Built by someone who has lived inside the systems we now automate.
LEAP isn't a group of generalists who discovered AI last year. It's a studio built around one founder's four years of hands-on work inside Microsoft Dynamics 365 — and the conviction that the best AI systems are built by people who already understand the enterprise software they're meant to work alongside.
Sufyan leads LEAP as both CEO and its senior Dynamics 365 Solution Architect, directing the design and delivery of ERP solutions end to end across the Microsoft Dynamics 365 Finance & Operations ecosystem — architecting data entities and customizations, engineering SSRS reporting, extending standard functionality with X++, designing workflow and security-role architecture, and building OData/API integrations that hold up under real client HR, payroll, and finance operations.
That enterprise foundation extends into mobile and AI: he architected and shipped a production Employee Self-Service (ESS) platform — a configurable app with OCR and resume parsing used by real organizations — and now leads LEAP's work as an AI solutions provider, engineering agentic AI systems that integrate natively with D365 and enterprise infrastructure, built to perform in production, not just in a demo.
LEAP exists because of a gap he kept running into: AI studios that don't understand enterprise software, and ERP consultancies that don't build production AI. Under his lead, LEAP is built to do both at a senior, architect-led standard.
Why an ERP background matters for AI.
Most AI agencies build impressive demos that fall apart the moment they need to touch a real system of record. Dynamics 365, and enterprise ERP generally, is unforgiving — data entities, security roles, and workflows all have to be respected, or the automation breaks something that actually matters to the business.
Having built inside D365 rather than just around it changes what LEAP ships: automation and agents that are designed from day one to work with your existing systems, not bolted on as an afterthought.
Why LEAP builds AI as infrastructure.
An AI agent that works in a demo and an AI agent that works in production are two different pieces of engineering. The gap is guardrails, evals, fallback behavior, and monitoring — the unglamorous parts that determine whether a system is still trustworthy after the tenth edge case.
That's the standard every LEAP AI Agent, chatbot, and automation pipeline is held to: built to run, not just to impress in a first call.
The defaults that don't change per client.
Senior hands only
No handing your project to someone learning on the job. Every engagement is staffed by people who have already shipped systems like the one you need.
ERP-literate AI
We design around your existing Dynamics 365, CRM, and data infrastructure from day one — not as an integration bolted on at the end.
Working software early
You see a running build in the first weeks. Momentum is the point, not a slide deck about momentum.
We stay after launch
Shipping is the start. We monitor, iterate, and scale as real usage arrives, so what launched keeps earning its keep.