# AI Adoption for a UK Mortgage Broker | Super Cat > 51 departmental skills and five live boards inside Claude: how a UK mortgage broker’s finance, compliance, marketing and broker teams adopted AI. Source: https://www.super-cat.tech/portfolio/uk-mortgage-broker-ai-adoption Last modified: 2026-10-24 [← All case studies](https://www.super-cat.tech/portfolio)51 skills · 5 live boards · 4 departments # UK Mortgage Broker: AI Adoption Across Four Teams A UK high-net-worth mortgage broker now runs 51 departmental skills and five live boards inside Claude. Finance, compliance, marketing and broker teams do their own work with AI, with human sign-off at every step. broker-skills.board 51 skills · 5 boards Finance - Commission run - Management pack Compliance - File audit - Marketing check Marketing - Content engine - Page optimiser Brokers - Sales board - New business one router · department skills · human sign-off Illustration ## The problem The broker’s teams handled high-volume, knowledge-heavy work across finance, compliance, marketing and brokerage. AI demos existed, but nothing was embedded in daily work, and a generic chat assistant did not know the firm’s data, templates or compliance route. ## What we built A Claude team-account layer: a router that loads the right department skill, 51 skills across finance, compliance, marketing and brokerage, five live boards built from the firm’s own connectors, a shared memory layer, and weekly routines. Every output is a draft for human review, and client-facing work follows the FCA compliance route. Before: AI demos, not daily use; Generic chat did not know the firm’s data; Compliance work needs a human route. After: 51 skills · 5 live boards · 4 departments.Before - AI demos, not daily use - Generic chat did not know the firm’s data - Compliance work needs a human route How it works - 01 Route before answering. One entry point loads the department skill, so a finance question never lands in a marketing template. - 02 51 departmental skills. Finance, compliance, marketing and brokerage each keep their own procedures, sources and guardrails. - 03 Five live boards. Sales, new business, marketing, KPIs and content priorities read the firm’s own connectors, with no retyped figures. - 04 A shared memory layer. Runs read and write the same state, so a routine picks up where the last one stopped. - 05 Weekly routines. Scheduled runs prepare the Monday meetings; the team reviews the output, not the raw data. - 06 Human sign-off. Every output is a draft. Client-facing work stays on the compliance route; nothing is sent without a person. After 51 skills · 5 live boards · 4 departments Stack AI Adoption Claude Skills Workflow Automation Dashboards Financial Services UK ## Why it holds up Adoption is the product. The team runs the skills in its own sessions and the boards in its own meetings; the system does not live in a demo account. Named owners sign off each department’s output, and client-facing work stays on the FCA compliance route. ## Team adoption Who uses it nowFinance, compliance, marketing and broker teams. Each department has a named owner who signs off its output. What we handed over51 departmental skills, five live boards, the shared memory layer and the weekly routines, on the firm’s own Claude team account. What changedFrom ad-hoc AI demos to skills the team runs in its own sessions and boards reviewed in its weekly meetings. Related service: [AI adoption, delivered by embedded engineers](https://www.super-cat.tech/ai-adoption) ## More case studies Big 4 client · fully on-premise ### Enterprise RAG Chatbot for a Big 4 Accounting Firm Multimodal retrieval over a Big 4 firm’s full compliance library, tuned for citation instead of summary — every answer arrives with its source paragraph attached. - Juniors reading thousands of pages per question - Seniors acting as search engines Read the case → 200k calls/month · 67% booking rate vs 77% human ### 24/7 AI Agent Call Center: 200k Calls a Month Across 60 US HVAC Brands Voice agents orchestrating 200,000 calls a month across 60 US HVAC brands for a 5,000-person enterprise, booking 67% of calls against 77% for human agents — within 10 points of a trained team, around the clock. 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