Your domain shapes the behavior.
Compose the context, tools, memory, policies, and verification that define the job. Keep business logic in Python, alongside the libraries your team already uses.
Why Cayu?
Your expertise. An agent that puts it to work.
Domain-specific long-horizon agents need a system shaped around the work. Cayu provides a Python framework for building that system, with model adapters, tools, context, memory, verification and evals. Its integrated runtime carries the resulting agent through execution and recovery.
Explore the framework Start buildingStart with the work
Section titled “Start with the work”The domain gives the agent its job.
Section titled “The domain gives the agent its job.”A document review agent needs to know which fields matter, which sources to trust, what counts as an exception, and when a person needs to decide. Those choices determine whether the work is useful.
The model proposes a next step. The harness supplies the context, tools, domain logic, memory, policies, and checks around it. With Cayu, you build that harness using Python components and run it on the framework’s integrated runtime.
The result is your agent: a product that performs a defined job in your domain.
Two parts of the same job
Section titled “Two parts of the same job”Specific to your domain. Built for a long horizon.
Section titled “Specific to your domain. Built for a long horizon.”Domain-specific describes how the agent works: the knowledge, tools, rules, and verification tailored to its job. Long-horizon describes how it executes: many decisions over hours or days, with new evidence, feedback, and interruptions along the way.
“Review these 5,000 documents”
has a finish line. Getting there takes a system.
The agent may need to inspect thousands of records, investigate exceptions, wait for an approval, and continue after a worker stops. Its state and evidence must remain available throughout that process.
Why one framework
Section titled “Why one framework”Build the behavior and its execution together.
Section titled “Build the behavior and its execution together.”Domain decisions have operational consequences. A tool needs an authority policy. A human review needs a durable pause. A completion check needs evidence from the run. Cayu gives those concerns a place in the same application.
Execution is part of the framework.
Sessions, state, workers, recovery, approvals, and budgets are integrated. Configure them as you build the harness, so they support the same application.
You can inspect and change the system.
Start with defaults, extend or replace components, and choose providers and infrastructure. Evaluate the effect of each change against work from your domain.
Why Python
Section titled “Why Python”Build on the expertise your team already has.
Section titled “Build on the expertise your team already has.”Bring existing data pipelines, calculations, models, integrations, and evaluation code into the agent. The harness remains ordinary Python that your team can read, test, and change.
Models and providers can evolve while your domain logic stays in the application. Cayu exposes replaceable components for those choices; your evaluations tell you whether a change improves the work.
When Cayu fits
Section titled “When Cayu fits”When the work needs more than one response.
Section titled “When the work needs more than one response.”Cayu is especially useful when a domain-specific job involves real systems, persistent context, many model and tool calls, human decisions, cost limits, or recovery across a long execution.
For a single request with no persistent state or operational lifecycle, you may need fewer of these capabilities. Start from the requirements of the job.
Inspect the implementation comparison ↗
From our work to yours
Section titled “From our work to yours”Built while building agents.
Section titled “Built while building agents.”Cayu was extracted from the production runtime behind an agent-operated software factory that built and deployed thousands of business applications. Specialized agents worked together as its SRE, product manager, coder, and forward-deployed engineering assistant.
We started with agent SDKs and frameworks, which made the model-and-tool loop quick to build. Production quality needed control of that loop and of everything around it: durable state, credentials, execution environments, human intervention, recovery, cost attribution, and evaluation. We brought those pieces together in an open-source framework.
Run Cayu on your own infrastructure, with its packaged operator dashboard. Cayu Cloud is an optional shared workspace for building, deploying, operating, and evaluating agents across a team. It is currently invite-only.