Lead

AI consulting

You have AI budget. You don't have a path to ROI.

50+

AI audits completed

3x

ROI improvement

2-4

Weeks to roadmap

Trusted by teams at

VodafoneNikeGeneral ElectricMicrosoftT-MobileBank of America

The Problem

What problem does this service solve?

Your leadership team knows AI matters, but there's no consensus on which use cases to pursue, how to evaluate vendors, or whether to build or buy. Internal teams don't have the delivery experience to assess feasibility accurately.

Every quarter spent debating AI strategy is a quarter competitors spend shipping AI products. The cost of indecision compounds faster than the cost of a wrong bet.

What you get

  • A prioritized AI roadmap tied to measurable business outcomes
  • Clear build-vs-buy decisions backed by cost and feasibility analysis
  • Leadership aligned on AI investment priorities and sequencing

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 stall before implementation begins. Teams chase trending use cases instead of high-impact ones, underestimate data readiness, or pick the wrong build-vs-buy path. Budget burns, outcomes slip.

We bring delivery experience to strategy work. Every recommendation is grounded in what actually ships, scales, and delivers ROI - not what looks good in a deck. We've built 100+ products with AI components and know where projects die.

You leave with a prioritized roadmap, clear architecture direction, and confidence that your AI investment will deliver measurable outcomes inside the quarter, not next year.

Experience Signal

Advised on AI strategy for organizations across healthcare, fintech, SaaS, and manufacturing - backed by 100+ shipped AI products. We don't write strategies we can't deliver.

What we build

AI consulting services we deliver

AI readiness assessment

Data, team, and infrastructure assessment across every dimension that decides whether an AI initiative succeeds or stalls.

Use case discovery and prioritization

Structured workshops that produce a scored use case backlog with impact, feasibility, and sequencing rationale.

Build vs buy analysis

Total cost of ownership, risk, and speed-to-value analysis for every priority use case with a clear recommendation.

AI vendor evaluation

Vendor-neutral evaluation with defined criteria, proof-of-concept testing, and honest scoring against your real data.

Architecture review

Review of an existing AI architecture or plan with concrete changes, risk flags, and remediation direction.

AI pilot recovery

Root-cause review of a failed pilot and a revised plan your team can actually ship.

90-day and 12-month roadmaps

Phased delivery plans with resource needs, risk controls, and success metrics mapped to business outcomes.

Board-ready AI strategy

Strategy deliverables your CEO, CFO, and board will actually read - tight, specific, and grounded in delivery reality.

Fit

Is this service right for you?

Good fit

  • CEOs who approved AI budget six months ago and have nothing in production to show for it
  • Teams whose last AI pilot failed and need a credible reset, not another experiment
  • CTOs evaluating five AI vendors where none of the sales engineers can answer architecture questions
  • Leaders prepping an AI roadmap for the board and need it grounded in what actually ships
  • Orgs planning a significant AI investment and want a second opinion before they commit

Not the right fit

  • Teams that just need implementation help without strategic direction
  • Orgs not willing to commit leadership time to workshops and decisions
  • Projects where the use case is already validated and just needs engineering execution

Process

How does AI consulting delivery work?

1
Phase 1· Week 1

AI readiness assessment

We evaluate your data, team, workflows, and tech stack to set a realistic baseline for AI adoption. No hand-wavy scoring - every gap gets a remediation path.

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 on impact and feasibility, and shortlist the ones that balance 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, vendor options, and build-vs-buy tradeoffs with real cost projections.

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 plans, risk controls, and success metrics. The plan is designed to start execution the Monday after delivery.

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 aligned on AI investment priorities and sequencing
  • A vendor shortlist you can actually defend to the board

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
  • Executive summary deck for the board

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 the first implemented AI use case
  • Number of stalled pilots revived into production

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 AssessmentRoadmappingBuild-vs-Buy Analysis

Use Cases

Common use cases for AI consulting

Enterprise AI strategy for manufacturing

A manufacturer wants AI for quality control, predictive maintenance, and supply chain optimization - but has no idea 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 a 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 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 real user adoption.

AI vendor evaluation for a healthcare platform

A healthcare platform is evaluating 5 AI vendors for clinical documentation automation but doesn't have the technical depth to separate real claims from sales talk.

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 wrapped in 3 weeks with confidence. Avoided a vendor that would have cost 2x more over 3 years.

What clients say

Real feedback from real teams

I spent years at Amazon fighting static surveys. RaftLabs built a working prototype in four days that already outperformed every survey tool I'd used. Twelve weeks later we had a full SaaS that product teams actually want to use.

Founder

Ex-Amazon PM - Perceptional

We went from text surveys that nobody finished to AI phone interviews that people actually enjoy. The voice agents handle the whole conversation, and the analytics tell us what we need to know without reading a single transcript.

Cherian Koshy

Behavioral Strategist - USA Today Bestselling Author

Proof

Recent ai consulting work

LeadFrom strategy to shipped AI SaaS for Perceptional
4x

Deeper insights

12 weeks

Concept to launch

Working prototype in four days. Full SaaS in twelve weeks.

Read case study
LeadAI strategy and delivery for Cherian Koshy
12 weeks

To production

Global

Call reach

Text surveys nobody finished became phone interviews people enjoy.

Read case study

Industries

AI consulting for your industry

Frequently asked questions about AI consulting

We're practitioners who build AI products, not analysts who write reports. Every recommendation comes from hands-on delivery experience. And we 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.