Enterprises face challenges in efficiently fine-tuning, evaluating, and deploying large language models (LLMs) across diverse cloud environments. Existing solutions often lack the necessary tools for comprehensive evaluation, version control, and compliance, leading to increased costs and slower deployment cycles. Furthermore, ensuring data sovereignty and maintaining control over the AI infrastructure can be difficult.

Factory provides a comprehensive platform and SDK designed to streamline the entire LLM lifecycle, from fine-tuning to deployment. The platform offers tools for data organization, version control using SHA256 fingerprints, and customizable infrastructure to maintain control over application hosting, data storage, training, and inference compute. Factory supports a wide range of LLMs and offers pre-built and custom metrics for in-depth model evaluation, enabling users to optimize performance and minimize deployment costs. Its fingerprint technology ensures traceability and meets regulatory requirements for AI/ML governance.

SDK for building and optimizing enterprise LLMs

Support for 10,000+ LLMs

Preconfigured metrics for simplified success verification and deployment

Custom model comparison to analyze training results

Fingerprint technology using SHA256 for tamper-proof security and revision control

Customizable infrastructure for on-premise and cloud deployments

Tools for organizing, managing, and versioning datasets

Integration with various GPU providers (NVIDIA, Google, AMD, Intel)

The primary target audience includes enterprises and developers seeking a comprehensive platform for building, fine-tuning, evaluating, and deploying LLMs, particularly those concerned with compliance, data sovereignty, and cost efficiency.

Factory offers tiered pricing plans, including a free Academic Use plan, a €25/month Developer plan, and custom-priced Enterprise plans with varying levels of storage, features, and support.