runtime via an SDK. This eliminates the need for code changes or deployments when refining a prompt, compressing a typical release cycle from days to seconds. Teams can review, collaborate on, and roll back changes without waiting on engineering.

Pricing is tiered. The free plan (£0 per month) is aimed at individual developers exploring prompt engineering and includes 5,000 observability traces per month, unlimited prompt enhancements, and unlimited prompts. The Pro plan (£29 per editor seat per month, with viewers free and unlimited) targets teams in production and includes 200K observability traces monthly. An Enterprise option offers custom pricing with unlimited team members and SSO (SAML/OIDC) for organizations with compliance requirements. No credit card is required for the free tier, and paid plans include a 14-day trial. A free browser extension is also available for experimenting with prompts in ChatGPT, Claude, and Gemini—useful for teams just getting started. The platform is SOC 2 Ready, addressing security and compliance concerns common in enterprise deployments.

Enprompta enters a market where AI applications are increasingly being deployed to production but teams lack visibility into their behavior and confidence in their reliability. The platform's three pillars—observability (tracing every call), evaluation (automated scoring of outputs), and iteration (versioned prompt management)—address a concrete pain point: today, teams must often redeploy code or guess at root causes when an AI output goes wrong. By enabling runtime prompt updates via an SDK, Enprompta eliminates the engineering bottleneck that forces product teams to wait for code changes, allowing faster experimentation and rollback if a new prompt degrades quality.

The product's positioning reflects the broader shift toward DevOps-style practices for AI: observability (via OpenTelemetry integration), continuous evaluation (scoring live traffic for regressions), and versioning (similar to configuration management). Pricing per editor seat, with unlimited viewers, suggests the platform targets small-to-medium AI teams where not everyone needs write access but stakeholders need visibility—a common structure for collaborative development tools.

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