FusionLeap Digital
Builders in a World of Theorists.

Get your AI out of the demo and into production.

Most AI stalls because of ungoverned data, a delivery process that can't absorb it, or a security review nobody planned for. We fix those and ship production AI in your cloud, working alongside your engineers.

Talk to an ArchitectSee what we've shipped

A free 30-minute call. No obligation.

Your AI demo

Works on a laptop

Production

Your cloud

Running
  • Data governed and tokenizedContracts, lineage, PII tokenized at the sourcequeued
  • Delivery team ready for an AI SDLCSpecs, guardrails, and code reviews built for AI-written codequeued
  • Security review approvedPlanned in from the start, not discovered latequeued

Live in production

In your cloud, run by your team.

Shipped and running900+summaries a month$4Msaved a year99.5%document accuracy40%faster quoting

Who we work with

Built for teams that can't afford a failed AI project.

We work with technology and data leaders, and with the operations and business leaders who own the outcome, at mid-market companies that handle sensitive or regulated data. Our clients include animal health and pharmacy platforms, supply chain and manufacturing operators, and retailers.

We're usually a good fit when your security team can veto an AI project, or when the board is asking for AI and the data isn't ready for it yet.

Document pipelines, text-to-SQL, forecasting, and governed agents that plan, use tools, and stop for a person's sign-off. Built in your cloud, through your security review, owned by your team.

Engagements

Three ways to work with us.

01

AI Enablement Sprint

For when you have a business problem and someone senior backing it. We start with Sprint Zero to work out which use case actually needs AI, then build it on your data and get it ready for production. By the end, your team is the one running it.

12 weeksSee the engagement
02

Rapid AI Development

For when you already know what you want built. Senior engineers take it straight to code, whether that's document intelligence, text-to-SQL, forecasting, or a governed agent. It runs in your cloud, with cost limits in place and a security memo for your InfoSec team.

6–10 weeksSee the engagement
03

Fractional AI Team

Senior architects and engineers working inside your team for three to twelve months. The work is usually some mix of data platform, delivery process, model evaluation, governed agents, and the controls your security team needs to see.

3–12 monthsSee the engagement

80%+

of AI projects fail

Industry estimates cited by RAND, 2024

2×

the failure rate of non-AI IT projects

RAND, 2024

Why pilots stall

Further back, most stalled pilots fell into one of four traps. Sprint Zero is where we check for all four.

  1. 01A use case that never needed AI
  2. 02ROI justified on hours saved
  3. 03Data nobody trusts yet
  4. 04A team never taught to work with it
How we diagnose a stalled pilot

What we've shipped

A few things we've built.

Veterinarian in scrubs updating visit notes on a tablet while a vet nurse holds a golden retriever on the exam table
900+ summaries / month

Animal Health & Pharmacy

Animal Health & Pharmacy Platform (USA)

Over one quarter, working with the client's engineers, we put a governed event spine and Schema Registry in place, tokenized pet-owner and clinical data with Cloud DLP, and set up an AI-assisted delivery process. Alongside that, we built a clinical documentation tool in ten weeks. It now writes more than 900 visit summaries a month, at a few cents each.

Read the case study
Operations clerk at a warehouse receiving desk sorting a stack of purchase orders and invoices beside a document scanner
$4M / year saved

Supply Chain

Supply Chain Operator (USA)

We replaced a brittle, template-based OCR setup with extraction that doesn't need templates. It handles 8,000 documents a day at 99.5% accuracy, more than half with no human touch, and saves about $4M a year. Low-confidence documents go to a reviewer, and every decision is logged.

Read the case study
Sales engineer on a headset matching a thread cone against a fabric swatch, with shelves of colored thread and color cards in a thread manufacturer's sample room
40% faster quoting

Manufacturing

Industrial Manufacturer (UK)

Customers describe the thread they need in plain English, and a text-to-SQL system finds the matching products in a large catalog. Quotes go out 40% faster, and pre-sales handles twice the volume with the same team.

Read the case study
All case studies

How we work

We build with you, not for you.

You work with senior people the whole way through. We're on your real data by week three and show working software every Friday. Before we leave, your engineers have the runbooks, have shadowed on-call, and have done enough of the build themselves to run it without us.

We'll also tell you when AI is the wrong tool. If a plain, deterministic pipeline does the job better, that's what we'll build.

How we work

The AI Enablement Sprint, about one quarter

  1. Phase 0Pre-engagementBefore kickoff
  2. Phase 1Sprint ZeroWeeks 1–2
  3. Phase 2Rapid prototypingWeeks 3–7
  4. Phase 3Production hardeningWeeks 8–10
  5. Phase 4EnablementWeeks 11–12

Get a straight answer from someone who's shipped it.

Bring whatever's stuck: a pilot, a data program, an agent your security team won't approve. In 30 minutes we'll tell you what it would take to get it into production, and whether it needs AI at all.

Talk to an ArchitectSee what we've shipped

Mutual NDA available before the call. We respond within one business day.