Overview

Our platform is designed around a cyclical process that simplifies LLM fine-tuning and enables continuous model improvements via monitoring and output evaluations.

FinetuneDB Features

The features we provide streamline the end-to-end model fine-tuning and serving workflow.

• Data Collection: Our SDK automatically captures all interaction data, from initial uses of generic models to engagements with custom fine-tuned models.
• Data Refinement: Use our dataset manager to filter and adjust content for high-quality training data.
• Fine-Tuning: Fine-tune both open-source and proprietary models with your datasets directly from our platform.
• Evaluations: Test models side by side. Use Human-in-the-loop and LLM-as-judge feedback to validate outputs.
• Model Serving: Deploy and serve fine-tuned open-source models from FinetuneDB with our inference API.
• Ongoing Monitoring: Continuously monitor models in production to detect data drift and identify performance edge cases.
• Continuous Retraining: Use feedback from monitoring to further fine-tune models through a continuous learning cycle.

Our Mission

We strive to provide the most user-friendly platform that empowers generalist tech teams to leverage the power of fine-tuned AI models. Our goal is to dramatically cut costs and boost performance without compromising quality. We are on a mission to democratize fine-tuning, making custom model development accessible to the next generation of builders on the next computing platform—GenAI. Welcome to FinetuneDB!