AI consulting services built around your business case
Our AI consulting services help U.S. businesses build a prioritized roadmap: which workflows to automate first, what each may cost, what it could save, and the assumptions behind its estimated payback.
AI consulting is a structured engagement in which specialists audit your workflows, data and systems, then recommend where artificial intelligence will produce measurable savings or revenue. A good engagement ends with a ranked roadmap that carries a cost estimate, a timeline and a payback period for every recommendation, not a list of tools to buy.
Most "AI strategy" is a slide deck, not a plan
Leadership teams are told to adopt AI without any clear picture of which processes actually justify the investment. The predictable result is scattered pilots, three overlapping subscriptions nobody uses, and no measurable return a year later.
The harder problem is that the loudest advice comes from people selling something. Platform vendors recommend their platform. Agencies recommend the build they are staffed for. Very few will tell you that two of your five ideas are not worth doing yet.
A roadmap ranked by savings, effort and risk
We map your current workflows and tech stack, then score every AI opportunity on three axes: annual cost or revenue impact, engineering effort, and implementation risk. The output is a ranked list, not a wish list.
Each recommendation arrives with an estimated build cost, a delivery timeline and an expected payback period, in a format you can hand to a CFO. If the math does not work, we put that in writing before you commit budget.
AI consulting services: scope and deliverables
Our AI consulting practice exists to answer one question honestly: where will artificial intelligence pay for itself in your business, and where will it just cost you money and attention?
We start with the work, not the technology. Consultants sit with the people doing the job, time the steps, and find where the hours actually go. Only then do we look at which of those steps a language model, a classifier, or plain deterministic automation can take over.
The engagement is deliberately vendor-neutral. We resell nothing and earn no platform commissions, so a recommendation to use a cheaper model, an open-source library, or no AI at all costs us nothing to make.
- A documented map of every high-cost workflow, with time and volume data attached
- An opportunity register scoring each candidate on savings, effort and risk
- Build-versus-buy analysis for every recommendation, with named alternatives
- Data readiness assessment covering quality, access, retention and residency
- A security and compliance review of the proposed data flows before you build
- A board-ready roadmap with sequencing, budget and payback per initiative
For organization-wide governance and investment planning, see our AI strategy consulting. For workflow-level discovery, these AI consulting services cover opportunity assessment and a practical roadmap. Read how to build an AI roadmap before the consultation.
Who AI consulting is right for
This service fits organizations that have decided AI matters but have not decided where to spend. It is most valuable before the first major build, when a wrong sequencing decision is still cheap to correct.
It is equally useful after a failed pilot. A surprising share of our engagements start with a company that bought a tool, watched adoption collapse, and needs an honest read on whether the idea or the execution was wrong.
- Companies with 20 to 5,000 staff carrying heavy manual back-office workload
- Leadership teams asked by a board or investors for an AI plan with real numbers
- Organizations that have run a pilot that stalled and want a diagnosis before spending again
- Operations leaders who know a process is expensive but cannot prove it in dollars
- Regulated businesses that need AI adoption reviewed against compliance obligations first
- Firms evaluating vendors who want an independent technical opinion before signing
Benefits of AI consulting services
Spend on the right thing first
Sequencing affects both risk and time to value. We compare estimated payback, dependencies and effort when choosing the first project.
A number your CFO will accept
Every recommendation carries a defensible cost and savings estimate, with the assumptions written down and open to challenge.
No vendor lock-in
We take no reseller margin. Model, platform and infrastructure recommendations are made on fit and cost per task alone.
Compliance risk surfaced early
Data residency, retention and access questions are answered in week one, not after your security team blocks the launch.
Internal alignment
The roadmap doubles as a communication tool. Operations, finance and IT see the same plan and the same trade-offs.
An exit from pilot purgatory
We identify why previous pilots stalled, usually integration or trust, rarely model quality, and design around that failure mode.
Business challenges this solves
Nobody can size the opportunity
Teams know a process is painful but cannot quantify it. We attach hours, volumes and fully loaded costs so the case argues itself.
Tool sprawl with no adoption
Three AI subscriptions, no measurable usage. We consolidate to what people actually use and cancel what they do not.
