Finance Risk Agent
Finance
Task depth
50+ steps
Context runs
12+ turns
Task Router
Build agents for complex professional work
Humanpath Task Router helps teams move from general-purpose LLM calls to domain-specific agents that hold context, follow specification, and keep performing deep into long-running workflows.
Request onboarding callBuilt for professional domains
FinanceHealthcareLegaland more
Works with frontier models
Featured Agents
Domain-specific agents across 12+ industries, up to 100+ task steps
Legal Review Agent
Legal
Task depth
35+ steps
Context runs
15+ turns
Clinical Workflow Agent
NewHealthcare
Task depth
40+ steps
Context runs
10+ turns
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 work, such as coding, and also how they 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 AlphaFold lesson
As Jeff Dean put it 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. 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 AI for professional work in healthcare, finance, legal, and other regulated domains.
Why Task Router
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 with the context and judgment professional work demands.