Custom AI agents for sales, support, research and operations

Choose one defined job, such as preparing an enquiry summary or a draft response from approved information. Supply representative examples, expected outputs and a clear human handover. StartSimple scopes custom agents around the business workflow. Agree which tools the agent may use, who reviews its output and how you will measure whether the pilot helps.

Include missing information, conflicting source material and a request outside the agreed role. Check whether the agent asks for clarification or hands the task to a person. Review the proposed permissions and outputs with the team, then agree acceptance criteria. A convincing demonstration answer does not establish accuracy or safe operation for every future task.

The acceptance test should require the agent to identify the missing information and use the agreed human handover. Include an intentionally unanswerable example alongside ordinary questions. A plausible answer is not a successful result when it cannot be supported by the company’s approved knowledge or the permitted tools.

Begin with representative read-only tasks and inspect the evidence, proposed action and intended recipient or destination. Then test the approval step in a controlled environment before expanding permissions. Agree which actions can run automatically and which need review; access to a tool does not by itself define appropriate authority.

Use ordinary tasks, ambiguous requests, missing records and a failed tool response. Include a case where a document contains instructions that conflict with the agent’s assigned role. Record the expected result and reviewer for each example so the project is assessed against business behaviour rather than a single impressive demonstration.

Record the current task time and the review or correction work it requires. Compare the same task mix during the pilot, including failures and human handovers. Faster drafting can still create more review work, so agree a useful completed outcome and an acceptable error rate before treating the pilot as a productivity gain.

Choose one input, expected output and named user. State the boundary of the task and the human handover before selecting tools or expanding access.

Include a representative conflict and check the response against the agreed review procedure. The agent should not silently turn uncertain source material into a confident business fact.

Use a clear out-of-scope request and inspect the resulting clarification or handover. Agree what the agent may do before giving it operational access.

Name the systems and actions the agent may use, with review points and permissions. Drafting a response and sending it are different capabilities to scope.

Provide routine questions, missing information and a case requiring a person. Agree the accepted response and handover for each before testing broader traffic.

Use questions with checkable sources and known uncertainty. Review citation relevance, factual accuracy and the action needed when evidence is incomplete.

Compare accepted draft quality and review time using similar cases. Keep drafts, sent messages, replies and resulting qualified conversations as separate outcomes.

Test a representative tool failure and agree the fallback and recovery owner. Confirm how the workflow avoids losing work or repeating an external action.

No. StartSimple scopes custom AI-agent services separately, including responsibilities, approved information, testing and support. Confirm the intended engagement before purchase.

Run the agreed routine, ambiguous and failure cases. Record whether outputs and human handovers meet the project criteria before widening the agent's access.