ELSOLVE builds and operates AI systems that do real, day-to-day work inside a business — in your own environment, on infrastructure and accounts you control.
The same three commitments on every engagement, whether the system serves one team or a fleet of client firms.
The system is built once as a reference pattern and improved centrally, so each deployment starts from the current version rather than a fresh experiment. Work outside that envelope is scoped and priced before anyone commits to it.
Each deployment runs in its own isolated environment, on infrastructure and model provider accounts owned and paid for by the client. Client data is not pooled into another client’s environment, and is not used to train shared models.
Monitoring, maintenance and second-line support under an agreed cadence, with the data flow and technical controls documented for each production deployment. Service levels are set per engagement, in writing.
Company details, insurance certificates and the data-flow and controls documentation for a deployment are available on request. Cyber Essentials certification is in progress; nothing else is claimed until it is held.
The workflow, the integrations and the acceptance criteria written down before the build starts, so what ‘done’ means is a document rather than an opinion.
An isolated environment provisioned from that pattern, on your infrastructure and your provider accounts - which keeps data, billing and exit clean from the first day.
Monitoring, maintenance and second-line support once it is live, with documented data flow and controls, and a route for escalating a fault to someone who built it.
You keep your data, your configuration, your outputs and your accounts, and can use them freely in your business. ELSOLVE keeps its reusable platform and tooling. Both positions are set out in the contract before work starts.
Shorter engagements - a diagnostic session, a review of an agent that isn’t performing, or a team workshop - are available where they lead somewhere useful.
A decade of shipping software that runs in production - including AI delivery in financial services and inside regulated and compliance-sector enterprises, alongside US accelerators and bespoke builds for operators.
Where Adrian has worked. Employment and engagement history - not ELSOLVE client logos.
ELSOLVE LTD · London
Bespoke agentic systems built into how your business already runs - on your hardware, on your terms.
Neutralis S.R.L · London
Leading technical strategy and execution for an early-stage venture.
Techbible · London
Technology owner and builder across the full stack.
Founders, Inc. · San Francisco
Hardware-focused founder programme. The build went on to ship as Device Hero.
ProDG Studio · Nairobi
A year of building, hiring, and shipping the studio’s product line end to end.
BT · Version 1 · Citation Group
Python, AWS, and AI delivery inside three of the UK’s larger engineering organisations - from research labs to regulated enterprise and the compliance sector.
Earlier: Full-Stack + AI at a stealth fintech, building an LLM finance assistant · Founder & CTO, Waypoint (Device Hero) · Python Developer, The Plugin People.
Roy was losing hours a week to a split between email, Slack, and a calendar nobody was minding. The fix: MailMind - an agentic assistant that lives on his own machine, ingests his mail end to end, reads attachments natively instead of mangling them, and keeps one searchable map of every conversation. A single typed command folds a Slack thread into the same record. And before any meeting he hasn’t replied to, it nudges him on WhatsApp - organiser, agenda, and join link already in hand.
She wanted serious AI capacity that ran on her terms, not a rented seat in someone else’s tool. The build: a private stack on her own machine - layered onto the runtime she already had rather than starting from scratch - wired to several model providers so the work keeps flowing if any one of them throttles. Usage and rate-limit windows surface on a shared dashboard, and the whole thing is kept patched, backed up, and monitored over a private network.
They had several thousand practitioner contacts and a plan to recruit the best of them as distributors, but no way to work that list at volume without putting their own email domain at risk. The build: an outreach operation on a machine provisioned for them, with its own database. Contacts are segmented by relationship and activity rather than blasted, the copy is written in the reader’s own language, and nothing sends until it has passed a human review queue. Replies are routed by intent and follow-ups stop the moment someone engages. Sending runs on separate domains, so the company’s primary domain is never exposed to deliverability damage - and pipeline figures surface on a dashboard the founders can show investors.
ELSOLVE runs its own engineering on the pattern it sells, which is the honest way to know whether it holds. A set of named agents, each with a defined role and its own isolated workspace, pick up tickets from an issue tracker, do the work on the company’s own hardware, and report back on the ticket they came from. Scheduled jobs mirror every workspace off-site overnight. Health checks flag an agent that stops answering, and a dashboard shows what is running right now. It is the same shape as a client deployment - isolated environments, documented controls, operated after go-live - which is why the fleet is worth showing.
A UK compliance and HR group was generating around three thousand sales calls a day and had no reliable way to tell which of them mattered. The build: a serverless pipeline that transcribed every call overnight and scored it for lead quality, writing the result straight back into Salesforce, so the sales floor arrived each morning to a ranked list rather than an archive of recordings. The work was award-winning. It is included here because it is the closest thing on this page to the scale and compliance posture an enterprise buyer asks about — but it was delivered as an employee, not as an ELSOLVE engagement.
The problem was time: discovery calls being spent on people who were never going to commit. The build: prospects text a WhatsApp number rather than booking straight into the calendar, and an agent runs the client’s own qualification criteria in conversation - filtering out the uncommitted early and routing only serious leads through to a live meeting. A CRM and dashboard sit behind it, so pipeline and lead quality are something to look at rather than guess at. It runs at any hour.
A sample of systems built and run. Most of the work stays under NDA.