General models
Built to answer almost anything.
Useful for open-ended reasoning, but oversized for the repetitive jobs that run inside most AI products.
Specialized inference
You do not need a large model for everything.
Forjal trains small, specialized language models for the repetitive tasks inside your product. Keep the large models for hard reasoning. Move the predictable work to models made for it.
Request early accessDesigned for the calls that happen thousands of times.
30-60x
lower cost than frontier calls
1 URL
to change in your integration
1 task
per specialized model
Forjal models
Built to do one workflow extremely well.
Small, specialized models trained for your classification, extraction, routing, formatting, and response tasks.
What changes
Stop paying frontier prices for narrow work.
Many LLM calls are not open-ended intelligence problems. They are repeatable transformations with a clear definition of success. Those are the workflows Forjal is built to specialize.
Classify tickets
Extract JSON
Route intent
Rewrite in brand voice
Format records
How it works
A smaller model, trained around your rules.
01
Define the workflow
Tell Forjal what the model should do, what good output looks like, and where the current LLM call sits in your product.
02
Shape the examples
Forjal generates training data for the task. You review a small batch so the model learns your edge cases and preferences.
03
Run a smaller model
Deploy behind an OpenAI-compatible endpoint and route the repetitive calls away from your large-model bill.
Early access
Replace one expensive LLM call with a model made for the job.
Join the waitlist if you are already running LLM calls in production and want to test a smaller, specialized model on a real workflow.