AI Customer Enquiry Assistant
Problem: enquiries arrive in different shapes — sorting them fast is hard.
A classification and triage assistant with human-approved follow-up. Includes a live rule-based demo you can try on the page.
Working systems, functional demos, and delivered client work — each clearly labelled so you know exactly what you’re looking at.
Three projects that show how we think about automation, operations, and customer handling.
// demo = working demonstration · live = running in production
Problem: enquiries arrive in different shapes — sorting them fast is hard.
A classification and triage assistant with human-approved follow-up. Includes a live rule-based demo you can try on the page.
Problem: follow-up depends on memory and scattered records.
Personalised outreach pages, automated follow-up sequences, unsubscribe and open tracking — in production.
Problem: tasks, leads, and system health spread across too many places.
One self-hosted dashboard: tasks, notes, contact queue, outreach pipeline, and technical health.
Real engagements and products — full case studies on each.

Problem: prediction content goes stale in hours; hand-publishing doesn’t scale.
Built: Laravel + Inertia.js platform with an AI cron engine generating and cycling fresh predictions.
Outcome: live in production — the engine runs unattended.
Problem: employee handbook and company content stuck in static documents nobody could keep current.
Built: a digital platform with content management, onboarding flows, and a clean publishing workflow — end-to-end, data model to deploy.
Outcome: shipped and in active use; engagement ongoing.
Problem: a fitness business running members, plans, and schedules by hand — errors and no-shows included.
Built: member management and class scheduling on Laravel, with a mobile client so members handle check-ins and bookings themselves.
Outcome: delivered and in active use by the client’s business.
Problem: repetitive ops work — email, briefings, record-keeping — consumed hours that should go into building.
Built: an autonomous assistant on our own infrastructure: production mail stack administration, verified mail, persistent memory, daily briefings.
Outcome: runs with an 11-check email regression suite that must stay green after every server change.
Tell us the problem — we’ll tell you what we’d build and what it would take.
Discuss Your Project