Evaluation

Level up AI Evals with AI Agent

If you release without sufficient evaluation, your AI may frequently hallucinate in the production environment. Teammately prevents that.

Reliable evaluation comes from good test cases & metrics

To develop high-quality AI, you need high-quality evaluation, which requires a sufficient number of fair test cases and insightful metrics tailored to your AI project. Teammately AI Agent automatically generates these while aligning with your requirements.

Fair & realistic test cases

Teammately AI Agent generates datasets based on major use cases and logs, enabling realistic simulations before deploying to production.

Customized metrics tailored to your AI project

Pre-defined LLM judge frameworks for cost, latency and bias don't provide significant insights. Instead, evaluate using more relevant and specific metrics tailored to your use cases.

Various evaluation methods

Enhance the validity of your evaluation by using various evaluation methods such as 3-grade, pairwise, and voting.

Test case synthesizer

Teammately AI Agent generates fair and realistic test cases by expanding on the major use cases of your AI project and your log data, and by intentionally creating edge cases.Learn more

Multi-dimensional LLM Judge

Teammately AI Agent generates LLM judge metrics every time based on your objectives. You can choose various evaluation methods such as 3-grade, pairwise, and voting.

Customized metrics

Collective decision-making

Pairwise evaluation

Customize metrics every time

Pre-defined LLM judge frameworks for cost, latency and bias don't provide significant insights. Instead, evaluate using more relevant and specific metrics tailored to your use cases.

Customize metrics every time

Pre-defined LLM judge frameworks for cost, latency and bias don't provide significant insights. Instead, evaluate using more relevant and specific metrics tailored to your use cases.

Collective decision-making

LLM judges are not always perfect. A voting system, where multiple LLMs evaluate the same dataset and metrics simultaneously, makes the judgments more reliable. [*Coming soon]

Pairwise evaluation

Pairwise lets you compare the outputs of two AI architecture versions to determine which performs better in comparison. [*Coming soon]

Simulate & evaluate multiple AI architectures

Teammately AI Agent simultaneously simulates multiple AI architectures, including Prompt, RAG, and models, compares their scores, and helps you find the optimal architecture.

AI Data Scientist drafts report

The AI Agent generate evaluation reports that include graphs & analysis of overall and per-use-case performance, potential hallucinations & common error patterns, analysis of whether this model is production-ready, and future improvements for enhanced performance.