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✓ On-time delivery
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2-wk sprints
AI Consulting Services

AI Strategy & Roadmaps That Drive Real Business Outcomes

From AI readiness audits to full implementation roadmaps — we help businesses identify where AI creates ROI, then build it. Technology-agnostic strategy.

AI Readiness Audit
Implementation Roadmap
ROI-First Approach
Tech-Agnostic
Free first consultationNo commitment needed

AI Strategy & Delivery

From roadmap to production

100%

code & IP yours from day one

typical MVP timeline
est.

6–10 wks

48h

Avg. Response Time

no surprises, ever

What is AI consulting?

AI consulting is the strategic and technical advisory process that helps organizations identify where artificial intelligence creates genuine value, determine the right approach and technology stack, assess data and infrastructure readiness, and build a practical implementation roadmap. It prevents expensive mistakes: choosing the wrong tool, building something that cannot scale, or investing in AI where the problem is actually a process issue. CodeShiper delivers AI consulting that leads directly to implementation — not a strategy document handed to a different team.

Services

What our consulting engagements cover

From initial readiness assessment to ongoing advisory — we cover every decision point in an AI adoption journey with engineers who have built production AI systems.

01

AI Readiness Audit

Assess your organization across four dimensions: data quality and accessibility, infrastructure readiness, team capability, and business process maturity. Identifies gaps before you invest in AI that cannot succeed.

02

Use Case Discovery & Prioritization

Map every AI opportunity in your business, score each by data availability, technical feasibility, business impact, and implementation risk. Deliver a prioritized roadmap with effort and value estimates for each use case.

03

AI Architecture Design

Design the technical architecture for your AI system — model selection, retrieval strategy, data pipeline, infrastructure, evaluation framework, and integration pattern. Written architecture document you can give to any development team.

04

Build vs Buy Analysis

Evaluate whether to build a custom AI system, integrate an off-the-shelf AI tool, or combine both. Compare on total cost of ownership, feature fit, data privacy, vendor lock-in risk, and timeline. Written recommendation with full analysis.

05

AI Vendor & Tool Selection

Evaluate AI platforms, model providers, vector databases, MLOps tools, and AI-native SaaS products against your requirements. Comparison matrices, proof-of-concept evaluations on your data, and a written vendor recommendation.

06

AI Governance & Risk Advisory

Advise on AI risk frameworks, hallucination detection, bias testing, audit logging, human-in-the-loop design, and regulatory compliance. Build internal governance documentation appropriate for your organization size and risk profile.

What you get

Deliverables you can actually act on

Every engagement produces written, structured documents — not verbal advice or slide decks that summarize what we said in meetings. You receive documents you can share with engineers, executives, and boards.

NDA before any technical discussion

We treat your data and business logic as confidential from the first call.

AI Strategy Document

Written strategy: use case prioritization, tech recommendations, build vs buy decisions, phased roadmap

Architecture Blueprint

Technical architecture with data flow diagrams, component selection, infrastructure spec, and integration patterns

AI Readiness Report

Scored gap analysis of data, infrastructure, team, and process readiness with prioritized action list

Vendor Comparison Matrix

Side-by-side vendor comparison with POC results on your data and a written recommendation rationale

Implementation Roadmap

Phased plan with milestones, dependencies, resource requirements, and success metrics for each phase

AI Governance Framework

Internal documentation covering model evaluation, audit logging, oversight requirements, and escalation procedures

How we work

From first call to actionable AI strategy

A structured consulting process with clear milestones. You know what we are doing, what we are producing, and when.

01Free

Discovery Call

We learn about your business, current technology, data situation, and the problems you are trying to solve. We tell you honestly whether AI is the right next step.

023–5 days

Fixed-Fee Proposal

Based on the discovery call, we produce a fixed-fee proposal with a defined scope, list of deliverables, timeline, and price. No hourly billing.

031–2 wks

Stakeholder Interviews

Structured sessions with your operations, product, data, and finance teams to map every AI opportunity and constraint. We go broad before we go deep.

041–3 wks

Analysis & Research

We evaluate your data, audit your infrastructure, test candidate tools and models against your use cases, and build the evidence base for our recommendations.

051 wk

Draft Review

We share draft deliverables for your review and input. You flag anything that does not reflect reality accurately. We revise before final delivery.

061–2 days

Final Delivery

Final documents with a walkthrough session. We explain the rationale behind every recommendation and answer questions from your team.

Pricing

AI consulting fees & timelines

All engagements are fixed-fee. No hourly billing, no scope creep surprises. Price is agreed before work begins.

