Not another pilot that dies in a slide deck. Autonomous agents, automations and custom LLM systems — designed, shipped and operated by one team, measured against the work they replace.
Retail chains, hospitals, factories and campuses — most of them still on support with us today.
Most companies do not have an AI problem. They have a workflow that nobody has modelled, data nobody has connected, and a queue somebody clears by hand every morning. We start there — then build the smallest system that makes it disappear.
Strategy, agents and automation sit at the centre. Engineering, growth and infrastructure exist so nothing stalls between the idea and production.
We map where AI actually pays inside your business — then hand you a costed roadmap, not a slide deck.
Autonomous agents that hold context, call your tools, and finish real work end to end — with a human in the loop where it matters.
The repetitive 60% of your operations, wired into workflows that run themselves overnight.
Private assistants that answer from your data — versioned, evaluated, and hosted wherever your policy demands.
Cameras that count, recognise and alert — retail footfall, ANPR, safety and shrinkage, running at the edge.
Custom platforms built to carry AI workloads from day one, not retrofitted later.
Fast, accessible, search-visible sites and web apps with measurable conversion.
iOS and Android products your customers keep on the first screen.
Zero to launched — validated, prototyped and shipped in focused cycles.
Technical and content SEO built for AI search results, not just blue links.
Strategy, production and community — on a cadence you can actually sustain.
Search, social and remarketing spend held to a cost-per-qualified-lead number.
Identity, collateral and campaign creative that holds up next to your competitors.
Managed infrastructure for apps and models — monitored, backed up, and on call.
The agent reads the world you give it.
Emails, tickets, PDFs, database rows, camera streams, webhooks. We normalise every source into a single typed context the model can reason over — with permissions enforced before a token is spent.
It plans before it acts.
A planner decomposes the goal into steps, picks the cheapest model that can do each one, and keeps a scratchpad of what it has already tried. Every decision is logged and replayable.
It uses your tools, not a chat window.
Typed tool definitions over your CRM, ERP, database and internal APIs. Destructive actions sit behind an approval gate, so a human signs off on anything that touches money or customers.
It gets measurably better each week.
Every run is scored against an evaluation set you own. Regressions block deploys the same way a failing test does — so quality moves in one direction only.
Put together, that is a colleague that works your queue at 3am and files a report you can audit in the morning.
Scope an agent with usNobody signs a twelve-month AI programme on a hunch. We prove value on a single workflow first, with numbers you can take to a board.
We sit with your operators, map the workflows, and score every candidate use case on value, data readiness and risk. You leave with a ranked backlog and a cost model.
We build the single highest-value agent against your real data and measure it against the humans doing that job today. If the number is not there, we say so.
Hardened architecture, guardrails, observability, SSO, audit trails and rollback. Deployed to your cloud or ours, with your team in the code review.
We monitor cost, latency and quality, retrain against fresh feedback, and roll the pattern out to the next department once it has earned the right.
Across AI, web, mobile and analytics
From startup to enterprise delivery
Retail, manufacturing, healthcare, BFSI
Monitored and on-call, 24/7
The pattern transfers; the domain detail does not. Every engagement starts with the vocabulary, constraints and compliance of the industry it serves.
Footfall analytics, shrinkage detection, demand forecasting and AI merchandising.
Visual quality inspection, predictive maintenance and shop-floor copilots.
Clinical documentation, patient triage assistants and back-office automation.
Admissions agents, learning copilots and administrative workflow automation.
Lead qualification agents, document processing and virtual site intelligence.
ANPR gate automation, route intelligence and exception-handling agents.
Reservation agents, guest sentiment analysis and dynamic pricing.
KYC document intelligence, fraud signals and compliance-grade assistants.
A sample of what we have built and still operate. Full write-ups available under NDA.
They came in expecting to sell us a model and instead spent the first week telling us which two of our six ideas were actually worth building. That saved us a quarter.
The agent handles the queue our team used to spend every morning on. What convinced our board was the evaluation report, not the demo.
Nine months in and it is still running, still monitored, still improving. That is the part most vendors do not stay around for.
No. The discovery sprint includes a data readiness audit, and most engagements begin with data that is messier than the client expects. What matters is that the data exists and we can reach it — cleaning is part of the build.
Never. We deploy into your cloud account or an isolated VPC, use zero-retention API configurations, and can run fully self-hosted open-weight models where policy requires it.
A chatbot answers. An agent acts — it holds context across steps, calls your systems, and completes a task end to end, with an approval gate on anything sensitive. The measure of success is work completed, not questions answered.
A discovery sprint is a fixed-fee, one-to-two week engagement. Proof-of-value builds are fixed-scope. We only move to time-and-materials once a system is in production and evolving.
Yes — and we do them with AI woven in rather than bolted on. Many clients start with a site or an app and expand into automation once they see where the repetitive work sits.
Forty-five minutes with the people who would actually build it. We will tell you which of your ideas is worth funding first — and which one to drop.