Enterprise AI Consulting
Enterprise AI consulting built around measurable outcomes
Your enterprise AI engagement needs more than a slide deck. You need scoped delivery, proof tied to your revenue line, and a team that ships. That is what enterprise AI consulting at Redefine delivers.
Client revenue scaled
$90M+
Parsons Kellogg, technology strategy and AI-powered data architecture driving enterprise scale
Revenue multiple
6×
Growth achieved post-engagement
Projects delivered
50+
Enterprise and growth-stage clients
After you submit
- 1Strategy call within 48 hours
- 2Scoped proposal in 3 business days
- 3Sprint 1 begins within 1 week of sign-off
The Status Quo Is Expensive
Most enterprise AI projects stall before they produce revenue
Your team has the ambition. The gap is always in how strategy connects to production-ready systems that move your numbers.
What typically happens
AI pilots launch without a clear production path
Strategy consultants deliver 80-slide decks with no implementation handoff
Data readiness gets assumed, not audited, causing 6-month delays
AI return on investment is tracked in buzz terms rather than actual revenue or cost reduction
Governance questions surface after deployment, not before
With Redefine
Every AI initiative scoped with a production target from day one
Strategy and implementation delivered by the same team, end to end
Data readiness audited in Sprint 1 before any model development begins
Return on investment measured against your actual revenue line, not proxy metrics
Governance, risk, and compliance built into architecture, not bolted on after
How Your Engagement Runs
From signed brief to live AI system, tracked end to end
Your AI engagement gets a real-time command center. Every initiative, readiness dimension, and sprint milestone visible from day one.
1
AI Readiness Index, tracked live
Data infrastructure, strategy alignment, machine learning infrastructure, and governance are each scored in real time.
2
Active sprint, every task visible
Sprint 1 through Sprint 6, every task, milestone, and deliverable mapped before the next review.
3
Revenue impact projection, not estimates
Each initiative carries projected annual uplift tied to your revenue model, updated as sprints close.
AI Readiness Index
Data Infrastructure0%
Data pipeline audit complete · 3 gaps resolved
AI Strategy Alignment0%
Roadmap signed off by CTO and board
Machine Learning Infrastructure0%
Cloud stack in setup · Sprint 3 target: 80%
Governance Framework0%
Risk model complete · Compliance review in Sprint 4
Overall AI Score
0/100Production-ready
In progress
Day 14 of 21Data pipeline ETL: complete
Feature engineering: complete
Model training v1: running67%
Stakeholder review: Sprint 4
Integration testing: Sprint 4
0
days complete
0
days remaining
Demand Forecasting AILive
Projected annual uplift
+$2.4M
Accuracy gain
+23pp
Customer Churn ModelSprint 3
At-risk revenue protected
$870K
Model accuracy
87%
Inventory Optimization AISprint 4
Target cost reduction
$1.1M
Timeline
6 weeks
Total projected uplift
$0year oneUpdating
What You Get
AI consulting delivered across every layer of your enterprise
Strategy without implementation is a report. Implementation without strategy is a risk. Your engagement covers both.
AI Strategy and Roadmap
You get a board-ready AI roadmap tied to your actual revenue model. Use cases are prioritized by return on investment, not novelty. Every initiative gets a build-versus-buy decision, a data dependency map, and a production timeline before a single sprint starts.
Use-case scoringReturn on investment modelingBoard-ready output
AI Model Architecture
You get architecture decisions made before you commit infrastructure spend. Model selection, fine-tuning approach, inference latency, and serving layer are all specified upfront. You own the architecture document, not just the output.
Large language model selectionFine-tuning strategyInference design
Data Readiness and Engineering
AI models are only as good as the data feeding them. Your engagement includes a full data readiness audit in Sprint 1. We identify gaps, build the pipelines to close them, and give your team a data quality score tied to your AI initiative targets.
Data auditPipeline engineeringQuality scoringFeature stores
AI Governance and Risk
Your board will ask about AI risk before your CFO asks about return on investment. You get a governance framework, bias testing protocols, explainability requirements, and a compliance readiness report aligned to your industry before models go live.
Risk frameworkBias testingCompliance mapping
AI Integration and Automation
AI that lives outside your existing systems is a side project. Your engagement wires AI outputs directly into the tools your team already uses: enterprise resource planning, customer relationship management, data warehouse, or custom workflows. Automation follows where it reduces actual labor cost.
Enterprise resource planning integrationAPI designWorkflow automation
Proof
From fragmented operations to $90M in annual revenue
See what enterprise technology strategy and AI-powered data architecture delivers when scoped and delivered as a single engagement.
