LLMs evaluation.
Continuous testing.

Monitor your LLMs performance with continuous testing, and detect model drift and hallucinations.

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Test & Evaluate
online & offline.

Unit and integration testing are essential software engineering practices to deploy production-ready products. Lynxius provides testing functionalities for LLMs. Generate your test dataset and assess your LLM performance over it offline (while experimenting), or online (from your CI pipelines).

AI Evaluators

Data Extraction Integrations

Automated Labelling

Synthetic Data

Monitor
performance.

Given the probabilistic nature of LLMs, it is imperative to monitor production performance to guard against model drift and hallucinations. Lynxius connects to your Continuous Integration (CI) and Continuous Delivery (CD) platform and constantly evaluates your LLMs over your ground truth and test datasets.

CI Integrations

Automatic Allerts

Detect Hallucinations & Model Drift

User Feedback Collection

Version Library
to re-run evaluations.

It gets difficult to compare the results of different evaluations while models, prompt strategies, thresholds and datasets keep changing. Lynxius maintains a registry of versions of all blocks to easily re-run evaluations combining blocks of different versions.

Prompts Management

Performance Comparison

Manage Versions Combinations

Make testing LLMs a breeze

Stop wasting your time with manual LLM testing. Lynxius makes automated LLM evaluation easy.

Accurate Evaluations

Accurately assess the performance of your LLM in various scenarios and with different metrics.

User-Friendly Interface

Quickly navigate the tool and easily interpret results without extensive technical expertise.

Comprehensive Tests Suite

Test LLM relevance, correctness, conciseness, harmfulness, maliciousness, discrimination, and more.

Customization and Flexibility

Customize tests and evaluation metrics. Tailor tests according to specific use-cases or industry requirements.

Reporting and Analytics

Build dynamic dashboards to highlight strengths, weaknesses, and potential areas for improvement of your LLM.

LLM Agnostic

Test any LLM you want. Your tests can also be run against multiple models for performance comparison.

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