Automate iterations with AI Agent to deliver production-grade AI instantly
Prompt generation & Self-refinementTeammately AI Agent chooses foundation models, generates prompts based on the best practices of each model, and a quick test using a few synthesized test cases before moving to large-scale evaluation. If the evaluation result is bad, the AI Agent autonomously analyzes the cause and refines your AI.Learn more
Test case & LLM Judge synthesizer for EvaluationTo 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.Learn more
Agentic RAG BuilderTeammately AI Agent builds RAG by automatically handling all processes, including chunking, embedding, and indexing. Learn more
Interpretable AI ObservabilityTeammately Observability automatically evaluates logs with multi-dimensional LLM judges, so you can quickly identify problems—even in production.Learn more
AI-Generated DocumentationTeammately AI Agent generates and updates documentation based on your work, showing your AI's current performance and challenges to support smooth team collaboration.Learn more
Your AI might hallucinate in ways you’ll never notice. Catching those edge cases takes tons of expert but tedious and dirty work.
Maximize safety and reliability with AI Agents designed for AI engineering

Multi-dimensional LLM Judge
Evaluate with various evaluation methods such as 3-grade, pairwise and voting to make the judgments more reliable.Learn more
Let AI organize your data for accurate RAG
Teammately AI Agent automatically cleans “dirty” docs, rewrites chunks to embed context, and identifies failures based on your requirements. [*Coming soon]Learn more
Compare 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.Learn more
Failover to secondary models & prompts
When the foundation model fails, Teammately AI Agent automatically routes to secondary models with pre-tailored prompts for each one. [*Coming soon]
Set up modular AI like a container and scale it everywhere without infra configs
LLMs and agents introduce many new dependencies. Rollbacks are frequent in AI, but codebase and Git management are becoming bottlenecks for prompts and retrieval databases.Implement in 5 min, deliver everywhere in under 30 ms
With a few lines of code, you can integrate Teammately into your app. Using Teammately adds only 30 ms or less compared to calling the fundation model's API directly.
Centralize management
Containerize models, prompts, and retrieval engines to ensure elasticity in your AI DevOps. All infra behind is automatically provisioned and managed by Teammately and its Agents.
Switch models, prompts, and databases with one click
Git-based management poses major challenges in AI. Teammately enables easy switching and rollback.
Learn more about how Teammately makes your AI hard to fail
Build
Prompt generation
RAG development
Self-refinement of bad AI

Retrieval
Agentic RAG Builder
Doc Cleaning
Context embedding

Evaluation
Multi-dimensional LLM Judge
Multi-architecture eval
AI-generated report

Test Case
Test case synthesizer
Expand from your data
Tune edge cases

LLM Judge
Customized metrics
Collective decision-making
Pairwise evaluation

Observability
LLM Judge in post-production
Identify AI failures
Alerts via email and Slack

Documentation
AI Architecture & Logic
Evaluation Report
Future improvements
