Case studies

What AI adoption looks like in practice.

Representative engagements showing the patterns we deliver. These are illustrative scenarios, not named clients; real case studies will replace them as engagements complete.

Distribution Example scenario

Order desk automation

The challenge. A 60-person distributor processed purchase orders by hand from email, PDFs and spreadsheets.

What we build

An agent reads incoming POs, checks stock and pricing, and drafts the order for approval.
Exceptions such as backorders and price mismatches are routed to a person with context attached.
Every action is logged for audit.

Outcomes we measure

Faster order turnaround
Fewer keying errors
Staff time redirected to customers

Professional services Example scenario

Knowledge assistant for proposals

The challenge. A consulting firm’s proposals were slow because past work lived in scattered documents.

What we build

Retrieval over past proposals, case notes and rate cards, with source citations.
A model tuned on the firm’s own tone and structure drafts first versions.
Partners review and approve before anything goes out.

Outcomes we measure

Shorter first-draft time
Consistent voice and structure
Institutional knowledge reused

Customer support Example scenario

Ticket triage and reply drafting

The challenge. A growing SaaS team’s support queue grew faster than headcount.

What we build

Classifies and prioritizes tickets, and suggests replies grounded in the help center.
A fine-tuned model matches support tone and escalation policy.
Evaluation set guards quality before every release.

Outcomes we measure

Quicker first response
Better routing accuracy
Agents focus on complex cases

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