Custom AI Agents

An AI agent is useful when it has a recognisable task, relevant information and clear operational boundaries. Assigning it a broad objective is not enough to expect it to handle every situation.

We design custom agents to support communication, research, monitoring, content and knowledge management activities. We start with people’s work and define which steps the system may perform, which tools it may use and when it needs to request a review.

The aim is to build useful, assessable support, not an indiscriminate replacement for the organisation’s expertise and responsibilities.

The quality of the work depends on how materials, instructions and permitted actions are organised. We define information sources, updating criteria and how the agent should distinguish available information from missing data.

The project may include searching authorised materials, preparing drafts, classification or clearly bounded sequences of activities. Each connection to tools and systems is assessed against access arrangements, compatibility and practical usefulness.

We do not assume that the agent can integrate every platform or independently verify every claim. When information is insufficient, the process needs to provide for clarification or referral to a responsible contact.

We agree permitted data, permissions and authorised operations with those responsible. We distinguish producing a proposal from authorising its execution: publication, sending or significant changes may require explicit approval before action.

We define human checks, error handling and ways to stop the process. Outputs are tested on representative cases, including ambiguous information, out-of-scope requests and inadequate responses.

Choosing a technology does not automatically resolve privacy, security or contractual matters. These are examined with the appropriate functions in the context of the project, without promising universal autonomy or the absence of errors.

The work may include task analysis, material organisation, instruction design, a prototype, selected integrations, tests and operational guidance. Deliverables and maintenance are defined within the agreed scope.

We clarify what the agent can do, what requires review and what it must not do. Its value lies in a manageable process where people can understand outputs and decide how to use them, rather than a promise to eliminate all human involvement.

User guidance also explains how to recognise an incomplete response and whom to contact. The team needs to be able to challenge a result and correct the process rather than rely solely on the fluency of generated language.