Adaptive Engine
Adaptive Engine is a platform designed to help businesses evaluate, tune, and serve the best Large Language Models (LLMs) for their specific needs. It leverages reinforcement learning to optimize LLM performance based on measurable business metrics.
Key Features:
- Reinforcement Learning Fine-Tuning: Utilizes reinforcement learning to fine-tune LLMs, enabling them to outperform frontier APIs with smaller, specialized models.
- Bespoke AI Judges: Employs AI judges to measure metrics relevant to your business, providing evaluations predictive of production performance.
- A/B Testing: Facilitates A/B testing to validate user preferences and ensure performance before deploying models to production.
- Production Feedback Optimization: Tracks business metrics and model interactions in real-time, using production feedback to continuously improve model performance.
- Adaptive Harmony: An in-house preference tuning stack that unifies inference, training, and RL under a single codebase.
Use Cases:
- Enterprise RAG (Retrieval-Augmented Generation): Enables access to enterprise knowledge at scale, improving retrieval accuracy and reducing hallucinations.
- Text-to-SQL: Creates specialized AI agents to accelerate business analytics by interfacing with databases using natural language.
- Customer Support: Transforms customer experience with personalized AI agents, improving CSAT and reducing escalation rates.
