AI Supervision
Comprehensive LLM Evaluation &
Real-Time Monitoring
Overview
AI Supervision is an integrated solution for evaluating and managing the accuracy, safety, and performance of generative AI applications.
It comprehensively assesses metrics such as hallucination, prompt injection, PII exposure, and response accuracy to prevent security risks.
In addition, it enables real-time monitoring of response time, token usage, and cost to optimize AI system performance and operations.
Real-time Insights Dashboard
A comprehensive dashboard that provides an at-a-glance view of your AI system’s overall performance and key metrics.
It visualizes critical indicators such as answer relevancy, bias, faithfulness, hallucination, and toxicity through radar charts and grids.
You can also monitor real-time usage metrics—like test runs, requests, and token counts—and analyze trends in toxicity, latency, and system performance to detect anomalies early.
Evaluation Execution & Metric Trend Management
Manage multiple test runs and track time-series changes in key metric data.
Visualize metric scores over time with multi-line charts to easily identify trends.
Analyze real-time changes in metrics such as faithfulness, answer relevancy, hallucination, bias, and toxicity, while systematically managing test execution history, including status, dataset, identifiers, and metric scores.
Detailed Results Analysis & Comparison
Perform deep-dive analysis of individual test run results and visualize metric-based score distributions.
Summarize key details such as total score, passing test ratio, and hyperparameters for each run.
Analyze metric distributions through bar charts, examining averages, medians, and score breakdowns in detail.
Use radar charts to compare metrics like answer relevancy, toxicity, bias, hallucination, and faithfulness, and evaluate multiple test results side by side to quantify model improvements.
Systematic Test Case Management
Create and manage test cases across various scenarios while tracking detailed results for each one.
Easily view all test cases with real-time PASSED/FAILED status updates.
Examine inputs, expected answers, actual outputs, and context side by side for in-depth analysis.
Review metric-specific scores such as answer relevancy, bias, faithfulness, hallucination, and toxicity, and use advanced filtering and sorting to quickly find and inspect individual cases.
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TestSet Auto Generation
The AI-powered TC Generator automatically creates realistic, high-quality Q&A datasets from documents, greatly reducing manual costs.
It generates conversational, user-like QA across diverse profiles for training and evaluation.
The tool improves model performance and supports validation with major LLMs, exportable in CSV or JSON formats.
Real-Time Monitoring & Enterprise Alerting
Monitor sessions, token spend, and latency for all LLM services in real-time.
Live Dashboards
Visualize cost trends, track latency, and enforce SLAs before issues affect users.
Cost & Latency Analytics
Instantly detect and block PII, toxic content, bias, hallucinations, and prompt injection attempts — with automated alerts to operators.
Sensitive Data & Content Filtering
Drill into session logs to identify, triage, and resolve issues — then update your app for continuous improvement.
Deep Log Correlation & Rapid Remediation
Why It Matters
In an era of fast AI deployment, enterprise customers and regulators alike demand transparency, fairness, and safety. From financial services to healthcare, AI must perform reliably and securely.
“AI Supervision helps you move beyond experimentation — into enterprise-grade, production-ready AI.”
Real-World Applications
AI Supervision is trusted by major enterprises powering the reliability and compliance of LLM services in PoC and production environments.