Real AI. Real results. Real numbers.

The problem: The recruitment team spent 12 hours every week manually screening CVs and matching candidates to job specifications. Senior staff were doing admin work instead of client-facing tasks.

What we built: An AI screening workflow that reads incoming CVs, scores candidates against job requirements, and produces a ranked shortlist. Integrated with their existing ATS. Staff trained in a half-day session.

The result: Screening time dropped from 12 hours to 2 hours per week. 520 hours saved per year. Quality of shortlists improved — hiring managers reported fewer mismatched candidates.

The problem: Over 200 customer enquiries per day handled manually by a team of four. Average response time was 4 hours. Customers were frustrated. Staff were overwhelmed.

What we built: An AI chatbot trained on the company's product catalogue, pricing, and delivery information. Handles stock checks, order status queries, and returns processing. Escalates complex issues to human agents with full context.

The result: The chatbot resolves 60% of queries without human input. Response time dropped from 4 hours to 90 seconds. The human team now focuses on high-value accounts and complex queries.

The problem: Internal documentation scattered across SharePoint, email threads, and individual hard drives. Staff spent an average of 45 minutes per day searching for information they knew existed somewhere.

What we built: An AI-powered internal wiki that ingests all existing documentation and makes it searchable in plain English. Ask a question, get a direct answer with a source link. Updated automatically as new documents are added.

The result: Staff satisfaction with internal tools went from 32% to 81%. Average search time dropped from 12 minutes to under 30 seconds. The firm estimates 15 hours per week saved across the team.