AI agents that work inside your business process
We scope and build AI agents that work inside your process: lead handling, quotes, scheduling and documents, with clear limits and human approval.
An AI agent does not just answer: it checks information in your systems, decides by rules you define and takes an action, such as classifying a lead, drafting a quote or booking a meeting. We scope and build agents around your business process, with clear limits, human approval where it matters and ongoing control.
Who it is for
- Businesses with request overload or repetitive work that can be described in rules
- Anyone who wants to start with one clear process and measure before expanding
- Teams typing the same data into several systems
- Anyone wary of an unsupervised agent who wants a clear approval framework
What we build
Lead handling agent
Captures requests from every channel, responds, qualifies and routes to the right person.
Quote generator
Turns a free-form request into a formatted quote that is ready for review and sending.
Automatic scheduling
Holds the conversation, checks the calendar, sends confirmations and reminders and books the meeting.
Document processing
Extracts data from invoices and forms and enters it into your systems, with validation checks.
Approvals and control
Approval levels by risk, logs, exception thresholds and a simple way to stop the agent.
How the work goes
Choose one process
A frequent, clear and measurable process with an expected return.
Define limits and approvals
What the agent may do alone, what needs approval and who approves.
Build and test
Tests against real cases, including edge cases and failures.
Measure and expand gradually
We add authority only after there is accuracy data, logs and operational trust.
Frequently asked questions
A chatbot answers from a script. An agent can check real systems, decide and take an action. The right question is whether your process ends in an answer or in an action.
It depends on the risk level. Low-risk actions can be automated with spot checks. Actions involving money, commitments or sensitive data need human approval before they run.
Confidence thresholds that route to review, a budget per process, technical and business monitoring, and choosing the model by task so an expensive model is not used for a simple one.
With one process that has a clear return, in a controlled pilot. Once there is data, we expand to more processes.
There is no fixed package. Price is set after scoping and depends on process complexity, the number of systems and activity volume.