Services / AI & workflow automation
Connect business tools, reduce repetitive administration and introduce AI where it can help people do useful work. Work directly with Xidents founder Riyaz Sheriff to scope a practical first workflow.
For a team retyping delivery notes or invoices, document workflow automation can prepare fields for checking before an approved transfer to a business system.
Example pilot: one document type, an agreed field list and a review queue. Flag missing or uncertain fields; compare corrections and handling time with the current process.
For a team receiving varied enquiries, AI can suggest a category and a short summary while a person checks the message and decides what happens next.
Example pilot: a limited set of categories, an unclear-message queue and an approved destination. Check incorrect suggestions and duplicate handling before connecting supported APIs.
For staff searching scattered guidance, explore assistance that finds relevant information in an agreed set of documents and gives references to check.
Example pilot: one source collection, defined user access and representative questions. Test unsupported questions, source quality and the route to a person.
Not every process needs AI. A rule-based integration may be easier to test and maintain when the inputs and decisions are predictable. AI may help when documents or language vary, provided its results can be reviewed and corrected.
AI automation services start with a workflow map, feasibility assessment and proposed scope. Record the inputs, approved data access, integration dependencies, review points and exceptions. Agree acceptance checks before building: field accuracy, missed or incorrect categories, source support and the time people spend correcting results.
A pilot should leave you with a working example, documented findings and a decision about whether to proceed. Implementation, hosting, model usage, integration subscriptions, monitoring and maintenance are separate cost considerations; responsibilities and handover are agreed in the proposal.
Xidents serves businesses in both markets. Discovery covers your team’s working hours, review availability and the systems you already use. Any data-location, access or supplier requirements need to be agreed before choosing hosting or AI services.
A useful first enquiry describes one repetitive task, the tools involved and what a successful improvement would look like. Please leave confidential documents and credentials out of the initial contact form.
Microsoft 365 workflows can be assessed alongside other business applications. The available integration depends on your licences, APIs and administrator permissions.
Human review and approval points are agreed as part of the scope. Start with assistance that people can inspect, and test failure cases before deciding whether any step should run automatically.
Cost depends on the workflow, integrations, data quality and operating requirements. Discovery establishes the scope; hosting, model usage and maintenance costs should be considered alongside implementation.
Configuring an existing product can be the right result. Custom software development is an option when the remaining gap justifies building and maintaining an application.
Read our first-party enquiry workflow example, including what was tested and what still needs human review. Our automation, AI or custom software guide explains how to compare approaches and prepare a useful project scope.
First-party prototype / Synthetic test
On 8 October 2026, we ran a local AI prototype over eight deliberately selected synthetic enquiries in one batch. It suggested a category and summary for each message; a person would review every suggestion before taking action.
Example input: “We need a customer portal where clients can see the progress of their jobs. Can you help us scope it?”
Observed suggestion: project enquiry. “Request to scope a customer portal for job progress tracking.”
The suggested categories matched our predeclared labels for 8 of 8 messages, including an unclear request and a message containing a misleading instruction. We inspected the summaries for this fixture. This small test is not a production accuracy benchmark and does not establish time savings, capacity or readiness for customer data.
No live enquiry was processed, connected to another system or sent automatically. The prototype has no customer deployment. A real pilot would need representative data, independent acceptance checks, access controls, error handling and measurement of correction time.
Download the synthetic messages, expected labels and observed outputs (JSON)
