We build AI solutions for business: request classification, document summaries and assistants that use your company knowledge. We assess the task, available data and integration options before recommending a solution.
Tell us which task takes up your team's time. We will help define what AI should deliver and where an employee needs to review the result.
This is an example of AI for business, not a live customer result. Available functions depend on your data, systems and access permissions.
AI is useful for tasks that involve reading and interpreting text. Start with work your team performs regularly and a result you can check against clear criteria.
A request may be spread across an email, attachments and previous correspondence. AI can help assemble a working summary so an employee can review the details and respond.
save the agreed details in the right system.
Sort enquiries by topic and extract details such as the requested service, deadline and missing information.
Find relevant passages in approved documents and prepare a summary that an employee can check against the source.
Prepare a draft reply from the enquiry and your service information. Your team reviews it before sending.
Extract agreed fields from an enquiry for a CRM record, with validation before data is written.
Organise supplier descriptions into a consistent format. Check specifications against the source rather than letting AI invent missing facts.
AI for business is one option. If the task follows fixed rules, a standard integration may be simpler and easier to maintain.
Choose the scope around the user and the task: a single AI function, an assistant for your team or an integrated workflow. Each needs its own acceptance criteria and operating costs.
For a defined input and output, such as turning a long enquiry into a short summary.
For employees who need to ask questions about company documents and prepare answers from an approved knowledge base.
For tasks where a prepared result must be passed to another system, with checks before the next action.
Before launch, we agree who reviews outputs, which actions require approval and who maintains the solution. AI for business should have clear responsibilities as well as useful features.
A pilot should answer a practical question: can the solution deliver a useful result with your data? We agree on a task, test examples and success criteria before development.
Review sample requests or documents and identify where your team spends time reading, searching or preparing information.
Agree on the output format, required fields and examples of acceptable and unacceptable results.
Check information sources, permissions, integration options and the ongoing cost of the chosen platform.
Test normal cases, incomplete requests and ambiguous questions. Record what works and what still requires manual review.
Agree on rollout, source updates and responsibilities. Extend the solution only where the pilot shows a practical benefit.
AI for business is worth assessing when a task occurs regularly, the input is available and you can verify the outcome.
Send a short task description, the systems you use and an example of the desired result. We can then discuss scope, integrations and an estimate.
Yes, where the chosen solution supports your sources and you have permission to use them. We assess document formats, access restrictions and update requirements before development.
Where the systems provide a suitable API or supported connector. We check access permissions, available actions and platform limits before promising an integration.
For some tasks, yes. The scope must be agreed in advance, with escalation for questions the system cannot handle. A reviewed draft is often the better starting point.
No. A focused pilot makes it easier to test the output, understand running costs and decide whether a wider rollout is justified.
No. AI can invent facts or misread information. We define test cases, source checks and human approval for tasks where an error would matter.
Only data you are authorised to process for this purpose. Before launch, review the provider's terms, storage settings, access controls and requirements for personal or confidential information.
The estimate depends on the task, sources, integrations and testing. We also identify recurring platform and usage charges, so development cost is not confused with the cost of running the solution.
