AI integration and agent workflows
Practical AI. Clear control.
Bring AI into document and business processes through scoped prototypes, application connections and reviewable agent workflows. Start with a defined task, test the behaviour and keep important decisions under human control.
Discuss this serviceWhat the work can include
Practical delivery.
Clear purpose.
AI application integration
Connect a suitable model to a web application or business process, with structured requests, validation and a clear route for reviewing its output.
Document assistants
Prototype document extraction, search, summarisation and draft preparation. Keep source references where appropriate and make review part of the workflow.
Scoped agent workflows
Prototype assistants that follow defined steps and use approved tools or APIs, with limited permissions, review points and a record of actions.
Local setup and evaluation
Set up local inference where suitable, test representative tasks and record errors and practical limits before expanding the scope.
The final scope, deliverables and support arrangements are agreed around your project.
A typical brief
A practical change
in the way work happens.
A team repeatedly reads documents, prepares summaries and copies the relevant details into another system.
A controlled assistant prepares a structured draft, keeps supporting references and passes the result to a person for review before the next step.
Illustrative scenario. The right solution depends on the process, data and systems involved.
A little more detail
Before you get started.
What is an AI agent in this context?
An agent is an assistant that can follow a defined workflow and use approved tools or APIs. The starting point is a scoped prototype, with its actions, permissions and review requirements agreed and tested.
Can AI run locally and still connect to an application?
Yes, with suitable hardware and an appropriate application connection. The complete workflow is assessed, including any external services, data access and human review needed.
Can it make important decisions without review?
AI can make mistakes. The intended task, source material and consequences of an error determine the checks and approval steps. Important decisions remain with the responsible people.