IT and operations disagree
Operations wants speed, IT wants control. The roadmap sets shared criteria so the argument is settled on evidence.
Data is not ready and nobody knows it
Data access can block an otherwise promising AI project. We assess access and quality before you fund a build.
The board wants a plan next month
A four-week engagement produces a defensible, presentation-ready roadmap with budgets attached.
Fear of picking the wrong model
We design for model portability so a better or cheaper model can be swapped in without a rebuild.
Features and deliverables
Everything below is in scope on a standard engagement. Nothing here is an upsell discovered halfway through the build.
Stakeholder interviews
Structured sessions with the people doing the work, their managers, and the systems owners, typically eight to fifteen interviews.
Workflow time-and-motion study
We measure how long each step actually takes and how often it runs, so savings estimates rest on observed data rather than guesses.
Systems and integration audit
An inventory of every system in the workflow, its API surface, its data quality, and what it would take to connect to it.
Data readiness assessment
Coverage, accuracy, labelling, access rights, retention rules and residency constraints for every dataset an initiative would need.
Opportunity scoring model
A transparent scoring sheet you keep, so you can re-rank later as costs change or new processes come into scope.
Build-vs-buy analysis
For each opportunity, named commercial alternatives with pricing, plus an honest assessment of when buying beats building.
Security and compliance review
Proposed data flows checked against HIPAA, SOC 2, GLBA, CCPA or your internal policy, with mitigations documented.
Board-ready roadmap document
The final deliverable: sequenced initiatives, budget per phase, payback per initiative, risks, and a recommended first project.
Technologies we use for AI consulting
We are not tied to one vendor. Model and infrastructure choices are made on accuracy, cost per task, latency, and where your data is allowed to live.
From AI consulting to implementation
The same five stages on every engagement, so you always know what happens next and what you get at the end of it.
Discovery
We interview the people doing the work, map the workflow end to end, and audit the systems and data behind it.
AI Strategy
Every opportunity gets scored on cost to build, time to value, and annual savings, then ranked.
Pilot Build
We ship the top-ranked automation as a fixed-scope pilot so you see real output before committing further budget.
Implementation
Integration with your live systems, staff training, human-in-the-loop review gates, and a documented rollback path.
Optimization
Monthly accuracy reviews, prompt and retrieval tuning, and a written report on hours and dollars saved.
How long it takes
A typical first engagement, week by week. Complex integrations and regulated environments extend this, and we say so during discovery rather than after.
Kickoff and interviews
We agree scope, then run stakeholder interviews and start the systems inventory.
Workflow mapping and data audit
Time-and-motion analysis on the priority processes, plus data quality and access testing.
Opportunity scoring
Every candidate scored on savings, effort and risk. Build-vs-buy analysis and security review completed.
Roadmap and readout
A working session with leadership to walk the ranked roadmap, challenge the assumptions, and agree the first project.
Optional pilot build
If you choose to proceed, the top-ranked initiative moves straight into a fixed-scope pilot with the same team.
Industries we deliver AI consulting for
Healthcare
Intake, prior authorization, clinical documentation, and revenue-cycle workflows built to respect HIPAA boundaries.
Financial Services
Document extraction, reconciliation, KYC support, and audit-ready reporting with full traceability.
Manufacturing
Quality inspection, maintenance prediction, supplier communication, and production scheduling.
Professional Services
Proposal drafting, timesheet capture, research synthesis, and client reporting at scale.
Retail & E-commerce
Product data enrichment, demand forecasting, support deflection, and personalized merchandising.
Legal
Contract review, discovery triage, and matter intake with citation-checked outputs and attorney sign-off gates.
Logistics & Supply Chain
Document processing, carrier communication, exception handling, and inventory rebalancing.
SaaS & Technology
AI features inside your product, support deflection, onboarding assistants, and usage analytics.
Real-world use cases
Pre-investment due diligence
A private equity firm asked us to assess AI readiness across four portfolio companies before allocating a shared technology budget.
Post-pilot rescue
A distributor had a stalled chatbot project. Discovery found the problem was inventory data freshness, not the model.
Back-office cost reduction
A services firm needed to cut administrative cost without headcount reduction. We found 31 weekly hours in three document workflows.
