Use cases

What we actually fix

A look at the engagement patterns we take on: the root problem, what gets built, and the metric that decides whether it worked.

Use cases

The problems we are usually brought in for

Recurring engagement shapes — each with the root problem, what we build, and how success is measured.

Internal knowledge01

Answers from manuals and contracts

Problem
People open hundreds of pages to find one clause, and two people answer differently.
What we build
Retrieval-augmented search that cites the source document for every answer, with role-based access.
How it is measured
Accuracy against an internal test set + average time to find an answer.
Customer support02

Triage and summarise incoming requests

Problem
Requests arrive by email, chat and forms, making priority hard to judge.
What we build
Classification, summarisation and draft replies that a human approves before sending.
How it is measured
Category accuracy + first-response time.
Planning & inventory01

Forecast demand ahead of time

Problem
Chronic overstock or stockouts because planning uses a flat historical average.
What we build
Weekly forecasting that accounts for seasonality, promotions and external factors.
How it is measured
Forecast error (MAPE) against the method currently in use.
Quality inspection03

Computer vision on the line

Problem
Manual inspection is slow and inconsistent between shifts.
What we build
A mobile app that captures an image, checks it automatically and queues unclear cases for a human.
How it is measured
Defect detection rate + false-alarm rate.
Finance & accounting01

Invoices and receipts into the ledger

Problem
The finance team keys document data by hand every month, and formats vary enough to cause mistakes.
What we build
Field extraction from PDFs and scans, cross-checked against purchase orders, with only the mismatches queued for a human.
How it is measured
Field-level accuracy + time per document + number of items requiring correction.
Sales02

Proposal drafts from past documents

Problem
Proposals take too long because material is scattered and written from scratch each time.
What we build
Retrieval across past cases and documents, then a draft with citations that the sales team edits.
How it is measured
Time to first draft + share of content the team has to rewrite.
Meetings & internal ops02

Meeting summaries that become tasks

Problem
Decisions made in meetings are never captured as work, so follow-through slips.
What we build
Key points summarised and action items extracted with owner and due date, pushed into the tools already in use.
How it is measured
Tasks closed on time + time spent writing summaries.
Help centre02

Semantic search on the website

Problem
Customers cannot find answers themselves, so every question becomes a ticket.
What we build
Semantic search that matches real questions, returning a short answer plus a link to the source document.
How it is measured
Self-service resolution rate + change in ticket volume.

These are example scopes of work, not results attributed to any client, and no outcome numbers are invented. Named case studies are published only with the client’s permission.

Does your problem look like one of these?

Tell us what is broken. We will say plainly whether AI is the answer or the process needs fixing first.

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