AI Supervision
Comprehensive LLM Evaluation &
Real-Time Monitoring
Overview
AI Supervision is a comprehensive solution for evaluating and managing generative AI applications and models. It focuses on ensuring the accuracy, safety, and performance of AI systems, and is designed to give you confidence when releasing AI applications and LLMs to customers and the public.
Evaluate AI Response Accuracy
Comprehensively evaluate AI responses with various metrics including Hallucination, Prompt Injection, PII, and Accuracy.
Data Security Management
Detect Prompt Injection and inappropriate use or exposure of Personally Identifiable Information (PII), and proactively block security risks.
Performance Monitoring & Real-time Tracking
Monitor and optimize performance metrics such as response time, token usage, and cost in real-time.
AI Supervision provides testing and evaluation tools needed during AI system development, along with monitoring capabilities during operations.
Real-time Insights Dashboard
A comprehensive dashboard to view overall performance and key metrics of your AI system at a glance.
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Performance Radar & Grid
Visualize key metrics like Answer Relevancy, Bias, Faithfulness, Hallucination, and Toxicity with radar charts and grids
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Real-time Usage Tracking
Monitor operational metrics including Test Run Count, Request Count, Input Tokens, and Output Tokens in real-time
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Trend Analysis (Toxicity, Latency, System Performance)
Track performance changes over time with graphs and detect anomalies early
Evaluation Execution & Metric Trend Management
Manage various test runs and track time-series changes in metric data.
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Metric Data Visualization
Display metric scores over time with multi-line charts to identify trends at a glance
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Metric Trends Analysis
Monitor change rates of key metrics like Faithfulness, Answer Relevancy, Hallucination, Bias, and Toxicity in real-time
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Test Execution History Management
Systematically manage each test run's status (Completed, Running), dataset used, Identifier, and Metric Scores
Detailed Results Analysis & Comparison
Deep-dive analysis of individual test run results and visualize score distribution by metric.
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Results Summary
Summarize key information of test runs including total score (48/60), passing test cases ratio, and Hyperparameters
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Metrics Analysis (Scorecard/Average/Median/Breakdown)
Visualize score distribution of each metric with bar charts and analyze average, median, and frequency by score range in detail
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Metric Scores Overview (Radar)
Compare comprehensive metrics like Answer Relevancy, Toxicity, Bias, Hallucination, and Faithfulness with radar charts
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Compare Test Results
Compare multiple test results side by side to quantitatively measure model improvement effects
Systematic Test Case Management
Create and manage test cases for various scenarios and track detailed results for each case.
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Test Case List & Status Management
View all test cases at a glance and track PASSED/FAILED status in real-time
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Detailed Test Case View
Review and compare Input, Expected Answer, Actual Output, and Context for each test case in detail
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Metric-specific Score Review
Check metric scores for each test case including Answer Relevancy, Bias, Faithfulness, Hallucination, and Toxicity
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Filtering & Sorting
Filter by Status, ID, Input, etc., and deep-dive into each case with View Details
TestSet Auto Generation
AI-powered TC Generator analyzes document structure and context to automatically generate high-quality Q&A datasets that feel like they were written by real people. Solve the simple structure and unnaturalness of traditional QA, with dramatic cost savings.
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Document-based Q&A Auto Generation
Analyze document structure and context to automatically generate high-quality Q&A data for AI training, evaluation, and validation. Support various formats including PDF, DOCX, TXT (Max 10MB)
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Natural QA Like Real Users
Go beyond simple problem-solution structure of traditional QA. Generate user-friendly conversational QA sets where LLM behaves like various real people, close to actual data
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Diverse User Profile-based Generation
Generate questions by specialized topics and subjects. Create QA from various user perspectives by segmenting profiles (tone, interests, personality, etc.)
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Dramatic Cost Reduction
Drastically reduce opportunity cost compared to high-cost manual creation, while improving evaluation reliability
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AI Model Performance Optimization
Utilize generated Q&A for AI training, evaluation, and validation to enhance model performance. Systematically provide data to improve adaptability and accuracy
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LLM Validation & Export
Provide validation results from various LLMs including GPT-4, Claude-3, and Gemini-Pro. Immediately usable with CSV/JSON download support
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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.