Engagement typeWhat it coversTimelineIndicative fee

AI Readiness Audit

Assessment only

Data, infrastructure, team, and process readiness — gap analysis and prioritized action list2–3 weeks$5,000–$12,000

AI Strategy Engagement

Full strategy + roadmap

Use case discovery, architecture design, build vs buy, vendor selection, implementation roadmap4–8 weeks$15,000–$40,000

Advisory Retainer

Ongoing monthly support

Architecture reviews, vendor evaluation, team support, second opinions on implementation decisionsMonthlyFrom $3,000/mo

Organization size, number of use cases, and depth of technical analysis are the primary cost drivers.

Why CodeShiper

AI consulting from people who actually build AI

We are engineers who consult, not consultants who learned AI. That distinction matters for the quality of advice you get.

Engineers who build, not just advise

Our consultants have shipped production AI systems. We know what works in practice because we have built it and dealt with the failure modes ourselves.

Vendor-neutral by policy

We have no referral arrangements with any AI vendor, cloud provider, or tool company. Our recommendations reflect your requirements, not our revenue model.

Fixed fees, written proposals

Every engagement is fixed-fee with a written proposal before we start. You know exactly what you are buying, what we are delivering, and when.

Strategy that connects to implementation

We can implement what we recommend. If you want to move from strategy to development, the same team continues — no knowledge transfer to a separate build team.

Honest when AI is not the answer

Sometimes the problem is a process issue, a data quality problem, or a hiring decision — not an AI product. We tell you that rather than selling you work you do not need.

Documented rationale on every recommendation

Every recommendation comes with written rationale. You can challenge it, share it with your board, or give it to another team. We stand behind our reasoning.

Got questions?

Frequently asked questions

AI consulting — what it delivers, how long it takes, what it costs, and whether you need it.

What does an AI consulting engagement actually deliver?
A structured AI consulting engagement delivers a written AI strategy document that identifies high-value use cases for your business, ranks them by feasibility and ROI, and provides architecture recommendations, build-vs-buy analysis, vendor shortlists, data readiness assessment, and a phased implementation roadmap. You leave with a document you can act on, not a presentation you present to someone else.
How long does an AI consulting engagement take?
A focused AI readiness audit and use case discovery takes 2 to 4 weeks. A full AI strategy engagement covering architecture, vendor selection, data readiness, and roadmap planning takes 4 to 8 weeks. Ongoing advisory retainers run monthly. Timelines depend on the scope of your business, the number of use cases to evaluate, and the depth of technical documentation required.
How much does AI consulting cost?
An AI readiness audit typically costs between $5,000 and $15,000. A full AI strategy engagement with roadmap, architecture, and vendor selection costs $15,000 to $40,000. Ongoing advisory retainers start at $3,000 per month. You receive a fixed-fee proposal before work begins — no hourly billing surprises.
What is an AI readiness audit?
An AI readiness audit evaluates whether your organization is prepared to successfully deploy AI — across four dimensions: data quality and accessibility, infrastructure and tooling, team capability, and business process readiness. It identifies gaps that would prevent an AI project from succeeding and prioritizes what needs to be fixed before investment begins.
How do you identify AI use cases for my business?
We run structured discovery sessions with key stakeholders across your operations, product, and finance teams. We map every repetitive decision, manual classification task, document processing workflow, and prediction problem in your business. We then score each use case on data availability, technical feasibility, business impact, and implementation risk — and deliver a prioritized list with effort and value estimates.
What is build vs buy analysis for AI?
Build vs buy analysis evaluates whether you should build a custom AI system, integrate an off-the-shelf AI tool, or use a combination. We compare options on total cost of ownership, feature fit, data privacy implications, vendor lock-in risk, and timeline. The output is a written recommendation with the analysis behind it — not a default toward whichever option we profit from.
Can you help us select AI vendors or tools?
Yes. We evaluate AI platforms, model providers, vector database vendors, MLOps tools, and AI-native SaaS products against your specific requirements. We produce comparison matrices, run proof-of-concept evaluations on your data, and deliver a shortlist with a written recommendation. We are vendor-neutral — we do not have referral arrangements that bias our advice.
Can you continue as an advisor during implementation?
Yes. We offer ongoing advisory retainers where we review architecture decisions, evaluate vendor proposals, assess model performance reports, advise on prompt engineering and RAG tuning, and provide a second opinion on implementation decisions made by your internal team or another development partner.

Let's Talk

Thinking about AI but not sure where to start? Let's figure it out together.

A free 45-minute strategy call. We ask about your business, your data, and the problems you want to solve. We give you an honest read on where AI is worth investing and where it is not.

NDA available before any technical discussionResponse within 48 hoursNo pressure. No hard sell.