Promotional ProductsEnterprise
A multi-channel distributor managing 30+ stores and over one million inventory items across fragmented enterprise resource planning, analytics, and fulfillment systems.
The Challenge
No unified reporting layer, manual warehouse workflows, and disconnected data across every system. Decision-making was slow and unreliable. The team could not see their own business clearly enough to scale it.
What Changed
Power BI was integrated across all stores and Dynamics 365 enterprise resource planning, building a real-time analytics layer. A headless commerce architecture centralized inventory management across every storefront. Custom application programming interface connections linked enterprise resource planning, customer relationship management, Power BI, and mobile applications into a single cohesive platform.
The Outcome
$0
annual revenueScaled from under $14 million to over $90 million through a unified technology strategy, real-time analytics, and AI-powered data architecture.
30+
stores unified
1M+
items managed
6.4×
revenue growth
Why Redefine
The difference between strategy that ships and strategy that stalls
Most enterprise AI consulting firms are broad, proof-light, and hand you a report at the end. Here is how the Redefine engagement model differs at each decision point.
Capability
Typical consulting firms
Redefine
Strategy tied to revenue line
Same team: strategy and implementation
Data readiness audit in Sprint 1
Governance built into architecture
Line-by-line scoped pricing upfront
Sprint demos before final delivery
Proof tied to same service category
FAQ
Answers before you commit to a call
Real questions from chief technology officers and chief information officers evaluating enterprise AI consulting. Answered directly.
Your engagement covers AI strategy and roadmapping, use-case prioritization by return on investment, data readiness auditing, model architecture design, integration engineering into your existing systems, governance and compliance frameworks, and production deployment. You get a scoped proposal before committing, and every sprint ships a deliverable you can act on immediately.
Sprint 1 produces a scored AI readiness report and a prioritized use-case roadmap within 3 weeks. Your first live model or integration is deployed in Sprint 3 or Sprint 4, depending on data readiness. Revenue or cost-reduction impact from the first initiative is visible within 8 to 12 weeks of the engagement start date.
3 to 4 hours per week: one sprint review session, async feedback on deliverables, and a final milestone sign-off. You do not need to manage developers, write briefs, coordinate quality assurance, or produce documentation. We handle all of that. Your role is to validate business context and approve production-ready work.
Governance is built into the engagement, not added at the end. Before any model accesses your data, we produce a data access and security design document. Compliance requirements, data residency, personally identifiable information handling, and model audit trails are specified in Sprint 1. Your legal and security teams review and sign off before implementation begins.
Yes. A scoping call and a brief technical audit of your current state is all that is needed to understand where the work stands. We then scope from your current position rather than from zero. Many engagements begin with rescuing a stalled pilot or accelerating an initiative that has hit a data or architecture wall.
Every engagement is scoped before work starts. You get a line-by-line proposal with sprint deliverables, milestones, and costs before you commit. No retainer ambiguity, no hourly rate surprises. See the full pricing model at AI consulting pricing.
Is This For You?
This engagement is not for everyone
We work best with a specific type of enterprise team. Read this before booking.
You are a strong fit if
- Your company has 50 or more employees and an existing data environment.
- Your chief technology officer or chief information officer is asking for an AI strategy that connects to profit and loss.
- You have run AI pilots that stalled before production or struggled to prove value.
- You want one team that handles strategy and implementation without a handoff gap.
This is not the right fit if
- You are a pre-seed startup with no data infrastructure yet.
- You expect a fully autonomous AI to replace your team by month two.
- You want a vendor relationship, not a strategic delivery partner.
- Your leadership team cannot commit 3 to 4 hours per week for the engagement period.
Not sure? Tell us your situation and we will be straight with you. Submit a brief and we will assess fit before proposing anything.
Get Your Scoped Proposal
Submit Your Brief
Scoped before work starts. Line-by-line pricing. No commitment to receive a proposal.
1
You submit your brief (takes under 3 minutes)
2
A strategy call within 48 hours
3
Scoped proposal with line-by-line delivery in 3 days
4
Sprint 1 begins within 1 week of sign-off
Form
Call within 48 hours · Proposal in 3 days · Sprint 1 within 1 week of sign-off
Brief received
Brief received, we will review your workflow and send a scoped proposal within 3 business days. Expect a call from our team within 48 hours to align on your priorities before the proposal goes out.
Call in 48 hours
Proposal in 3 days
SOC 2 process
50+ projects
Ready When You Are
Your AI strategy call is 48 hours away
No commitment. No pitch. A direct conversation about your situation and whether this engagement makes sense for your team.