Your first agent, in production
We turn your AI adoption into a first agent role: one clear area of work, the integrations it needs, and an operating layer you do not have to build yourself.
Adoption becomes real when work is handed over
with clear inputs, outputs, permissions, and boundaries.
inside the existing tools rather than in a separate demo.
with a measure and a deliberate decision about what happens next.
What turns a workflow into an agent role
Technology is one part. The harder questions are who owns what, what the agent may access, and how its work is reviewed.
Role and outcome
We shape a recurring area of work until inputs, outputs, and responsibilities are explicit.
Tools and context
The agent receives only the access and sources required for its role.
Evaluations and measure
We define examples, failure classes, and one measure for usefulness and quality.
Permissions and approvals
Sensitive actions, edge cases, and exceptions get a clear route to a person.
Deployment
We put the workflow into your working environment and make changes traceable.
Ongoing operations
We manage models, tokens, cost, monitoring, and improvements while the role is in service.
Using AI or handing over work
Enable employees
- Unit
- Tool access and training
- Execution
- A person starts every run
- Operations
- Remains with your team
- Outcome
- Individual productivity
Hand over work
- Unit
- An agent with a clear role
- Execution
- The agent repeats the workflow
- Operations
- Maintained and monitored by twigbit
- Outcome
- Recurring work that gets done
Training can be useful. It produces a different result from a managed agent role.
One role, one metric, one review.
From first role to live operations
First we shape the work. Then we deploy and operate the agent.
Agent role sprint
We assess one concrete workflow and design the smallest responsible agent role.
- Job, inputs, and expected outputs
- Systems, data, and required access
- Failure classes, approvals, and measure
- A clear call: deploy, prepare, or wait
Managed first agent
We adapt the agent, integrate it, and own the ongoing technical operation.
- Agent, tools, and context configured
- Evaluations, monitoring, and human handovers
- Model, token, and cost management
- Regular review and improvement cycles
Scope depends on the role, integrations, data, and control requirements.
What we get asked most.
Teams we have built products and systems with
Let's discuss your first agent role
Bring one recurring workflow. We will assess whether it is clear, frequent, and controllable enough for an agent.