General models, specific work
Over the last two years I have seen first hand at Fortune 500 companies how amazing LLM models from our friends at OpenAI and Anthropic are helping businesses do great jobs, such as coding, and also how they might fail at the same work when the specification of tasks increases. This is not a problem. It is the feature: they are general-purpose model providers, not specific-purpose model providers like Humanpath.
The bet Humanpath is built on
Model customisation is the next intelligence frontier and open-weight is the power behind it. As Jeff Dean made the case for specificity at Y Combinator's Startup School this summer: "AlphaFold, that was a very specific model for protein folding... it was able to really handle that domain quite well." But AlphaFold took one of the best-resourced labs in the world and years of work. That is exactly what we want to change.
Democratising specificity
Humanpath wants to democratise model customisation so a team that deeply knows its domain can reach that kind of specificity without a research lab behind it.
When tasks get complicated
People at enterprises are increasingly using AI for work. It can run many basic tasks very well, but the moment the task gets complicated, and it often does, models stop working as well, especially after the 9th or 10th interaction. That pushes companies away from using models for professional work in healthcare, finance, legal, and other regulated domains.
Built for domain-specific agents
That is why we introduced Humanpath Task Router. It enables you to build agents that are domain-specific and able to run much longer, more complex tasks. Specialist is how Humanpath helps teams reach that specificity in the models themselves.
Tell us where specificity matters most
Share with us what work you believe needs specific-purpose models the most.
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