Hexaware · Corporate overview

The Zero Friction Enterprise™

Helping enterprises achieve infinite momentum by removing friction across the estate. Each pillar drives one kind of friction to zero — together they form the Zero Friction operating model.

Watch the 30-second film Explore the six pillars

The film

Six pillars in thirty seconds

Narrated intro film — best played full screen at the top of the session.

The operating model

Zero friction. Infinite momentum.

Zero Tech Debt

We modernize aging code and legacy systems so technical debt stops compounding, keeping every application ready for what's next.

Deep dive →

Zero Vulnerability

We build identity-first, zero-trust security into every layer, so vulnerabilities are caught and closed before they become incidents.

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Zero Backlog

We pair AI-led engineering with human oversight to clear delivery backlogs faster, so teams spend less time waiting and more time building.

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Zero Tickets

We use AIOps and intelligent service operations to resolve issues before users ever notice them, so support tickets stop piling up.

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Zero Defects

We bring AI-led quality engineering into every stage of development, catching defects early so they never reach production.

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Zero License

We transform licensed applications into fit-for-purpose cloud-native or Agentic AI solutions, freeing enterprises from vendor lock-in.

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Zero Tech Debt

Retiring and preventing legacy problems

The problem

Legacy platform constraints, undocumented code and integrations
Hidden dependencies buried in aging codebases
Slow release cycles that increase change risk
Rising maintenance effort that crowds out innovation

The AI-enabled approach

AI discovers dependencies and extracts business logic automatically
AI prioritizes modernization targets by impact and feasibility
AI assists code refactoring, re-platforming and migration
Delivered modernization factories with architecture governance

Change risk reducedModernization velocity fasterMaintenance effort lowerScalability improved

Case study 1

Modernizing legacy banking systems without the disruption

A North American retail and commercial bank

A multi-agent SDLC — planner, executor and reviewer agents — modernized legacy CICS and aging .NET systems, automating COBOL copybook parsing and business logic extraction with human checkpoints at every stage.

98%: reduction in migration time
75%: fewer post-migration defects
60%: reduction in manual effort

Zero Vulnerability

From periodic testing to continuous AI cyber defense

The problem

Scheduled scans and annual pen tests miss machine-speed threats
Findings pile up as reports, queues and manual remediation
Alert noise buries the small number of real risks
Access and identity requests move slower than the business

The AI-enabled approach

Authorized agents continuously discover and validate weaknesses
Exploit validation proves real risk instead of theoretical findings
Automated test generation and pull requests with human approval
Approved automated response with exception-led human operations

From find and report to find, fix and proveContinuous, not periodic, assuranceAutonomy scaled only where controls are strongEvidence for every remediation

Case study 2

Detecting real threats faster with AI-assisted security operations

A leading home mortgage company

AI-assisted triage and access governance separated real threats from noise across the security operation, with human approval gates preserved throughout.

12x: faster triage
90%: reduction in false positives
9x: faster user access requests

Zero Backlog

Accelerating value flow with a fully enabled AI SDLC

The problem

Delivery queues growing faster than teams can clear them
Requirements, code and tests handled in disconnected silos
Brownfield change slowed by unfamiliar code
Release throughput capped by manual effort

The AI-enabled approach

Agentic AI embedded across the engineering lifecycle
AI-generated requirements, code, tests and documentation
Human-in-the-loop review at every stage gate
Continuous flow measurement across the SDLC

Cycle time reducedRelease throughput higherBrownfield velocity improvedBusiness value delivered sooner

Case study 3

Embedding agentic AI across the engineering lifecycle

A leading US pharmacy benefit manager

Agentic AI was embedded end to end across the engineering lifecycle, lifting velocity on established brownfield estates and shortening cycle times.

Up to 60%: increase in brownfield velocity
Lower: cycle time per release
Faster: business value delivery

Zero Tickets

From firefighting to lighting a fire

The problem

High ticket volumes consuming scarce operations talent
The same recurring issues resolved again and again
Automation stalling at simple, scripted tasks
User experience degraded before anyone is alerted

The AI-enabled approach

AIOps correlates signals and predicts failures early
Agentic automation reasons across operational context
Self-healing runbooks close issues without a ticket
Human operations focus on exceptions only

Auto-resolution improvedMTTR fasterEmployee experience betterRoutine ticket demand reduced

Case study 4

Closing the automation gap with AI that reasons across operations

A British home improvement retailer

AI that can reason across operational context lifted the share of work that could be automated well beyond the previous ceiling of around 35%, cutting routine ticket demand.

~35% → higher: automation potential
Reduced: routine ticket demand
Faster: mean time to resolve

Zero Defects

Preventing quality issues before they reach production

The problem

Defects discovered late, when they cost the most to fix
Test coverage lagging behind rapid change
Manual regression cycles slowing releases
Rework effort eroding delivery capacity

The AI-enabled approach

Generative AI creates and maintains test cases
AI-led quality engineering at every stage of development
Automated user testing and defect triage
Continuous quality signals feeding the delivery pipeline

Test coverage improvedRelease confidence higherRework effort lowerDefects caught before production

Case study 5

Driving improved efficiency through generative AI-powered testing

A leading UK insurer

Generative AI-powered testing accelerated new test case development and compressed execution time across every release cycle.

50%: productivity increase in new test cases
30%: reduction in execution time per release
Higher: release confidence

Zero License

It's not a buy vs build world anymore. It's just AI-build.

The problem

Rising renewal costs for software that is barely used
Vendor lock-in constraining architecture choices
Heavy integration overhead around packaged products
Workflows shaped by the licence, not the business

The AI-enabled approach

Identify avoidable software dependency across the estate
AI-build fit-for-purpose cloud-native replacements
Agentic AI solutions replacing licensed capability
Migrate and decommission with governed cutover

Licence dependency removedWorkflows simplifiedIntegration overhead reducedRenewal exposure eliminated

Case study 6

Replacing licensed capability with an AI-built solution

A regional US-based health insurance provider

A licensed product was replaced with a fit-for-purpose AI-built solution, ending a recurring IBM RO licence dependency and simplifying the surrounding workflows.

Eliminated: recurring IBM RO licence dependency
Simplified: downstream workflows
Reduced: integration overhead

Creating smiles across the estate

Proof, pillar by pillar — wherever friction is costing you the most

Zero Tech Debt

98%

reduction in migration time

A North American retail and commercial bank

Zero Vulnerability

12x

faster triage

A leading home mortgage company

Zero Backlog

Up to 60%

increase in brownfield velocity

A leading US pharmacy benefit manager

Zero Tickets

~35% → higher

automation potential

A British home improvement retailer

Zero Defects

50%

productivity increase in new test cases

A leading UK insurer

Zero License

Eliminated

recurring IBM RO licence dependency

A regional US-based health insurance provider

Our value proposition

Why choose Hexaware?

Pioneering an AI-first approach

Zerovity™, our AI delivery layer, runs underneath every pillar — the same agentic engineering model applied to code, security, delivery, operations, quality and licensing.

Consulting-led, outcome-bound

Innovative, consulting-led services help customers fully leverage new-to-market and new-to-enterprise innovation and technology, with commercial models tied to outcomes.

Human oversight by design

Autonomy increases only where authorization, evidence and controls are strong. Every agentic action runs through approval gates and leaves an audit trail.

Make a start

Engage Hexaware with a 6–8 week pilot

Pick the pillar where friction costs you the most. We prove the outcome on your estate before you scale it.

marketing@hexaware.com