01 Enterprise Strategy02 AI & Data Strategy03 Scaled Agile04 Process Optimization
Service 02

AI & Data Strategy -
built on solid ground.

Organizations racing to deploy AI without a data foundation are setting themselves up for expensive failure. We design AI and data strategies grounded in your actual capabilities, prioritizing the use cases with real near-term value and a credible path to scale.

What you walk away with
  • AI readiness assessment across data, talent, infrastructure, and governance
  • Prioritized use case roadmap with ROI projections and risk factors
  • Data governance framework and architecture principles
  • Build vs. buy analysis for key AI capabilities
  • Executive briefing on AI risk, compliance, and responsible use
Why This Is Hard

The AI readiness gap most
organizations do not see coming.

Every executive has an AI strategy. Most are aspirational documents that assume data infrastructure, governance, and talent that do not exist. The gap between "we want to be AI-driven" and "we have the data foundation to do that" is where most AI investments stall, expensively and visibly.

The organizations that succeed at AI are not the ones with the best models. They are the ones with trusted, governed, and accessible data.
Healthcare DataRegulated IndustriesMulti-cloud ArchitectureData GovernanceMLOps

AI use case selection

We cut through the noise, vendor demos, analyst hype, internal enthusiasm, to identify the AI applications that will actually deliver value in your specific environment. Selection criteria include data availability, change capacity, regulatory constraints, and time-to-value.

Data foundation assessment

Before recommending any AI investment, we evaluate the actual state of your data: quality, accessibility, ownership, and governance maturity. This is the conversation most vendors skip and most consultants rush past. We do not.

Responsible AI & risk

AI risk in regulated industries, healthcare, financial services, public sector, is a governance and compliance problem as much as a technical one. We design AI strategies that include the risk framework, oversight model, and audit trail from the beginning.

What We Build

Three interconnected
deliverables.

AI Strategy & Roadmap

A prioritized portfolio of AI use cases, sequenced by value, data readiness, and organizational change capacity. Each use case comes with a clear business case, data requirements, build/buy/partner recommendation, and risk assessment.

Data Governance Framework

Ownership model, data stewardship structure, quality standards, and the policy architecture that makes data trustworthy across the organization. Designed to be operationally realistic, not a governance ideal that nobody enforces.

Architecture Principles

Technology-agnostic data architecture principles that guide platform selection, integration decisions, and infrastructure investment. Includes evaluation of current-state architecture against the demands of the AI use cases you have prioritized.

35+
Client engagements spanning AI readiness, data architecture, and analytics strategy
$10M+
Analytics and data platform investments advised and overseen
4
Industries with deep domain knowledge of data and regulatory context
Also In Scope

Analytics platform strategy
and vendor selection.

Platform selection decisions are among the highest-stakes technology choices an organization makes. We bring an independent, vendor-neutral perspective grounded in your specific business requirements, data reality, and organizational capability.

01

Requirements definition

Business and technical requirements derived from your prioritized use cases, not the vendor capability checklist.

02

Market evaluation

Structured vendor assessment against your requirements. We have evaluated most major platforms across multiple client contexts and know where demo-to-deployment gaps appear.

03

Selection & negotiation support

Final recommendation with rationale, implementation sequencing, and commercial negotiation guidance. We work for you, not the vendor.

What makes this different
No vendor relationships
We receive no referral fees, no partner commissions, and no consideration from vendors. Our recommendation is based solely on what is right for your organization.
Data foundation first
We will not recommend a platform investment until we are confident the data foundation and governance model are in place to make it succeed.
Gartner-level analytical rigor
20+ years advising C-suite leaders on technology decisions at Gartner means we bring a research-grade evaluation methodology to every platform assessment.