47 AI projects delivered130 brands served
AI Consulting Services
Turn your AI strategy into a competitive advantage
Your competitors are already deploying AI. The gap between exploring and shipping a real system is where most organizations stall. Redefine's AI consultants qualify your use case, scope the build, and stay accountable to outcomes.
The cost of stalling
Most AI initiatives fail
Most AI initiatives fail
before they ship
You have data, ambition, and a mandate. Yet 70% of enterprise AI initiatives never reach production. The problem is rarely the technology.
With Redefine
- Use case qualified in week one. Structured discovery before any code ships.
- Sprint-by-sprint delivery. Working deliverables every two weeks with defined outputs and reviews.
- Outcomes your board can measure. Key performance indicators tied to revenue or operations from day one.
Without AI consulting
- Unclear scope. Proofs-of-concept loop forever with no production pathway or accountable delivery.
- Vendor risk. Dashboards instead of working systems. The engagement ends before production.
- Rising cost of inaction. Every quarter without shipped AI widens the gap on speed, margin, and experience.
Who this is for
Built for the executive who owns the outcome
AI consulting looks different depending on where you sit. Select your role below to see what Redefine delivers for you specifically.
You need AI that integrates with your stack and ships without blowing up your architecture
Architecture-first consulting
Every AI system is scoped against your existing infrastructure. No rip-and-replace. No vendor lock-in built into the design.
Integration scoping in week one
Discovery maps every system the AI needs to connect to. You receive a written integration plan with dependency risks identified before build starts.
Code ownership stays with you
All intellectual property transfers on sign-off. Your team can maintain, extend, or hand off to another vendor after delivery. No black box.
Large language model integrationRetrieval-augmented generation architectureMLOps pipelineAPI security
Use case
Automated request-for-quote response drafting
Data readiness
72% complete, 2 sources pending
Integration risk
Customer relationship management auth layer: OAuth 2.0 needed
Sprint 1 output
Working prototype, customer relationship management connected
You need AI governance, security controls, and a clear line from pilot to enterprise rollout
Governance built into delivery
Every engagement includes a risk register, data handling policy, and sign-off gate before production. Your legal team does not receive a surprise.
Rollout sequencing
Pilot, then department, then enterprise. Each phase has defined success criteria and an exit gate before the next phase starts.
AI governanceData privacyEnterprise rollout
Data controls
Active
Risk gates
4 of 4
Audit log
Live
Personally identifiable information handling policy
ApprovedLegal sign-off gate
PassedYou need AI features that ship on time, delight users, and do not break existing product workflows
User-facing AI feature design
Discovery includes user research and user experience scoping. Your AI feature ships with a clear interaction model, not just a backend endpoint.
Sprint cadence matches your roadmap
Two-week sprints sync with your existing release cycle. No separate AI timeline that drifts out of alignment with your product roadmap.
AI feature scopingGenerative AI user experienceRoadmap alignment
Prompt layer design
DoneStreaming response interface
In reviewError state handling
In progressA/B test instrumentation
Sprint 4You need AI that removes manual work, integrates with your current tools, and runs reliably without your team babysitting it
Process mapping before build
Consulting starts by documenting the exact manual workflows AI will replace. Your team reviews and approves before a single line of automation ships.
Managed handoff and monitoring
Delivery includes documentation, operator runbooks, and 30-day post-launch monitoring. Your team can run the system independently from day one.
AI automationWorkflow mappingManaged AI
Tasks automated today
0
Hours saved this week
0
Invoice processing agent
LiveData reconciliation pipeline
LiveWeekly operations reporting
DeployingWhat Redefine delivers
Every engagement ships a working system, not a slide deck
AI strategy and use-case qualification
Discovery sessions produce a written use-case brief: the problem, the AI approach, the data requirements, the integration path, and the success metric. You approve before build starts.
Deliverables
Use case briefRisk registerData map
Architecture design and tech selection
Your AI system needs the right model, the right retrieval layer, and the right infrastructure. Redefine consultants recommend and justify every technology choice in writing before you commit.
Deliverables
Architecture documentModel selection rationale
AI governance and risk controls
Production AI systems need guardrails. Every Redefine engagement ships with a data handling policy, output monitoring setup, and documented escalation paths your legal and compliance teams can audit.
AI governance consultingAI advisory on demand
Access senior AI consultants for vendor selection, model evaluation, request-for-proposal review, and executive briefings without committing to a full build engagement. Scoped by hour or by project.
AI strategy consultingFrom brief sign-off to production in 6 to 10 weeks
Every engagement follows the same five-phase model: discovery, architecture, build sprints, governance, and production handoff.
- Days 1 to 5Discovery, use case brief, and scoped proposal
- Days 6 to 10Architecture blueprint and integration map
- Weeks 2 to 6Build sprints with working software every two weeks
- Weeks 9 to 10Production deploy, handoff, and 30-day monitoring
Sprint-by-sprint AI delivery
Working software, every two weeks. Not reports, not presentations. Your stakeholders see the system running in a real environment before any invoice is finalized.
Sprint 1Prototype live
Sprint 2Data integrated
Sprint 3Stakeholder review
Sprint 4Production deploy
0
AI projects delivered
0
Days to first sprint review
$70M+
Client revenue impact tracked
0
Enterprise brands served
Client results
Real systems. Measurable outcomes.
Enterprise resource planning and AI automationB2B operationsSystem integration
The business
A multi-channel B2B distributor managing orders, inventory, and customer data across fragmented platforms with a growing operations team and no single source of truth.
The problem
Inventory, orders, and customer data lived in separate systems. Staff spent hours each day manually reconciling records across platforms. As volume grew, operational errors and customer delays compounded every week.
