A close view of a computer circuit board

Services

AI agents for business operations

An agent is not a chat window. It is permission to carry out a short process, and it should stop when the case is unclear.

Digiting builds agents around one process at a time. Example shapes, not customer claims: a clinic intake that collects the question and books nothing until a person confirms; an accounting office assistant that finds a policy and does not file the return; a builder’s office that drafts a quote from a price list and waits for approval.

The design names the tools the agent may touch, the phrases that force a hand-off, and the log you can read later. If those three things are missing, it is a demo, not an operations tool.

Multi-agent setups are reserved for processes that truly have separate jobs. Most SMBs need one agent and a clear inbox.

What you receive

  • A process map with the stop rules
  • The agent inside the agreed tools
  • A log and a human fallback
  • A care period inside the later subscription hours

Who it is for

Teams with a documented process and a system of record. Agents that invent the process as they go are out of scope.

What this can cover

  • Single-purpose agents
  • Tool use limited to named systems
  • Drafting, routing, and retrieval
  • Evaluation on a set of real examples you provide

Why businesses use it

  • Repeat steps move faster
  • Exceptions stay with a person
  • You can explain the agent to staff without a model lecture

The first agent is a project. Later tuning fits the hour pool if the tools do not change. API fees are extra.

Questions

How can AI reduce administrative work without removing judgement?

Give it the repeatable steps and keep approval on the steps that commit money, medical decisions, or legal positions. The agent should produce a draft or a routing action, not the final commitment, unless you have explicitly designed that and accepted the risk.