Most people focus on the models.

The benchmarks. The demos. The startup press cycles that drop before the product even exists.

But where AI falls apart isn’t in the training phase.

It’s what happens after.

That brutal stretch between building a model and getting it to actually run in the real world. On edge devices, inside public infrastructure, under real-world conditions. Where latency spikes, cost spirals, and compliance rears its head.

It’s the bit nobody talks about.

The messy middle between prototype and production.

That’s the bit this team went after.

And this isn’t another model company, nor another cloud host.

This is a real-time deployment layer. Built for motion. Wired for scale. And designed to run AI where it’s needed, not just where it’s convenient.

Who are they?

AIREV.

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Company Background

UAE homegrown AIREV was never meant to be a research lab or a SaaS frontend.

It was built from the ground up to fix the delivery bottlenecks that cripple most AI systems the moment they hit real environments.

The founding team (Muhammad Khalid, Youssef Ahmad Youssef, and Kayaan Keki Unwalla) understood these problems because they weren’t theorising from a distance. They were shipping logistics platforms across emerging markets. Deploying mobility systems in latency-sensitive regions. Building infra stacks where hyperscaler coverage was patchy at best.

They were in the field, and what they kept running into was the same wall:

AI that looked great on paper, but couldn’t survive in production.

Too slow. Too expensive. Too fragile.

The stack wasn’t designed for reality.

So they started small.

Their first product, SchoolHack, was built for students. A simple GPT-powered assistant that delivered real-time academic help.

No frills, just functional AI for a highly active user base.

And it worked.

3.3 million users. Real traction. Global footprint.

But the breakthrough wasn’t in the UI.

It was in the backend.

What powered SchoolHack was a modular AI infra layer that could serve personalised inference at scale. In real-time. Across spotty networks and unpredictable demand. And that’s when the team saw the real opportunity.

They didn’t need to build the next vertical AI app.

They needed to build the infrastructure layer that made every app possible.

And so, AIREV evolved. From barebones EdTech to a full-stack AI deployment platform.

Their flagship product?

OnDemand.

OnDemand is a plug-and-play runtime designed to bridge the gap between AI capability and AI delivery. It runs across edge environments, cloud platforms, or sovereign zones. It abstracts away the hyperscaler bloat. And it delivers fast, low-latency inference in any geography.

Because this isn’t about chasing benchmarks.

It’s about operational fit.

That’s why every design decision gets filtered through one question:

“Will this actually work in the field?”

So far, the answer has been yes.

Executive Team

• Muhammad Khalid (Founder & CEO) - Serial entrepreneur, leads product innovation, R&D, and global expansion strategy.

• Youssef Ahmad Youssef (COO & Co-founder) - Platform execution and GTM operations lead.

• Kayaan Keki Unwalla (CSO & Co-founder) - Strategy, market expansion, and ecosystem partnerships.

The Edge

AIREV isn’t trying to make AI easier. It’s trying to make it deployable.

• Plug-and-play delivery - OnDemand is a drop-in runtime. No six-month enterprise onboarding cycles. No managed service dependencies. You turn it on, and it runs.

• Built for motion - Smart routing. Dynamic workflows. Sensor-triggered AI. OnDemand is optimised for moving targets, not static cloud environments.

• Cloud + edge orchestration - The engine understands latency, bandwidth, and cost in real terms. It routes workloads intelligently across compute endpoints, balancing throughput with budget.

• Sovereign by default - Need local deployment? No problem. AIREV supports fully sovereign rollouts with in-country data handling and zero cloud rerouting.

• Proven cross-vertical performance - The same stack that powers an education platform now supports smart mobility, logistics, and government AI services.

Recent Moves

• Strategic Investment from VentureWave - Investment from the Irish PE firm to support AIREV's growth trajectory as it scales OnDemand.

• Core42 Partnership - Partnered with the UAE’s sovereign cloud company to drive AI adoption.

• OnDemand rolls out - Deployed the platform from Q1 2024 across pilot markets at home in the UAE, and abroad in Canada, and with Qualcomm, validating platform architecture in multiple scenarios.

• Enterprise partnerships initiated - The team has opened conversations with multiple Fortune 500 companies, laying the groundwork for embedded AI use cases across transport, utilities, and hardware ecosystems.

What’s Next

OnDemand is moving fast.

It’s now rolling out across Qatar, Oman, Canada, Saudi Arabia, Thailand, and Vietnam. Each deployment is tuned to its own latency, regulatory, and network constraints.

Why?

Two reasons:

1. You can’t deliver low-latency AI from the wrong geography.

2. Infra alone doesn’t win - distribution does.

That’s why OnDemand is being white-labelled and integrated into third-party and partner edge devices and infrastructure stacks.

Telecom boxes. Industrial controllers. Robotics systems.

The goal is to move from a mere platform to the embedded layer behind everything else.

And it’s already happening.

AI modules are being tested inside telco deployments across the UAE and Southeast Asia, powering predictive maintenance, churn reduction, and network optimisation. Utilities are entering early pilots with inference modules. Manufacturers are testing real-time optimisation and asset tracking.

And these aren’t just demos; they’re sales pipelines.

Behind the scenes, AIREV is building out a hybrid GPU strategy.

Think proprietary and partner infra stitched into a single orchestration layer. With flexible scheduling across edge and cloud. Optimised for speed, cost, and locality.

Rolling out in Q4.

And finally, the raise.

AIREV is preparing its Series A to fund global infrastructure, expand OnDemand licensing, and embed real-time AI into the pipes of public and enterprise systems.

This isn’t about proving the tech.

That’s already done.

It’s about taking what already works and deploying it everywhere, and showing that the UAE is a serious competitor in the AI startup race.

That’s why AIREV isn’t another AI startup trying to build a moat around a model while failing to convince investors it isn’t a commodity.

AIREV is building the roads that those models run on.

In real-time. In-country. At the edge.

And while everyone else is talking about what comes after the model,

AIREV is making sure there is an after.

And they’re not waiting for the conversation to finish.

They’re doing it now.

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