01
Boardroom Strategy
- AI opportunity thesis & positioning
- Use-case portfolio & sequencing
- Operating-model & capability lift
AI for Business Transformation
From AI ambition to deployed capability
CloudXStack combines board-level strategy, operating-model design and cloud-native AI engineering to move enterprises from AI ambition to deployed business capability — in as little as 120 days.
Boardroom AI strategy. Enterprise-grade execution.
AI is not a technology upgrade — it is a business model shift. Our founder-led engagements advise, govern, build and deploy, so the AI commitment your board signs off on actually arrives in production.
0+Years strategy & transformation experience
0Continents — APAC, EMEA, Africa, North America
€0M+Enterprise deals & partnerships governed
0+Markets & operating models designed
0+Engineering projects delivered
0Days from alignment to live capability
Our Approach
Three layers. One outcome.
Strategy, governance and engineering working as a single operating system — so the AI use cases you fund actually become capabilities your customers feel.
02
Architecture & Governance
- Reference architecture & data foundations
- Model-risk & responsible-AI framework
- Security, privacy & sovereignty
03
Engineering & Deployment
- Cloud-native build & MLOps
- Generative AI agents & RAG systems
- ROI dashboard & scale roadmap
The 120-Day Engagement
What you leave with
Seven board-ready artefacts that turn AI ambition into a running, measurable business capability.
01 AI Readiness Assessment
An honest, evidence-based view of where your data, talent and operating model stand against deployment-grade AI.
02 Board-Level AI Opportunity Thesis
A concise narrative the board can defend — where AI creates margin, moat and measurable customer value.
03 Prioritised Use-Case Portfolio
Ranked use cases scored on value, feasibility and risk, with executive sponsors mapped to each.
04 Costed Implementation Roadmap
Wave-based delivery plan with effort, run-cost, dependencies and decision gates per quarter.
05 Governance & Risk Framework
Model-risk, data-privacy and responsible-AI controls aligned to your regulator and board appetite.
06 Technical Architecture Plan
Reference architecture for data, MLOps, secure inference and integration into your enterprise stack.
07 Deployed Pilot & ROI Dashboard
A live workflow in production, instrumented with an executive dashboard and a credible scale roadmap — not a deck, not a sandbox.
The Operators
The people behind the engagement
A founder-led team that has sat on both sides of the table — the boardroom and the build pipeline.
Business & Strategy
Boardroom and operating-model leadershipTanmay Sonawane
Co-founder · Strategy & Growth
SaaS and platform transformation, board engagement, GTM and capital readiness across multi-market deployments.
- Boardroom advisory
- Multi-market GTM
- Capital readiness
Kevin Da Silva
Senior VP · Operating Model Design
Designs the org, governance and capability lift required to make AI commitments stick beyond the pilot.
- Target operating models
- Change & capability
- Programme governance
Ganesh P
Co-founder · AI Value & Economics
Translates use-case portfolios into defensible business cases the CFO and CRO can both stand behind.
- Business case design
- Risk-adjusted ROI
- Portfolio prioritisation
Technology & Engineering
CloudXStack delivery benchGanesh P
Co-founder · Engineering & Architecture
Cloud-native architecture, generative AI, secure applications and enterprise engineering delivery at scale.
- Cloud-native
- Generative AI
- Enterprise delivery
Akash Banerjee
Head of Data & MLOps
Builds the data foundations, feature stores and MLOps pipelines that move pilots into dependable production.
- Data platforms
- MLOps
- Vector & RAG
Pramod Nair
Head of DevOps & Secure Cloud
Owns the secure deployment fabric — landing zones, identity, observability and run-cost discipline.
- Secure landing zones
- FinOps
- Observability
Vikas Pandey
Principal Engineer · Generative AI
Designs production-grade GenAI systems — agents, retrieval, evaluation and safety guardrails.
- Agents & RAG
- Evaluation
- AI safety
Case Studies
From AI ambition to deployed capability
Illustrative engagements based on real problem patterns we have solved with enterprise clients.
Financial Services · Pan-AfricaIllustrative
Generative AI for a Tier-1 Bank's Relationship Managers
The bank needed to lift RM productivity across 14 markets without breaching local data-sovereignty rules or its model-risk framework.
- 38%
- Faster client briefing prep
- 2.4x
- Cross-sell suggestions surfaced
- 118
- Days from kickoff to pilot
Stack — Private LLM, RAG over CRM & product data, jurisdictional data partitioning, model-risk governance.
Telecommunications · Multi-marketIllustrative
Customer Churn & Care Automation
Rising churn and contact-centre costs were eroding margin. The board wanted measurable retention impact within two quarters.
- 17%
- Reduction in voluntary churn
- 41%
- Tier-1 tickets auto-resolved
- €6.2M
- Annualised margin uplift
Stack — Churn propensity models, GenAI care agent, event-driven data platform, MLOps with drift monitoring.
Insurance · Composite InsurerIllustrative
Claims Intake & Triage Automation
A composite insurer was losing days per claim to manual intake, document checks and triage — and customer trust with it.
- 72%
- Reduction in intake time
- 3.1x
- Throughput per assessor
- +22
- Net Promoter Score lift
Stack — Document AI, computer vision for damage assessment, decisioning workflow, human-in-the-loop review.
Selective Engagement
Request a private briefing
A confidential 60-minute session with the founders for CEOs, CIOs and boards. We share the diagnostic framework, recent engagement patterns and an honest view of whether a 120-day engagement is the right move for you.
- Confidential. No deck. No sales theatre.
- Founder-led from first call to deployed pilot.
- Selective intake — typically 4–6 boards per quarter.
Typical response within one business day.