Systems built for real clients

Five systems, built for very different problems, and the same pattern: read the messy real-world input, build the system that turns it into a repeatable process. Where a client is confidential, the case study describes the system without naming them.

What these case studies show

Each case study describes a system built for a real client, with the result measured in the way the client cared about: for bettercoach, the time from a client enquiry to a ranked coach shortlist; for the enterprise SaaS client, the time needed to prepare a client setup plan. Where a client has given a testimonial, it appears on the case study page.

The approach is the same in both: read the messy input people actually work with, turn it into structured data with confidence checks, and keep a person in charge of the decisions that carry risk. Our current fixed-fee stages for this kind of work are published on the pricing page.

We add new case studies as client projects complete and clients agree to be named.

Corporate Coaching · AI Matching

AI-Assisted Coach Matching

bettercoach

A privacy-aware matching engine that cut coach-matching time to seconds, using semantic search, RAG retrieval, and explainable, human-reviewable matches.

Seconds →

Intelligent Document Processing · Client Onboarding

IDP-Powered Client Setup

Enterprise SaaS (client name withheld)

An AI system that reads raw client documents across formats, extracts structured requirements, and generates a dependency-aware setup plan — cutting preparation time from days to hours.

Days → hours →

Financial Intelligence · Agentic AI

Natural-Language Business Intelligence

Confidential client

An agentic system that answers plain-English business questions across finance, expenses, budgets and operations, without SQL.

Plain English →

AI Infrastructure · Distributed Processing

Distributed Worker Orchestration

Confidential client

A distributed worker layer that lets CPU and GPU machines join one AI processing system, with automatic registration and health monitoring.

CPU + GPU →

Data Engineering · Business Intelligence

Automated Reporting and Audit Trail

Confidential client

A data platform hosted entirely on client-owned infrastructure, with historical entity tracking, timelines and an audit trail.

Client-owned →

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