GET A DEMO

See How AI Gets Built for the Real World

ModelCat shows you what production-ready AI looks like before deployment—not after it breaks.

In this demo, you’ll see how ModelCat autonomously builds, optimizes, and validates AI models against real hardware constraints so teams can move from data to deployment in days, not months.

Every test drive begins with a short working session to understand your use case and target environment.

We’ll follow up to schedule a short working session tailored to your use case and environment.

Trusted by Chip Teams at

120 ms

vs. 500ms target · Vidar

3 days

data to validated model

the walkthrough

What You Can Expect in the Demo

This isn’t a slide deck. It’s a working session showing how AI actually gets built.

During the demo, we’ll show you:

  • How ModelCat ingests your data and understands your target constraints
  • How models are generated, optimized, and evaluated automatically
  • How memory, power, latency, and performance tradeoffs are handled explicitly
  • How models are validated on real hardware, not just simulated
  • What “production-ready” means in practice

Everything happens before deployment so surprises don’t show up later.

WHO THIS IS FOR

Who the Demo is for

ModelCat is designed for teams building real products, not experiments.

This demo is most relevant if you are:

A CTO / VP of Product

Responsible for getting AI into production

An Engineering or Platform Lead

Working with constrained devices

A Product Team

Struggling with slow, fragile AI  workflows

A Chip or Hardware Partner

Supporting customer AI enablement

A Data Scientist

Who wants models that actually deploy, not just train

If AI performance, reliability, and delivery timelines matter, this demo is for you.

WHy Teams Book A Demo

Why Teams Book a Demo

Teams typically come to ModelCat because:

Model development is slow and brittle

Hardware constraints show up too late

AI expertise is scarce and expensive

Validation happens after decisions are already locked

“It works in the lab” doesn’t mean “it works in production”

The demo shows how these problems disappear when AI is built with constraints first.

"We needed 500ms. ModelCat delivered 120ms. Three days, start to finish."

Name, Title, Vidar systems

4.2x

Better than target latency

500ms target → 120ms delivered

WHy Teams Book A Demo

When the usual approach stops working

Model development is slow

Months of iteration before you know if it'll deploy

Hardware constraints arrive late

Architecture locked before power and latency are factored in

ML expertise is expensive

Scarce team members blocked on model work, not product work

"Works in the lab" ≠ production

Validation gaps surface after decisions are locked

After the Demo

What Happens After the Demo

After the demo, we can:

01

Engineer reviews your submission

Discuss your target hardware and use case

02

We assess fit honestly

Review whether ModelCat is a fit for your workflow

03

Scope a pilot project

Outline next steps for testing or onboarding

04

Your engineers own it

Connect you with relevant partners or supported chips

No pressure. No generic pitch. Just clarity.

If there’s a strong fit, we’ll move forward with a structured test drive using your data and target hardware.

Start Your Model Creator Test Drive
See how AI gets built when production is the starting point.

Tell us a bit about your use case and environment. We’ll tailor a working session around your data, constraints, and target hardware.