ANNOUNCEMENT

Hexaware Positioned as a Visionary in the 2026 Gartner® Magic Quadrant™ for Custom Software Development Services

Gartner, Magic Quadrant for Custom Software Development Services, By Jaideep Thyagarajan, Ryan McKinney, Nathan Davie, 28 September 2026. Gartner and Magic Quadrant are trademarks of Gartner, Inc. and/or its affiliates. Gartner does not endorse any company, vendor, product or service depicted in its publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner publications consist of the opinions of Gartner’s business and technology insights organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this publication, including any warranties of merchantability or fitness for a particular purpose. This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Hexaware.

Whitepaper

The Chassis Effect: Building Deterministic AI for the Enterprise — Part 3 of 3

The architecture, the economics, and the playbook that make it real

This whitepaper’s final part makes the whole argument concrete: the architecture, the economics, and the playbook for putting it into production.

Why This Matters

Part 1 argued that the enterprises winning the next decade will build a deterministic chassis before layering AI on top, and showed how that chassis comprehends application code. Part 2 turned to the harder estate, enterprise data, and laid out the capabilities that compound once both estates are comprehended.

What You’ll Get in Part 3 of This Whitepaper

The agentic AI architecture and agentic AI orchestration underneath Zerovity™: the Kubernetes, knowledge-graph, and model-routing stack, specified down to the layer
How AI-SDLC matures into Dark Room Development, a gated, largely unattended build cell bounded by two human checkpoints
Why a CIO should price the chassis as one front-loaded investment, not four competing initiatives
Enterprise AI governance that doubles as audit evidence: the same provenance that makes an AI answer trustworthy is what a compliance function needs
A phased playbook that proves the chassis against both code and data, and the difference between real transformation and a shallow enterprise AI adoption exercise

Three parts, one argument: build the chassis first.

Download Part 3 to see the architecture, the economics, and the playbook that make it real, then go back to Parts 1 and 2 for the full case.

Get the Resource

Fill out the form below to gain instant access to our exclusive content.

Your name*

Email address*

How did you hear about us*

••••••

Type the characters to the left*

By checking this box, you consent us to store and process the information provided in accordance with our terms of Privacy Policy*