The engineer you talk to is the engineer who builds it
Jillani SofTech is a founder-led AI engineering consultancy. We design and ship production RAG systems, AI agents, LLM products and machine learning infrastructure for companies that need the system to work on a Tuesday afternoon, not just in a demo.
Built by an engineer, run like a product company
I am Muhammad Ghulam Jillani, Founder and Lead AI Engineer at Jillani SofTech. I started this consultancy because I kept meeting the same situation from the other side of the table: a company that wanted AI, a vendor that delivered an impressive prototype, and a system that fell apart the first week real data hit it.
So the company was built around one rule. Nothing ships unless it works in production. Every system we deliver has documented architecture, real monitoring, a clean handover and post-launch support. Not as an upsell. As the baseline.
What that means in practice
6 years and more than 22 production systems later, I still personally lead architecture and delivery on every engagement. When you work with us you work with the engineer who designs the system, not a project manager relaying messages to a team you will never meet.
It also means I will talk you out of work. If a gradient boosted model on your existing tabular data solves the problem more cheaply and more defensibly than a language model, that is what the scoping document recommends, even though it is a smaller engagement for us. The reputation is worth more than the invoice.
How we are set up
Jillani SofTech is a registered IT services firm, founder-led by design. When this site says we, it means Muhammad Ghulam Jillani as the architect on every build, plus a small team of AI engineers, including a lead AI engineer, who work alongside him with no account managers or delivery layers in between.
You contract with a company, not an individual: master services agreement and NDA on request, USD invoicing, international bank transfer, and milestone payments agreed in writing before work starts.
Continuity is designed in. 2 engineers know every codebase, documentation begins in week 1 rather than at handover, and we work in your time zone: clients in the USA, UK, Germany and the EU each get working hours and a weekly checkpoint set to their calendar, not ours. We work fully remote with clients across the USA, UK, Germany and the EU.
Engagements run asynchronously with a fixed weekly checkpoint, working demos from sprint 2 and honest reporting on blockers rather than a status update written to sound reassuring.
If you have a workflow costing you time and money, data sitting unused, or an AI system that is not performing the way it should, book a call. In 30 minutes I will tell you whether we can fix it, roughly what it takes and what it is likely to cost.
Where we work
Fully remote · USA, UK, Germany, EU. Remote-first delivery with overlap hours agreed per engagement and a fixed weekly review regardless of time zone.
Verified, not self-declared
4 commitments that shape every engagement
These are the rules we hold to even when a different answer would be more profitable for us.
We will tell you when AI is the wrong answer
Plenty of problems are solved better by classical machine learning, a deterministic workflow or a change to the process itself. If that is the case for yours, the scoping document says so, and we would rather lose the build than deliver an expensive system that underperforms a simpler one.
Success is defined before code is written
Retrieval accuracy, cost per request, hours removed, error rate. We agree the measurable target in week 0 and report against it throughout, so nobody is arguing about whether the project worked at handover.
You own everything
Repositories, pipelines, infrastructure configuration and documentation live in your accounts from the first commit. There is no licensed platform underneath and no dependency on us to keep the system running.
We stay after launch
Monitoring, incident response, model tuning and quarterly improvement cycles are part of every engagement. The delivery date is when the system starts being used, not when our attention ends.
Numbers from live production systems
Not projections or theoretical benchmarks. These come from deployed systems with real clients.
7 delivery stages, 1 owner
The full delivery model lives on its own page: the 7-stage lifecycle, the 12 week engagement calendar, and the questions procurement teams ask.
Want to know whether we are the right fit?
Book 30 minutes. You will get an honest read on feasibility, timeline and cost, and a straight answer if the problem does not need us.