Production-Ready AI Models for the Real World

Most AI models are designed in abstraction and only encounter hardware constraints at deployment. ModelCat generates production-grade models based on use cases and real hardware constraints.

See how ModelCat builds production AI systems for real-world deployment.

ModelCat hero graphic — interactive (square, v4) Square 1:1 layout. An animated processor chip with a rotating validation ring and a 45-degree warm-to-red gradient core sits in the center, with four floating callouts orbiting around it. Each callout pauses, brightens and scales up slightly on hover. Validated on real hardware AI-in-the-loop Constraint-driven optimization 24–48 hours to deploy
ModelCat hero graphic — interactive (square, v4) Square 1:1 layout. An animated processor chip with a rotating validation ring and a 45-degree warm-to-red gradient core sits in the center, with four floating callouts orbiting around it. Each callout pauses, brightens and scales up slightly on hover. Validated on real hardware AI-in-the-loop Constraint-driven optimization 24–48 hours to deploy

THE PROBLEM

Most AI Doesn’t Fail in the Lab. It Fails in Production.

01

Traditional AI model development still assumes unlimited compute, memory, and time. Production systems don’t.

02

Models are trained in abstraction, physical constraints arrive late, and performance collapses when systems meet the real world.

03

By the time issues surface, teams are already deep into deployment and fixing them is slow, manual, and expensive.

ModelCat was built to change that.

AI MODEL DEVELOPMENT

Traditional Workflows vs. Production AI

The Traditional Approach

12 – 24 months from data to deployed model

Models built without hardware context

Constraints discovered late

Manual tuning and trial-and-error

Benchmarks that don’t reflect reality

High risk at deployment time

Reliance on wizards and unicorn engineers

The ModelCat Approach

24-48 hours from data to production-ready AI models

Real hardware constraints applied from day one

Validated and benchmarked directly on real hardware

Single-step operation

Confidence in production systems

Easily used by developers, data scientists, and product owners

THE SOLUTIOn

Production AI Solutions

ModelCat provides users with single step workflows for automating model production. Build, Retarget and Benchmark AI and integrate model production into development lifecycles.

Build Custom AI Models

Produce production-ready AI models grounded in real-world hardware constraints using labeled data or trained models.

Retarget Existing Models

Adapt trained AI models across evolving hardware environments without restarting development.

Test Model Performance

Benchmark and validate AI accuracy, latency and power directly on real hardware instead of simulated environments.

Integrate into your Production Lifecycle

Continuously optimize AI as your deployment requirements change.

How It Works

How ModelCat Works in the Real World

ModelCat automates the most fragile and time-consuming parts of production AI model development by grounding every model in real-world system constraints.Inside ModelCat is an AI-in-the-loop system where each step is reasoned, validated, executed, measured, and fed back into ModelCat, continuously refining the model until it reaches its performance requirements.

Upload your existing model or dataset and select your target hardware

Bring your trained model or your dataset into ModelCat along with the hardware you plan to deploy on.

Define your real-world system constraints

Power, memory, latency, and hardware behavior are treated as first-class inputs, not afterthoughts.

Autonomously build and optimize models

ModelCat constructs models tailored to your system design, eliminating manual tuning and iteration loops.

Validate on real hardware

Performance is measured where it actually runs—no synthetic benchmarks.

Deploy with confidence

What you test is what you ship.

What Makes ModelCat Different

When production AI systems are built around real-world constraints instead of abstract assumptions, everything downstream improves. ModelCat delivers:

Faster time to production for edge and on-device AI systems

Reduce months of manual optimization to days.

Lower engineering burden

Eliminate late-stage surprises and rework.

Higher system reliability

Models behave predictably in production environments.

Better business outcomes

Decisions are based on systems that actually perform.

ModelCat doesn’t just accelerate AI development—it de-risks it.

Grounded in ReaIity, Not Theory

ModelCat is built and validated against real hardware environments.

Strategic partnerships across leading silicon and AI ecosystems

Hardware farm for real, continuous validation

Supported chips and hardware targets across embedded, edge, and constrained systems

partner spotlight

NXP Semiconductors

ModelCat partners with NXP to deliver eIQ Model Creator powered by ModelCat, a joint solution within the NXP eIQ® AI ecosystem that enables developers to generate and validate production-ready AI models for NXP hardware.

Learn more about the eIQ Model Creator solution. This isn’t abstract AI. It’s AI engineered to run in the real world.

Build Production-Ready AI From Day One

ModelCat powers AI across a wide range of computer vision applications—from inspection and industrial automation to robotics, sensors, and intelligent edge devices.

Production AI systems should be designed around the real-world environments they ultimately need to operate within. See how ModelCat builds production-ready AI for real hardware.

Get a Demo

Contact us to discuss your needs, challenges, and projects