A practical example
An incoming message could be categorised and a suggested response prepared for your approval. AI can make mistakes, so sensitive actions should not run without appropriate checks.
AI automations
Use AI to help with documents, messages and repetitive work.
What we do for you
We connect AI tools to specific tasks, such as sorting enquiries, extracting information from documents or preparing draft replies. We define what the tool may access and when a person must check its output.
Discuss a project
When it is useful
Useful for repeated work involving text or documents. We start with a small test and assess accuracy, data protection and provider usage costs before expanding.
What we can take care of.
Use-case and data-readiness assessment
Prototype and quality evaluation
AI-assisted workflow integration
Human review and monitoring design
The specific deliverables are confirmed in your project proposal.
From conversation to delivery.
Start with the right questions.
We define your audience, priorities and practical requirements before proposing a solution.
Bring the right pieces together.
Design and development move together, with clear milestones and feedback throughout the work.
Launch with a plan for what follows.
We test before launch and agree how support, measurement and future improvements will be handled.
FAQ
Your questions. Clear answers.
Will AI replace human review?
Not by default. The level of review depends on the task and the impact of a mistake. We define when the system can proceed, when it should ask for help and what must remain a human decision.
How are cost and timing defined?
After an initial discussion, we define priorities, deliverables, dependencies and approvals. The proposal sets out the scope, stages and fee before work begins.
Can you work with our existing team?
Yes. We agree roles, system access and communication so responsibilities and coordination are clear.
What do you need to get started?
A description of your goal, the tools you use and the main constraints. You do not need a finished technical specification.
Can an AI system produce an incorrect answer?
Yes. Outputs can be inaccurate or unsupported. We define evaluation examples, limits and review steps for the task; a fluent response is not treated as proof that the result is correct.
Can AI work with our own documents?
It can be designed to retrieve and use authorised business documents. We assess data quality, permissions and the provider’s handling of information before connecting a source.
Does every automation need AI?
No. A clear rule or deterministic integration is often more suitable for predictable tasks. AI is considered where interpretation or generation adds value and its uncertainty can be managed.
How are operating costs controlled?
We estimate usage and define limits, model choices and monitoring. External model and platform charges are separated from implementation work; actual cost depends on the volume and complexity of use.