Illustrative engagement
AI that cites its sources and knows when to ask a human.
An illustrative engagement for a company that wants AI to search documents, answer operational questions, automate repetitive tasks or support internal teams.
Illustrative: how we would scope this, not a completed client project.
The situation
Where it breaks today.
Common patterns we plan for, not a description of a specific client.
Knowledge buried in documents
Answers exist in contracts, manuals and past emails, but finding them depends on who remembers where.
Pilots nobody trusts
An AI demo gives fluent answers without sources, so the team can’t tell when it is wrong.
Permissions ignored
A general-purpose assistant can surface documents a user was never allowed to see.
What we’d build first · illustrative
One governed workflow before a general assistant.
A possible first scope. The real one is agreed with your team after discovery.
A scoped document set
One collection of documents, with owners and access rules agreed before anything is indexed.
Retrieval with citations
Search and retrieval (RAG) that links every answer back to its source documents.
Extraction where it pays
OCR and data extraction for the repetitive documents that take the most time today.
Human review built in
Uncertain or sensitive outputs routed to a person, with the decision recorded.
Decisions we’d make early
Governance before automation.
The expensive-to-change decisions come first, so later changes stay cheap.
Apply access rules before retrieval
The system checks what a user may see before it searches.
Trade-offMore integration work with your identity and document systems, but no answer draws on content the user can’t access.
Cite, don’t just answer
Every answer shows the passages it came from.
Trade-offAnswers are sometimes less fluent, but people can check them.
Keep people in the loop for decisions
AI prepares and suggests; people approve.
Trade-offLess automation on day one, but a clear record of who decided.
How we’d judge it
AI moves from experiment to a useful, governed business workflow.
Success is defined with your team before development begins.
Traceability
Answers link back to their source documents.
Permission-aware retrieval
Access rules apply before information is retrieved.
Human review
Uncertain outputs reach a human reviewer.
What stays with you
Your workflow, your documents.
The workflow, its configuration and the custom code are yours under the engagement agreement. Where your documents are stored and processed is agreed during scoping.
- Service
AI & Intelligent Automation
AI assistants, document search, OCR, knowledge tools, and workflow agents built into real business processes.
Explore - Service
Technology Advisory
Architecture reviews, technology selection, and system roadmaps — so the expensive decisions are made before anything is built.
Explore - Monitoring after release
ErrorLens
AI-assisted debugging, monitoring and issue visibility, offered as SaaS, to improve system reliability and engineering response.
Explore
Who owns the code?
You do, for the custom work we build for you. It is set out in the engagement agreement. Our own products stay ours.
Is our data ours?
Yes: your data belongs to you.
Will you sign an NDA?
If you need one, yes.
How do we start?
With a free 30-minute discovery call about the workflow, then a short discovery that turns it into an architecture and a phased plan.
How long will it take?
It depends on scope. We confirm scope, timeline and price in a written proposal after discovery.
Where is it hosted?
We can host in-region when data residency matters, or deploy to your own cloud account instead.
Start a conversation
Working through a similar challenge?.
Free 30-minute discovery call. Bring the workflow; we’ll tell you whether it’s a product fit, a custom build or neither, and what a first release could include.