Readiness first
Data quality, infrastructure maturity, team capabilities, and governance gaps assessed upfront.
Strategy · Architecture · Implementation
AI strategy that ships
We help enterprises cut through AI hype and build practical strategies that deliver measurable ROI — from readiness assessments and architecture design to vendor evaluation and implementation roadmaps grounded in 10+ years of production AI delivery.
2–4 wkReadiness
4–8 wkFull strategy
200+Projects
EngineersNot slides
What we build
Consulting that builds, not just advises
Most AI consulting firms deliver a strategy deck and walk away. We're engineers who consult — every recommendation we make, we can build. With 200+ projects across healthcare, fintech, insurance, and SaaS, we bring pattern recognition that avoids the pitfalls that derail AI initiatives.
Use case ROI
Impact vs feasibility scoring — prioritize the highest-ROI opportunities, not the flashiest demos.
Vendor objectivity
Hands-on POC tests with your data — compare alternatives beyond vendor marketing claims.
Build-ready plans
Architecture, timelines, and budgets grounded in what we've actually shipped in production.
Capabilities
What we deliver
End-to-end delivery — from discovery through production and ongoing optimization.
AI Readiness Assessment
Evaluate data, infrastructure, team capabilities, and organizational readiness — with a prioritized action plan.
- Data quality audit
- Infra maturity score
- Skills gap analysis
Use Case Identification
Map business processes against AI capabilities — score by impact, feasibility, and data availability.
- ROI modeling
- Quick-win mapping
- Risk classification
Architecture Design
Scalable AI architectures — data pipelines, model serving, monitoring, and integration patterns.
- Reference architectures
- Security & compliance
- Cost projections
Vendor Evaluation
Objective comparison using your actual data — technical capabilities, TCO, and lock-in risk.
- POC scorecards
- Benchmark reports
- Contract guidance
POC Development
Rapid proof-of-concept with your real data to de-risk investment before full-scale build.
- 2–4 week sprints
- Eval harnesses
- Go/no-go criteria
AI Governance
Bias detection, explainability, HIPAA/SOC2/GDPR compliance, and model risk management frameworks.
- Policy templates
- Audit readiness
- Ethics guidelines
Where teams start
Sound familiar?
Most enterprise AI programs begin with one of these — we meet you where you are and build a practical path forward.
"We want to use AI but don't know where to start"
AI readiness assessment + use case prioritization workshop
"We have a use case but need the right architecture"
Technical design sprint + technology selection with POC
"Our AI POC works but won't scale to production"
Production architecture review + scaling roadmap
"We need to evaluate AI vendors objectively"
Hands-on vendor comparison with your actual data
"Our AI project failed and we need to course-correct"
Technical audit + recovery plan with realistic milestones
How we work
Discovery to production
A proven delivery rhythm — scoped for accuracy, structured for scale.
Discover
Stakeholder interviews, data audit, and current-state architecture review.
Assess & prioritize
Readiness scoring, use case ranking, and ROI modeling with executive alignment.
Design & validate
Architecture blueprint, vendor selection, and POC to prove feasibility.
Roadmap & build
Phased implementation plan — we can execute the build or advisory-support your team.
Deliverables
What you get
Concrete outputs at every phase — not abstract frameworks. Every deliverable is build-ready.
Deliverable 01
Strategy
Deliverable 02
Architecture
Deliverable 03
Evaluation
Deliverable 04
Execution
Proof of work
Shipped systems
Production AI systems with measurable business outcomes.
AI-Powered EHR Onboarding
End-to-end AI strategy for automating patient EHR onboarding — assessment through production across 12 facilities.
82%Faster onboarding
$1MAnnual savings
Multi-Agent CRM Pipeline
AI strategy and implementation for multi-agent CRM automation — lead scoring, outreach, and pipeline management.
34%More pipeline
$1.2MRevenue
LLM Contract Analysis
Architecture design and vendor evaluation for enterprise contract analysis with fine-tuned LLM deployment.
87.5%Faster review
$480KAnnual savings
2–4 wkReadiness audit
4–8 wkFull strategy
10+Years AI delivery
200+Projects shipped
01What does an AI consulting engagement include?
AI readiness assessment, use case identification and prioritization, architecture and technology selection, vendor evaluation, implementation roadmap with timelines and budgets, POC development, and ongoing advisory during implementation.
02How long does an AI strategy engagement take?
Focused readiness assessment: 2–4 weeks. Comprehensive strategy with architecture and roadmap: 4–8 weeks. Ongoing advisory retainers for implementation phases.
03Do you help implement the solutions you recommend?
Yes — we're engineers first. We design strategies and build the systems: data pipelines, model development, infrastructure, and production deployment. Every recommendation is practical and achievable.
04How do you evaluate AI vendors and platforms?
Technical capabilities, scalability, security/compliance, TCO, lock-in risk, and infrastructure alignment — validated with POC tests using your actual data, not vendor demos.
Next step
Ready to build your AI strategy?
Book a free 30-minute assessment call — we'll discuss your use cases and outline a practical path forward.