The solution
An AI-integrated enterprise resource planning environment with two-way synchronization across all sales and fulfillment channels. Automation replaced manual data entry across every major workflow. All customer and inventory data was unified into a single live source.
The result
1
Week 2
Manual reconciliation workflows documented and automation scoped
2
Week 5
Live two-way integration with Shopify and fulfillment partner
3
Week 8
Full production deploy: all platforms unified, zero manual reconciliation
Headline metric
0%
Reduction in manual data-handling hours per week. Integrated systems now deliver consistent, reliable data across all platforms with no daily reconciliation effort from operations staff.
Response time
48 hours
Proposal delivery
3 business days
Sprint 1 start
Within 1 week
Code ownership
100% yours
The Redefine delivery model
From signed brief to production AI in 6 to 10 weeks
Every engagement follows a structured five-phase model. Click any phase to see what happens inside it.
1
Discovery
Days 1 to 5
2
Architecture
Days 6 to 10
3
Build sprints
Weeks 2 to 6
4
Quality assurance and governance
Weeks 7 to 8
5
Production and handoff
Weeks 9 to 10
What happens
Stakeholder interviews and goal setting
Data source audit and readiness score
Use case prioritization and feasibility check
Deliverables you receive
Written use case briefDay 5
Data readiness reportDay 5
Scoped project proposalDay 5
Why Redefine
Most AI consulting firms sell roadmaps. We sell shipped systems.
Other implementation partners produce thorough reports and strong proposals. They are broad but often generic and proof-light. Their scope rarely connects to a specific business key performance indicator. When the engagement ends, you own a document, not a system.
Ideal client qualification
We tell you if you are not ready
Discovery produces a written readiness score. If your data is not ready or the use case is not viable, we say so before any build contract is signed. You cannot lose money on a bad AI project with Redefine.
Outcome accountability
Every sprint has a defined, measurable output
Not "we made progress." A specific deliverable with acceptance criteria your team signs off on. Every invoice is tied to a completed sprint output, not elapsed time.
Transparent pricing
Scoped and priced before work starts
Line-by-line pricing in the proposal. No hourly bleed, no change-order culture. Your finance team can budget the engagement before signing. See AI consulting pricing
Smaller team, faster decisions
A senior consultant on every call, not an account manager
You speak to the person building your system. No handoffs to junior delivery teams after the proposal stage. The consultant who scoped it ships it.
Intellectual property ownership
Your code, your models, your data
Full intellectual property transfer on sign-off. You own every line of code, every fine-tuned model weight, and every integration. No software-as-a-service dependency, no recurring licensing tied to our platform.
Go / no-go gates
Build starts only when discovery passes
Every engagement ends discovery with a written readiness score. If data, scope, or risk fails the gate, we stop before a build contract is signed.
Use case qualifiedPass
Data readiness 72%Review
Sprint 1 scopedReady
Before you decide
Honest answers to the questions that stop good AI projects
Your internal engineers are valuable, and this engagement does not compete with them. Consulting fills the gap between your team's depth in your specific stack and the pattern knowledge that comes from shipping many AI systems across many industries. We also bring a neutral scoping function: an outside team is better positioned to push back on scope, challenge assumptions, and say no to a bad use case than an internal team reporting to the same executive who owns the budget.
Discovery and architecture take one to two weeks. Build sprints run two weeks each. A focused single-use-case engagement reaches production in six to ten weeks. Multi-use-case or enterprise rollout programs run longer, but each use case follows the same sprint structure, so you see production output from the first sprint while later use cases are still in design.
That is a good place to start. A discovery engagement is scoped to help you identify, prioritize, and pressure-test your top three AI use cases against your data readiness and operational context. You receive a written brief and a recommended build order. No build commitment is required at discovery stage. Take the AI readiness assessment to start that conversation.
Engagements are scoped and priced before any work starts. Discovery is priced as a standalone project. Build sprints are scoped by deliverable, not by time. Most single-use-case engagements scope at a fixed project price with milestone payments tied to sprint completions. See full AI consulting pricing for bands and what drives scope. You receive a line-by-line proposal within three business days of your discovery call.
Every sprint has written acceptance criteria. If a sprint output does not meet criteria, it does not advance to the next phase and the sprint is revisited at no additional cost. Performance expectations are defined in the scoping document before build starts, not retrofitted at the end. This is why the discovery phase is non-negotiable: acceptance criteria cannot be written without a qualified use case and a known data set.
Is this engagement right for you?
We are a strong fit for some teams. Not for others.
Good fit
You have a specific operational problem you want AI to solve, not a general interest in AI
A decision-maker is available for weekly sprint reviews (two to four hours per week)
You have some structured data the AI system can train on or retrieve from
You want a production system by the end, not just a strategy document
Not the right fit
You need a deck to present to the board with no immediate intention to build
You have no structured data and no clear source of training or retrieval data
No team member can commit time for async feedback and sprint reviews
Not sure? Tell us your situation and we will be straight with you. Submit your brief
Start your AI consulting brief
Tell us what your team does manually that AI should handle
No commitment. No pitch. You get a scoped proposal within three business days of your discovery call.
Form
Call within 48 hours · proposal in 3 days · Sprint 1 within 1 week of sign-off
Call in 48 hours
Proposal in 3 days
47 projects delivered
Code stays yours
Brief received
Brief received, we will review your workflow and send a scoped proposal within 3 business days. Expect a call within 48 hours to clarify any details before we scope the engagement.
Ready when you are
Your AI system could be in production by next quarter
The gap between deciding to explore AI and shipping a working system is smaller than you think. Tell us what you need and we will scope it inside 72 hours.