Ten scoped services. One implementation framework.
Each service starts from a process you already run, names the people who stay accountable for it, and ends with documentation you can hand to someone else.
One process, mapped end to end, before anything is built.
Almost every engagement begins the same way: we sit with the team that runs the process and write down what actually happens — including the informal steps that never made it into a procedure document.
That map tells us three things: which steps are repetitive enough to automate, which steps carry judgement or risk and must stay with a person, and which steps are broken for reasons that AI will not fix.
- Current steps, owners and handoffs
- Volume, timing and exception patterns
- Systems, access and data sources
- Agreed measures of a good outcome
Ten services, sequenced to how adoption really happens.
Most clients begin with one assistant or one automated workflow, prove it in a single department, then widen. You are not required to buy the whole range, and we will say when a service is not worth your money.
AI Assistants
Customer-facing and internal knowledge assistants that answer from an approved source set, cite where the answer came from and hand over to a person when a question falls outside scope.
- Approved knowledge base
- Escalation rules
- Answer logging
Workflow Automation
Automate the repetitive middle of a process — intake, classification, routing, drafting and system updates — while approvals stay with the people accountable for them.
- Trigger to audit record
- Business-rule gates
- Approval checkpoints
Document Intelligence
Extract, classify, validate and route information from invoices, application forms, supplier paperwork and operational correspondence into a fixed structure.
- Field-level extraction
- Confidence thresholds
- Reviewer queue
Sales Workflow Support
Enquiry capture, qualification summaries, follow-up preparation and CRM housekeeping. Outbound messages remain owner-approved rather than automatic.
- Enquiry triage
- CRM hygiene
- Owner-approved sends
Customer-Service Automation
Reply drafting from approved wording, ticket routing by intent and priority, quality review sampling and clear escalation paths for anything account-specific.
- Draft-and-review
- Intent routing
- QA sampling
Reporting Assistants
Turn operational records into consistent management summaries — with the underlying figures kept visible so a person can check them before circulation.
- Consistent formats
- Source visibility
- Scheduled preparation
Custom AI Tools
Purpose-built internal applications connected to systems you already run, built when an off-the-shelf tool cannot express your process.
- Scoped build
- Named integrations
- Documented handover
AI Strategy & Governance
Acceptable-use policy, data-handling rules, responsibility mapping and a register of where AI is used across the organisation.
- Usage policy
- Responsibility map
- Usage register
Training & Adoption
Executive briefings, department workshops and role-specific programmes so the workflow is actually used after go-live.
- Role-based sessions
- Practical exercises
- Takeaway materials
Support & Optimisation
Ongoing quality review, exception analysis, prompt and rule tuning, and a change log of what was adjusted and why.
- Exception review
- Tuning cycles
- Change log
We design for the week after go-live, not the launch demo.
Exception handling, reviewer workload and what happens when the workflow is wrong are part of the scope, not an afterthought.
Assistants that know the edge of their own knowledge.
An assistant is only as trustworthy as the material behind it. We agree the approved source set first — the policies, product information and procedures the business is willing to stand behind — and the assistant answers from that set only.
Anything outside it is handed to a person, with the original question preserved so nobody has to ask the customer to repeat themselves.
Assistant design detail
Structured extraction with a reviewer in the loop.
Paperwork arrives in whatever shape the sender chose. Document intelligence turns that into a fixed structure so it can be checked, approved and posted — instead of being re-keyed by hand.
Items below the agreed confidence threshold, or missing a required field, go to a review queue rather than straight through. That threshold is a commercial decision, and it is yours to set.
Document intelligence detail
A usage policy people can actually follow.
Governance work is deliberately unglamorous: who may use which tool, with what information, for what kind of task, and who is accountable when the output is wrong.
We write it in plain language, keep a register of where AI is used, and review it as the estate grows. We do not issue certifications and we do not claim regulatory compliance on your behalf.
Responsible AI approach
A workflow nobody uses is a cost, not a capability.
Adoption is the part most projects underfund. We train the people who will use the workflow on their own cases, not generic examples, and we leave written guidance behind for the next joiner.
Where a team is sceptical, that is useful information — it usually means the process map missed something. We would rather hear it in a workshop than three months after handover.
Training programmesFor every solution we document
The same nine points, every time. If we cannot answer one of them, the work is not ready to be sold to you.
- The business problem in the client's own words
- How the proposed solution works, step by step
- Information and access we need from you
- Systems the workflow will touch
- Where a human must review or approve
- Security and data-handling considerations
- Implementation stages and sequence
- Commercial model and what triggers payment
- Known limitations and what is out of scope