AI and automation for
everyday work

One practical use is the business inbox. A system can analyse incoming messages, use information about the company and prepare a reply that matches the enquiry.

The reply does not need to be sent automatically. It can be prepared for a member of staff to approve, while unusual, important or higher-risk messages can be excluded from automation and flagged for manual review.

AI can support data analysis, summarise larger sets of information, prepare reports and create working summaries for a team.

The model does not replace source data or human review. We design its role so that AI output is one controlled part of a wider process.

You do not always need a separate “AI application”. Often the better solution is to add one useful capability to a system the team already uses - for example message analysis, document classification, draft replies or data summaries.

Depending on the project, we use APIs including OpenAI and Google as well as other tools suited to the task.

See the AI Email Agent workflow implementation. AI can also form part of a bespoke business system. Our guides discuss private and hosted AI and a working alternative to unapproved AI tools.

Local models can still be appropriate where data, infrastructure or organisational requirements make them useful. We do not treat local AI as the only valid way to implement AI.

The right approach depends on the task, cost, quality, data privacy and how the solution will be maintained.