Build and improve custom models for your use case.

Glaive builds models that are faster, cheaper and consistently outperform general purpose models with the help of synthetic data.

App screenshot

Why custom models?

Instead of general purpose models which try to do everything, custom models are LLMs tailored to perform a specific task.

Tailored to your use case

Custom models are designed to be great at just one use case, and thus outperform general purpose models.

Cheaper to run

Custom models are smaller, and hence cheaper to run than general purpose models. Get more tokens per dollar without losing quality.

Faster inference times

Custom models can be run at a much higher throughput than massive general purpose models. This enables much better experiences built on top of these models.

Stay in control

Own the weights, integrate with your tech stack, and keep your data private. Our users own the models trained with Glaive, and are free to host them anywhere.

Consistent quality responses

General purpose models can be unpredictable. Custom models are designed to be consistent and reliable.

Schemas instead of prompt engineering

Instead of relying on prompt engineering, Glaive uses schemas to define the structure of your inputs and outputs.

Dataset generation

No need to bring your own data, Glaive generates high quality synthetic data for you.

Rapid iteration

Need to add new information, or change the way your model works? Glaive makes it easy to iterate and improve on your model.

Glaive exclusive

Creating a model with Glaive

1 | Describe task

Describe task

2 | Edit knowledge graph

Edit knowledge graph

3 | Design schema

Design schema

4 | Create dataset

Create dataset

5 | Train model

Train model

6 | Repeat to improve

Repeat to improve