SpicyGen
What is Okareo?
Okareo offers advanced monitoring tools designed to help AI teams quickly identify errors, prevent hallucinations, and maintain accuracy in production environments for their AI agents. It provides full visibility into agent behavior through real-time monitoring and analytics, supporting faster AI iteration and deployment.
The platform allows for thorough testing of system boundaries by generating diverse scenarios to uncover potential failures and explore edge cases. Furthermore, Okareo facilitates the optimization of models by enabling users to isolate model concerns, synthetically generate necessary data, and fine-tune retrievers and generators, enhancing overall system performance and reliability for specific domains.
Features
- Agent Error Discovery: Identify issues within AI agents.
- Online & Offline Evaluation: Assess agent performance in different environments.
- Custom Evaluators: Define specific metrics and methods for evaluation.
- Synthetic Data Pipeline: Generate tailored data for training and testing.
- Fine Tuning Pipeline: Streamline the process of optimizing models.
- Advanced Monitoring: Real-time tools to track agent behavior and identify errors.
- Edge Case Exploration: Generate diverse scenarios to test system boundaries.
- Persona-Based Agent Simulation: Simulate user interactions for realistic testing.
- Agent Network Debugging: Tools to diagnose issues in complex agent systems.
- Dataset and Prompt Versioning: Track changes in data and prompts.
- Python/Typescript SDK: Integrate Okareo into existing workflows.
- CI/CD Integration: Incorporate evaluation into continuous integration and deployment processes.
Use Cases
- Evaluating and optimizing Retrieval-Augmented Generation (RAG) systems.
- Developing and evaluating Agentic AI applications.
- Integrating AI model evaluation into CI/CD pipelines.
- Monitoring and improving Chat Bot performance.
- Implementing LLM observability and monitoring strategies.
- Fine-tuning Large Language Models (LLMs) for specific tasks.
- Evaluating function-calling capabilities in LLMs and agent networks.
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