Forefront

Forefront enables developers to fine-tune and deploy open-source language models on their own data through a managed platform. Users can customize leading models like Mistral and Mixtral with private datasets, validate performance with built-in evaluations, and run inference via serverless API endpoints—all without managing infrastructure. The platform handles scaling automatically and charges only for actual usage, making it accessible from research through enterprise deployment.

Forefront is a managed platform that enables developers to fine-tune and deploy open-source language models on their own data without managing infrastructure. The platform supports leading models like Mistral, Mixtral, and Phi-2, allowing users to customize them with private datasets, validate performance through built-in evaluations (including MMLU, TruthfulQA, MT-Bench, and HumanEval), and run inference via serverless API endpoints with simple three-line code integration. Forefront handles all scaling automatically and charges only for actual token usage—for example, $0.001 per 1k tokens for Mistral-7B—making it cost-effective from research through enterprise deployment. The platform includes a data warehouse feature that consolidates training, validation, and evaluation datasets in a single place, with an Inspector tool for analyzing data distribution and detecting imbalances without manual effort. Users can also import models directly from HuggingFace, export fine-tuned models for self-hosting elsewhere, or experiment in the built-in Playground before deploying. For enterprises, Forefront offers flexible deployment options across secure clouds and maintains strict data privacy—requests are not logged and user data is never used for model training.