Prisma provides a structured way to evaluate how your AI models perform in real-world conditions — with the ability to explain what’s influencing their outputs, and why performance changes over time.
From correctness and hallucination to fairness and ambiguity handling, Prisma enables your team to monitor performance with context, track behavior across environments, and adapt evaluations to your internal requirements.
From Ambiguity to Confidence
Most evaluation tools are rule-based or static - Prisma isn’t.
When it encounters an ambiguous output — one that falls between categories or depends on context — Prisma doesn’t guess. It routes the case for review, incorporates human feedback, and stores it as evaluation memory.
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Over time, Prisma builds a set of learned preferences based on how your team thinks about quality, accuracy, and compliance. The result: fewer false positives, more consistent evaluations, and faster resolution of edge cases.
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This is how Prisma scales precision — by learning what matters in your AI use case, and applying it reliably.
Have Experts in the Loop only when necessary
Gain instant visibility into your AI system's performance. Receive timely alerts and notifications, allowing you to take immediate action and mitigate any risks.
Observe Behavioral Change – and Its Causes
Palqee Prisma surfaces early signals of behavioral drift, hallucination, or bias, and helps you understand what’s causing them – not just that they’re happening.
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Prisma’s output feeds into your data visualization tool of choice, showing model behavior across time, environments, and input conditions. Contextualize your observed attributes for a socio-technical analysis and ensure performance across different deployment environments.
What You Can Evaluate with Prisma
Prisma supports both standard and custom evaluation metrics. You can define your own rules, or use existing ones aligned with industry practice.
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Correctness & Hallucination
Identify factual inconsistencies and hallucinated content.
Discrimination & Fairness
Detect unjustified output variation across sensitive inputs or environments.
Behavioral Drift
Monitor how outputs shift over time or across input variations.
Ambiguity Handling
Route uncertain cases for feedback. Prisma builds memory from your reviewers to apply these learnings automatically in future evaluations.
Custom Attribute Analysis
Analyze influence of tone, input length, phrasing, formatting, or domain-specific signals.
Built for AI Governance and Risk
Prisma is ued by AI/ML teams, model risk owners, and responsible AI leads to:
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Evaluate production models in structured, repeatable ways.
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Track performance over time with explainability.
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Support audit and risk review with evidence-rich outputs.
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Adapt evaluations to their internal criteria and definitions.
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Meet regulatory requirements.
TRUSTED BY INDUSTRY LEADERS AND POLICYMAKERS
The power of our evaluations, integrated to your existing infrastructure.
Our SDK provides API integrations to merge the power of proprietary Agentic Observability and Explainability data with the industry-leading platforms your team is already familiar with.
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Use with traces or stored logs
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Query data via our API or get structured outputs (JSON, CSV)
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Visualize using your preferred tools: Power BI, Tableu, custom observability layers
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Deploy on-prem or in a private cloud