Agents and users are unpredictable. Traditional testing doesn’t work.

Manual datasets don’t scale and lead to critical blindspots

Proper training and testing requires realistic  and exhaustive datasets. Creating test scenarios by hand is slow and incomplete, leaving gaps that your users discover first.

Unreliable evaluation methods provide false confidence

LLM-as-a-judge and other basic scorers miss the nuanced failures that matter to your business, blocking you from measuring what actually drives results.

Production mistakes are inevitable and expensive

Even well-trained agents make errors. When those errors reach users, the business impact can be severe.

Complete lifecycle management for AI agents

Plurai unifies simulation, evaluation, protection, and optimization into a single platform that makes building self-improving agents as fast, systematic, and reliable as your CI/CD pipeline.

Simulate

Eliminate Blindspots

Automatically generate synthetic test datasets customized to your product specifications and policies. No more shipping agents with unknown failure modes.

Generate highly realistic edge-case scenarios tailored specifically to your product.
Multi-modal Scenarios:text, tools, PDFs, images, and voice

Evaluate

Know before (and after) you ship

Stress test agents before deployment and monitor performance continuously with superior evaluations and observability – aligned to your specific requirements.

Automatic and custom eval generation powered by high precision, calibrating evaluators aligned with your use cases
Advanced observability and reporting for monitoring agents performance metrics and deep exploration
Continuous, automatic evaluation integrated directly into your CI/CD pipeline

Protect

Proactively prevent risks in real-time

Monitor agents in production and enforce guardrails that prevent policy violations before they reach users.

Alerting for real time awareness and intervention
Real time blocking of production agents violations to eliminate failures and prevent user facing risks.

Optimize

Improve continuously to meet business KPIs

Leverage real-world performance data to systematically improve agent efficiency – without taking systems offline.

Continuous feedback loop leverages real production data to adapt and improve your models with precision.
End-to-end optimization that improves business outcomes  by increasing systemwide efficiency, not just surgical prompt and local issues.
Optimization of agentic cost and response time by eliminating failed paths and reducing internal logical loops

90%

Cut time to market

99%

Reduce production Failures

96%

Improve agent efficiency

Already running agents in production?

Connect your existing monitoring tool and get complete visibility in under 2 minutes.

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One-click API integration

Drop in your Langsmith, Braintrust, or Arize API key. We'll automatically pull your traces and cluster them into operational patterns.

Auto-generated evals

We analyze your production logs and apply relevant evaluations: GDPR compliance, PII exposure, policy violations. Review and customize what we surface.

Zero-code custom evals

Define new monitoring rules through our interface. No code changes, no deployment cycle.

Research that moves the industry forward

We're on the forefront of applied research around Agentic AI in production, and we share our findings to help the entire industry move faster.

Evals

Tracking Emotional Change to Measure User Satisfaction with AI Agents

Agent Deployment

Plurai Accelerates LLM Agent Deployment with NVIDIA Nemotron and NIM

Introducing IntellAgent

Your Agent Evaluation Framework

Time Engineering

Controlling Latency in Reasoning LLMs

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Build and ship your agents with trust. Watch them get better every day.

Agents and users are unpredictable. Traditional testing doesn’t work.

Manual datasets don’t scale and lead to critical blindspots

Unreliable evaluation methods provide false confidence

Production mistakes are inevitable and expensive