Real projects. Real results.

Challenge

Meridian Wealth, a London-based investment advisory firm managing over 800 client portfolios, was relying on spreadsheets and overnight batch processing. Portfolio managers couldn't react to intraday market shifts, and client reporting took three days to generate.

Solution

We built a real-time portfolio management platform on Next.js and Node.js with WebSocket-driven market data feeds, AI-powered risk scoring, and automated client reporting. The system processes 50,000+ data points per second with sub-200ms latency, and generates white-labelled PDF reports on demand.

Result

Portfolio rebalancing time reduced from 3 days to 4 hours. Client NPS increased from 34 to 71 within the first quarter.

Challenge

Borough Kitchen, a premium homeware brand with 3 London stores and a growing online presence, was losing 68% of mobile visitors at checkout. Their legacy Magento site was slow, their search was ineffective, and they had no personalisation.

Solution

We redesigned and rebuilt their entire e-commerce experience on a headless Shopify + Next.js stack with AI-personalised product recommendations, predictive search, and a streamlined one-tap checkout. Every product page was optimised using AI-generated layout variants tested against real user behaviour data.

Result

Mobile conversion rate increased 156%. Average order value rose 28%. Page load time dropped from 4.2s to 1.1s.

Challenge

A Harley Street clinic group running 12 locations across London was managing appointments via phone and email. No-show rates hit 23%, patient records were fragmented across systems, and clinicians had no visibility into patient engagement between visits.

Solution

We developed a cross-platform mobile app (React Native) with AI-powered appointment scheduling that predicts and prevents no-shows, a secure video consultation module, and a patient health timeline. The backend integrates with their existing EMIS clinical system via HL7 FHIR APIs.

Result

No-show rate dropped to 6%. 82% of patients now use the app weekly. Clinician time saved: 11 hours per week across the group.

Challenge

A Series A SaaS company in Shoreditch had burned through budget on paid acquisition with diminishing returns. Customer acquisition cost had risen 60% year-over-year, their content wasn't ranking, and their sales team was drowning in unqualified leads.

Solution

We deployed a full-stack AI marketing engine: predictive lead scoring using their CRM data, automated content personalisation across landing pages and email sequences, dynamic Google Ads bidding, and a LinkedIn ABM campaign targeting their ICP with machine-generated creative variants.

Result

Customer acquisition cost fell 54%. Marketing-qualified leads increased 3.2x. Pipeline value grew from 1.2M to 4.1M within 6 months.