Make the Right Technical Decisions When Success Depends on Data Readiness
Most technology projects fail not from lack of expertise, but from fragmented data, inconsistent quality, and missing governance. We help regulated organizations assess data readiness and build the technical foundations that make innovation and technology projects successful.
You Have an AI Strategy.
But Not a Data Readiness Strategy.
The gap between AI ambition and AI execution is almost never about the AI. It's about what's underneath it.
- ✓AI strategy approved by leadership
- ✓Budget allocated and teams assembled
- ✓Modern cloud infrastructure in place
- ✓Talented data scientists and engineers hired
- ✗Data is fragmented with no integration layer
- ✗No consistent definitions or quality standards
- ✗Can't trace data lineage or transformations
- ✗Missing governance and accountability structures
- ✗Regulatory requirements create bottlenecks
of AI initiatives fail at the data layer, not the AI layer. We help you assess where you actually stand across seven dimensions of data maturity, then build the foundation your AI projects require to succeed.
Focused Services.
One Clear Outcome.
Whether you need clarity on where you stand or proof that a new technology will work, we deliver technical strategy grounded in production experience.
Digital Transformation Assessment
Objective assessment of your data maturity across 7 dimensions, with a quantified scorecard, gap analysis, and executable 12–18 month roadmap.
- Current state assessment across 7 dimensions
- Quantified Transformation Readiness Scorecard
- Gap analysis and prioritized roadmap
- Target architecture design
- Basis of estimate (time / cost / resources)
Innovation Prototype Engineering
Working prototypes of emerging technologies — blockchain, AI/ML, graph, digital thread, digital twin (etc.) — built in regulated environments, with a go/no-go recommendation.
- Working source code (documented, clean)
- Deployment scripts and infrastructure
- 90-day demo environment
- Technical feasibility assessment
- Go/no-go recommendation + production roadmap
Fractional Technical Leadership
Ongoing senior technical guidance on architecture, vendor selection, and technical decision-making. Works as a follow-on to an assessment or as a standalone engagement for organizations that need senior expertise without a full formal project.
- Continuous technical guidance
- Architecture reviews and decision support
- Vendor evaluation and selection
- Team capability development
- Executive communication support
Built for Regulated Industries
Where data complexity intersects with strict compliance requirements and high-stakes AI ambitions.
We've Built the Systems
We're Advising You About
Not theory. Not slides. Production systems in the most demanding regulated environments.
Production clinical data management system for multi-study pooled analysis across hundreds of trials. Millions of subjects, graph-based architecture, CDISC-compliant with FDA submission-ready outputs and a GraphQL API for ML model training.
Production NFT platform on Flow blockchain with hybrid on-chain/off-chain architecture at scale. Event-driven microservices solving the trust problem while maintaining performance under live transaction load.
Enterprise data strategy from fragmented systems to integrated AI-ready foundation. Governance framework design (CDO, stewardship, policies), Azure-based integration architecture, master data management and regulatory compliance.
7 Dimensions of Data Readiness
We assess your organization across seven critical dimensions, scoring each 0–4. The result is a quantified view of where you stand — and a prioritized roadmap to close the gaps that matter most.
Can you access and combine data from all critical systems? Is it real-time or batch? Can the infrastructure handle AI workload volumes?
Do stakeholders trust the data? Are quality issues known and measured? Can you trace and fix problems when they occur?
Is there clear ownership of data assets? Are policies defined and enforced? Is there a decision-making framework in place?
Can you find data when you need it? Do you know where it came from? Can you trace every transformation end-to-end?
Are key entities consistently defined? Is there a single source of truth? Can you reconcile duplicates across systems?
Can your infrastructure support AI workloads? Is architecture modern and flexible? Can you scale compute and storage independently?
Do you have the right team structure? Are data engineering capabilities sufficient? Can the organization sustain AI initiatives long-term?
Every dimension scored 0–4. Benchmarked against industry peers. Clear priorities and an actionable roadmap.
A Focused 2–3 Month
Engagement Process
Three phases. Clear deliverables at each stage. Designed to give you answers, not billable hours.
- Stakeholder interviews (business + technical leaders)
- Data landscape mapping and architecture review
- Data Readiness Scorecard across all 7 dimensions
- Gap analysis with priorities and risk assessment
- Stakeholder alignment workshop
- Target state architecture + technology recommendations
- 12–18 month phased roadmap with milestones
- Basis of estimate (time, cost, resources)
- Organizational design recommendations
- Executive summary and board-ready presentation
- Validation workshop with key stakeholders
- Technical deep-dives for implementation teams
- Vendor evaluation criteria
- Implementation playbook
- Success metrics framework
Start With a 30-Minute
Conversation
No obligation. We'll discuss your AI initiatives, current data challenges, technology innovation projects, and whether an assessment, a prototype, or technical leadership makes sense for your organization.