Neuralectic

A model is not value. Delivery is.

Frontier models keep getting more capable, and that capability is becoming abundant. But a model on its own doesn’t do much. It sits there, waiting for someone to put it to work. The hard part now isn’t building the intelligence. It’s getting it into the real work people do every day. That’s why we started Neuralectic, and it’s the only thing we work on.

Think about a supply chain. A factory can make the best goods in the world, but none of it matters until the last mile, when a driver carries the package the final stretch and puts it in someone’s hands. It’s the least glamorous part of the journey and the most important. AI works the same way. The model is the factory. The last mile is where it meets the real work of an industry and has to hold up to that industry’s standard.

We’ve watched this happen across the industry. Take a raw model, then take the same model wrapped in the right tools and harness, and the difference in adoption, revenue, and growth is enormous. The capability didn’t change. The harness around it did. Everyone has the same models. Not everyone has the harness, and that’s where the value ends up. It isn’t really a market to chase. It’s a hard technical problem to solve.

Neuralectic is a lab with one focus: that last mile. We’re building what we call an evolving meta-harness. It’s the layer that wraps a frontier model in the tools, context, and judgment a particular kind of work actually needs: the test suites, the codebase, the conventions, the checks that decide whether the work is any good. It keeps adapting as the models improve and the work changes. It isn’t a model, and it isn’t fine-tuning. It’s the thing that carries intelligence that final stretch into real work, and it’s all we build.

We’re based in San Francisco. We’re PhDs from Berkeley, MIT, and Oxford who built intelligence at NVIDIA before turning to the harder problem of delivering it. Between us we’ve published more than a dozen papers in top machine learning and physics venues, including ICLR, TMLR, and the Physical Review journals.

We’re starting with engineering, where the work is concrete, the feedback is fast, and the leverage is highest. From there the same approach extends to other industries, one at a time. Models will keep getting better on their own. Delivery won’t. We’re building the part that does.

We’re building it now.

The Neuralectic team