About Us

We believe that AI models will become significantly smaller and more efficient, without sacrificing capability. This will unlock a wave of accessible, private AI deployments that don't rely on third-party APIs or cloud infrastructure. In this future, every company will operate its own version of ChatGPT, managed securely behind its firewall, tailored to its data, tone, and operations.

But owning an AI system is only part of the story. To make them truly useful, companies will need software to orchestrate these models - tools that allow them to manage prompts, monitor performance, allocate workloads, and govern access.

AI agents will become part of the fabric of internal operations. They'll handle customer support, draft documents, sort inbound messages, analyze data, and more. The role of the human will shift from execution to verification - reviewing outputs, guiding agents, and defining high-level logic.

It's not automation for the sake of speed. It's automation for the sake of clarity, control, and long-term intelligence.

We're already testing the limits of what small, local models can do. Our ensemble model, built from models ranging between 8B and 32B parameters, achieves 62.3% accuracy on MMLU-Pro + Math - significantly outperforming GPT-4o, which scores 52.1% on the same benchmark.

Even with a leaner ensemble of models between 7B and 12B, we reach 52.3% accuracy, proving that strong performance doesn't require massive infrastructure.

These results demonstrate that companies no longer need to rely on monolithic external models to achieve meaningful automation. With the right tools and architecture, you can run capable systems locally - securely, efficiently, and independently.