esya

We build AI inside your business, until it ships.

A senior AI engineer takes one workflow from the first conversation to production. What we build runs in your business and stays in your hands.

The person on your first call owns what ships. Your repo · your IP · your runbook.

See how we work
London Est. 2020

In production.

Your workflow Live

Owned by your team.

Everything your team needs to own and operate what ships.

Accepted into operation

The work crosses the line. Your team keeps the controls.

Selected work
Finance operations

We built a controlled Xero submitter. It refused 1,740 duplicates before commit in year one.

Read the evidence
Engineering

How the work moves

Every room we enter already has AI: a small one, barely used, on a stool in the corner. We raise it. We never replace it.

  1. Map

    Find how the work moves.

  2. Build

    Build one workflow in your repo.

  3. Ship

    Ship with evals and a runbook.

  4. Run

    Tune, train and hand over.

See the engineering room
Selected work

Selected work

Controlled ledger automation · Finance operations

A ledger that refuses to double-post

Duplicate journal entries refused in year one
1,740
Year-end clean-up
Under a day

A controlled Xero submitter refused 1,740 duplicates before commit in year one and cut year-end duplicate clean-up from three weeks to under a day. The operation served 18,000 subscriptions. Applying the published sensitivity model’s per-refusal assumptions to those measured refusals yields $435,000 to $870,000 of annual debt, credit and resolution value at risk, not an audited client saving.

Read the case
Property-transaction network · India-based team

A team built to be handed over

Engineers transferred in-house
14
Still in post after one year
12 of 14

We built and employed 14 engineers in India, embedded them in one client team, then novated all 14 in-house; 12 of 14 were still in post a year later. Using an approximate direct-hiring baseline of 90 elapsed days and a 31-day median, the sensitivity model estimates roughly 590 working engineer-days brought forward and $885,000 to $1.48 million of accelerated capacity, not the client’s commercial results.

Read the case

Also built for: a collaboration-services provider · a creator-economy platform · a mobile-app studio

Talent

Teams, found and employed

When what you need is a team of your own: the build tells us what the role actually needs, then we help you shape it, find the people, employ them compliantly wherever they live, and train them for the role once it is defined. We build teams, not placements, so the shape is ten or more hires over six months, and they transfer in-house when you’re ready. Your IP, always.

How talent works
About

About

“We’ve been the founders in the room. We know what it costs to get this wrong.”

Gopal Patel – Founder and engineer. Chief technology officer at Auriens, where he built its early-stage ventures arm. He has structured cross-border transactions, worked in commodity broking, and created the by-appointment technology concierge service at Selfridges.

Jon Percy – Co-founder and lawyer. Brings the legal view in early, while decisions are still open. Fourteen years as a consultant general counsel to scale-ups; he now leads the legal function at an energy software company and a credit platform. Founder of esya.law.

About Esya
Contact

Tell us the workflow that hurts.

Or the team you can’t hire. We’ll come back with a build plan, not a proposal.