AI Engines for Fine-Tuning
LLM Engines for Fine-Tuning
Purpose-built LLM engines for every critical workflow — using LoRA, QLoRA, SFT datasets, and advanced preference tuning. Pick an engine, connect your data, and let us handle the rest.
Cody
Agent: Cody
Fine-tunes your GitHub repo using QLoRA (4-bit quantized LoRA) to produce a fast, lightweight model optimized for code autocomplete and inline suggestions. Uses the Axolotl framework with QLoRA to efficiently fine-tune on your repository's code patterns, naming conventions, and project structure.
SIERA
Agent: SIERA
Synthetic Intelligent Error Resolution Agent — fine-tunes a repository-specialized coding agent using AllenAI's Open Coding Agents (SERA) approach. Generates synthetic bug–fix trajectories from your codebase and trains the model to perform code edits, debugging, and maintenance tasks aligned with your repository's patterns, APIs, and conventions. Optimized for Python in the current reference pipeline.
Extractor
Agent: Flux
Turn Messy Inputs Into Clean, Validated JSON. Fine-tune for strict schemas, validation-friendly outputs, and high-recall extraction.
Guard
Agent: Aegis
Ship Faster Changes Without Shipping Risk. Fine-tune reviewers that catch risky patterns, propose safer fixes, and follow your org's standards.
OpsPilot
Agent: Atlas
Turn Runbooks Into Reliable Incident Response. Fine-tune on your runbooks, on-call notes, and postmortems to guide recovery steps.