What you get
- A prioritized AI roadmap tied to measurable business outcomes
- Clear build-vs-buy decisions backed by cost and feasibility analysis
- Leadership alignment on AI investment priorities and sequencing
Back to services
Lead
AI Consulting
You have AI budget but no clear path to ROI.
We provide strategic AI advisory - readiness assessments, use-case prioritization, architecture reviews, build-vs-buy decisions, and vendor evaluations for teams planning AI investments.
50+
AI audits completed
3x
ROI improvement
2
Week assessment
The Problem
What problem does this service solve?
Your leadership team knows AI matters, but there is no consensus on which use cases to pursue, how to evaluate vendors, or whether to build or buy. Internal teams lack the AI delivery experience to assess feasibility accurately.
Every quarter spent debating AI strategy is a quarter your competitors spend shipping AI products. The cost of indecision compounds faster than the cost of a wrong bet.
Overview
What is AI Consulting?
Most AI strategies stall because the people writing the roadmap have never shipped AI into production. We have - over a hundred times - and that changes what the roadmap looks like.
Most AI strategies fail before implementation begins. Teams chase trending use cases instead of high-impact ones, underestimate data readiness, or pick the wrong build-vs-buy path. The result is wasted budget and delayed outcomes.
We bring implementation experience to strategy work. Every recommendation is grounded in what actually ships, scales, and delivers ROI - not what looks good in a slide deck. We have built 100+ products with AI components and know where projects fail.
You leave with a prioritized roadmap, clear architecture direction, and confidence that your AI investment will deliver measurable business outcomes.
Experience Signal
Advised on AI strategy for organizations across healthcare, fintech, SaaS, and manufacturing - informed by 100+ shipped AI products.
Fit
Is this service right for you?
Good fit
- You're the CEO who approved AI budget six months ago - and still has nothing in production to show for it
- Your last AI pilot failed and now leadership is skeptical. You need a credible reset, not another experiment
- You're the CTO evaluating five AI vendors and none of their sales engineers can answer your architecture questions
- You're preparing an AI roadmap for the board and need it grounded in what actually ships, not vendor hype
Not the right fit
- Teams that only need implementation help without strategic direction
- Organizations not willing to commit leadership time to workshops and decisions
- Projects where the AI use case is already validated and needs only engineering execution
Process
How does AI Consulting delivery work?
1
Phase 1· Week 1
AI Readiness Assessment
We evaluate your data infrastructure, team capabilities, existing workflows, and technology stack to establish a realistic baseline for AI adoption.
Deliverables
- AI readiness scorecard across data, team, and infrastructure
- Gap analysis with remediation recommendations
- Leadership alignment on current state and ambition
2
Phase 2· Week 1-2
Use-Case Discovery and Prioritization
We identify AI opportunities across your business, score them by impact and feasibility, and prioritize a shortlist that balances quick wins with strategic bets.
Deliverables
- Use-case inventory with impact and feasibility scores
- Prioritized shortlist with sequencing rationale
- ROI projections for top-priority use cases
3
Phase 3· Week 2-3
Architecture and Build-vs-Buy Analysis
We evaluate technical approaches for priority use cases - model selection, infrastructure requirements, vendor options, and build-vs-buy tradeoffs with total cost of ownership analysis.
Deliverables
- Architecture options with tradeoff analysis per use case
- Build-vs-buy decision framework with cost projections
- Vendor evaluation for relevant AI platforms and tools
4
Phase 4· Week 3-4
Roadmap and Implementation Plan
We deliver a phased AI roadmap with timelines, resource requirements, risk controls, and success metrics. The plan is designed for immediate execution.
Deliverables
- 90-day and 12-month AI roadmap
- Resource plan with team structure recommendations
- Risk register with mitigation strategies
Outcomes
- A prioritized AI roadmap tied to measurable business outcomes
- Clear build-vs-buy decisions backed by cost and feasibility analysis
- Leadership alignment on AI investment priorities and sequencing
Deliverables
- AI readiness assessment with gap analysis
- Use-case prioritization matrix with ROI projections
- Architecture review and build-vs-buy recommendation
- Vendor evaluation report for relevant AI tools and platforms
- Phased AI roadmap with implementation plan
Success Metrics
- Time from strategy to first AI initiative kickoff
- Alignment score across decision-makers
- Accuracy of feasibility and cost projections vs. actuals
- ROI of first implemented AI use case
Engagement models
2-4 week AI strategy engagement ending in a build-ready roadmap and architecture direction.
Best forTeams that need fast clarity on AI priorities before committing budget.
Core technology stack
AI StrategyArchitecture ReviewVendor EvaluationData AssessmentRoadmapping
Use Cases
Common use cases for AI Consulting
Enterprise AI Strategy for Manufacturing
A manufacturing company wants AI for quality control, predictive maintenance, and supply chain optimization but does not know where to start or which vendor claims to trust.
How we build it
We assess data readiness per use case, benchmark vendor solutions against custom build options, and deliver a phased roadmap starting with the highest-ROI initiative.
Outcome
Leadership aligns on a 12-month AI roadmap. First initiative launches within 8 weeks of strategy completion.
AI Pilot Recovery for SaaS Company
A SaaS company spent 6 months on an AI copilot pilot that never reached production. The team is demoralized and leadership is skeptical about further AI investment.
How we build it
We audit the failed pilot, identify root causes, reassess the use case, and recommend a revised approach with realistic scope, architecture changes, and success criteria.
Outcome
Revised initiative ships to production in 10 weeks with clear quality benchmarks and user adoption targets.
AI Vendor Evaluation for Healthcare Platform
A healthcare platform is evaluating 5 AI vendors for clinical documentation automation but lacks the technical depth to compare claims against reality.
How we build it
We design evaluation criteria, run structured vendor assessments, test key claims against the platform's actual data, and deliver a recommendation with total cost of ownership projections.
Outcome
Vendor selection completed in 3 weeks with confidence. Avoided a vendor that would have cost 2x more over 3 years.
Frequently asked questions about AI Consulting
We are practitioners who build AI products, not analysts who write reports. Every recommendation comes from hands-on delivery experience. We also execute after strategy - same team, no handoff gap between planning and implementation.
Related Services
Next Step
Ready to stop debating AI and start building it?
A 2-4 week engagement that gives your team a prioritized AI roadmap, clear architecture direction, and build-vs-buy decisions you can act on immediately.