TL;DR: Companies are spending more on AI every month, but almost none of that spending becomes an asset they own. We train a small language model for your company's use cases. You fully own it, and we guarantee the same or better quality as the frontier models you use today at 50% lower cost.

https://youtu.be/YRkN_-6rl3Y

Companies are spending more on AI every month, but almost none of that spending becomes an asset they own.

The prompts, traces, and use cases are yours, but the model stays rented.

So you keep paying frontier prices for repetitive work a smaller, specialized model could do faster, cheaper, and often better

We built Experiential Labs to change that.

Here's how it works

Keep using GPT, Claude, or whatever models are already in your stack.

Experiential Labs uses your traffic to build a simulation of the tasks, failures, and edge cases your agent encounters. You can also upload existing traces to bootstrap the process.

The platform trains you a model against that simulation, so it gets better at your specific use cases over time.

As your model improves, it earns more traffic. Hard requests can still go to the frontier. Everything else moves to your faster, cheaper model.

You own the weights, can run them wherever you want, and keep the profits they create. When a stronger base model comes out, we transfer what your model has learned instead of making you start over.

On some tasks we've seen up to 97% lower cost and +50% higher quality. Across a full deployment, we guarantee at least 50% lower cost at the same or better quality, backed by an SLA.

The team

We are both AI researchers. Kion built simulation systems for autonomous vehicles at Waabi after earning his ML PhD at Georgia Tech. Silen built and grew AutoGPT to 160,000 GitHub stars and has worked across continual learning, evaluations, interpretability, and AI for science.

Our ask

If your company sends significant traffic to GPT, Claude, or other frontier models, we would love to help.

Intros to founders and AI leaders with growing inference bills are also greatly appreciated.

Email: founders@xplabs.ai

Schedule a call: https://cal.com/silen/experiential-intro

Website: xplabs.ai