AI-INFUSED VALIDATION ยท BY KPIT

KPIT's World Foundation Model

To accelerate AD/ADAS Validation

Seamlessly integrating with simulation and validation benches to improve coverage, reduce costs, and enable production-ready autonomy

100ร—
More scenarios from every hour of already captured data
5ร—
Lower compute economics
Monthsโ†’Weeks
Compression in certification cycles
Shift left
Defects caught in SIL, not while vehicle testing

All stages of validation, powered by KWFM.

One foundation. Every bench. From pure software to real vehicle.

STAGE 01

Software in Loop Simulation

SIL
PURE SOFTWARE
STAGE 02

SIL-HIL Integrated

Component HIL
AD/ADAS ECU ONLY
STAGE 03

System / Lab Car Benches

System HIL
AD/ADAS + ALL ECUs
STAGE 04

Vehicle in Loop Simulation

VIL
REAL VEHICLE + SENSORS
KPIT World Foundation Model
The single engine powering every stage
What's KWFM

A foundation model, purpose-built for Autonomous Driving Systems.

KWFM is KPIT's automotive-grade foundation model that generates millions of lifelike driving scenarios on demand, tuned for every geography and every sensor stack. It empowers automakers to validate their autonomous driving stacks against every conceivable scenario, without driving millions of real miles on the road.

LIVE ยท KWFM

What sets KWFM apart from others

Diversified

Trained for geographic and segment variations.

Quantized

Optimized model for real-time executions.

Simulationized

Integrated with leading simulation engines.

HDMAPized

Integrated with HD maps for real-world road grounding.

Two routes in. One engine out.

ROUTE 01

OEMs have FoT DATA

Stretch your existing data. Find the ODD gaps. Multiply coverage.

ODD GAP ANALYZER + FOUNDATION MODEL
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ROUTE 02

OEMs don't have FoT DATA

No data? Start from KPIT's Scenario Catalogue. Generate scenes the road can't safely create.

SCENARIO CATALOGUE + HD MAPS + FOUNDATION MODEL
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THE ENGINE
Purpose-trained on driving data. Physics-aware. Sensor Configuration-aligned.
Synthetic Scenarios Generated at Scale across Geographies
Synthetic driving scenarios โ€” geographies, road types, weather and conditions

One Foundation Model. Scenarios for every road, every region.

๐Ÿ‡บ๐Ÿ‡ธUSA
๐Ÿ‡ฎ๐Ÿ‡ณINDIA
Built on database shared by ARAI under agreement
๐Ÿ‡ฏ๐Ÿ‡ตJAPAN
๐Ÿ‡ฐ๐Ÿ‡ทSOUTH KOREA

Frequently asked, directly answered.

How is KWFM different from a general-purpose world model?

General-purpose world models serve robotics, warehousing, medicine and automotive from a single training base. KWFM is purpose-trained for autonomous driving, fine-tuned by geography, configured for the specific sensor modalities used in automotive perception, and quantized to run at production cost. KWFM produces physics-consistent reflections, road textures, lane and sign artefacts that general models miss.

Where does KWFM run โ€” our infrastructure, or yours?

KWFM runs inside your infrastructure. Sensitive programme data, HIL Rigs data stay on your premises or cloud tenancy. Our engineers work alongside your team to fine-tune the model, generate scenarios and integrate with your HIL benches.

How do we know the scenarios KWFM generates are realistic enough to trust?

On the BRISQUE perceptual realism index, KWFM-generated scenes sit adjacent to real-world driving video and a clear distance ahead of conventional simulation output. Reflections, road textures, pedestrian behaviour, camera glare and weather artefacts are all represented at a level that lets your AD stack react as it would on the actual road.

How do we quantify completeness of scenario coverage?

Coverage is anchored to your Operational Design Domain (ODD). Starting from the ODD definition, KWFM generates scenarios systematically across the corner cases and adversarial conditions it implies โ€” and traces them back to NCAP, GSR, UN R157, ISO 26262 functional safety and ISO 21448 SOTIF requirements. Every generated scenario maps to a regulatory or programme requirement, so you can demonstrate completeness, not just volume.

We already have an AD stack from a different supplier. Can KWFM help validate someone else's stack on our behalf?

Yes. KWFM is fine-tuned for your geography and run inside your environment, letting your team systematically validate that the integrated stack behaves correctly in the world your customers will actually drive in โ€” well before the vehicle test.

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