Competitive response
A regional insurer whose competitor launched instant quoting needed a realistic assessment of what matching it would take.
Regulated adoption planning
A healthcare group needed a plan that its compliance committee would approve before any patient data touched a model.
Board and investor reporting
A CEO needed a credible twelve-month AI plan with budget for a board meeting six weeks away.
Why choose DevSolutionsAI for AI consulting
Business case before build
Every recommendation carries an estimated cost, timeline, and annual savings figure. If the math does not work, we say so before you spend.
Vendor-neutral by design
We resell nothing and take no platform commissions. Model and infrastructure choices are made on fit, cost, and your data-residency rules.
Fixed-scope pilots
The first engagement is a defined deliverable at a defined price, not an open-ended retainer that quietly grows each quarter.
Built for handover
You own the code, the prompts, the infrastructure, and the documentation. No lock-in to a proprietary wrapper you cannot leave.
Human-in-the-loop where it counts
Anything customer-facing, clinical, financial, or legal gets a review gate, a confidence threshold, and a logged audit trail.
Security reviewed early
Data flow diagrams, retention rules, and access boundaries are agreed in week one, not retrofitted after your security team objects.
Find out what AI consulting would cost you, before you commit to anything
Every engagement is quoted after a short discovery, so you get a fixed written price built around your actual volumes rather than a rate card that assumes someone else’s business.
The first call is thirty minutes and free. Bring one workflow. We will tell you what it is likely costing you each year, roughly what automating it would take, and whether we think it is worth doing at all.
- A written savings estimate before any paid work
- Fixed scope and fixed price, agreed up front
- Full ownership of everything we build for you
- An honest recommendation when the numbers do not work
Figures are internal measurements across recent engagements, reported to every client monthly in writing.
Illustrative project scenario
Finding $410,000 of annual cost in three document workflows
Challenge. A national professional services firm was under pressure to cut administrative overhead without cutting client-facing staff. Leadership suspected AI could help but had no idea where to start, and a previous chatbot pilot had been quietly abandoned.
What we built. A four-week discovery covering fourteen interviews across three offices, a time-and-motion study on eleven recurring processes, and a data readiness audit. We scored nine AI opportunities and recommended three, explicitly advising against four others on cost or risk grounds.
Outcome. The top three initiatives carried a combined estimated saving of $410,000 annually against a build cost under $95,000. The firm proceeded with the highest-ranked project, an intake document extraction workflow, which went live eleven weeks later.
Illustrative project scenario. The figures demonstrate how a project could be scoped and evaluated; they are not verified client results or an audited average.
What clients say about working with us
AI Consulting FAQs
How much does AI consulting cost for a small business?
Most engagements start with a fixed-fee discovery phase between $4,500 and $15,000 depending on how many workflows are in scope and how many people we need to interview. That fee is fixed before we start, and nothing beyond it is billed without written agreement. Larger organizations with regulatory review requirements sit at the upper end of that range.
Do we need existing AI tools or data infrastructure before we start?
No. The majority of our clients begin with no AI infrastructure at all. Part of the engagement is assessing what you already have, systems, data quality, and access rights, and telling you what needs to exist before any build is realistic. Discovering that your data is not ready is a useful and money-saving outcome.
How long does an AI consulting engagement take?
A focused roadmap sprint takes two weeks. A full discovery covering multiple departments takes four weeks from kickoff to leadership readout. If you proceed to a build, the first automation typically reaches production six to ten weeks after that.
What do we actually receive at the end?
A written roadmap document containing the workflow maps, the scored opportunity register, build-versus-buy analysis, the data readiness findings, the security review, and a sequenced plan with budget and payback per initiative. You also keep the scoring model itself so you can re-rank opportunities later without us.
Will you recommend building something even if we do not need it?
We regularly recommend against building. On a typical engagement we advise proceeding with three of nine scored opportunities. We are not compensated on build volume during discovery, and the roadmap is a fixed-fee deliverable, so recommending unnecessary work earns us nothing.
Do you work with companies outside the United States?
Our practice is focused on U.S. businesses, and our compliance expertise is strongest with U.S. frameworks such as HIPAA, SOC 2, GLBA and state privacy laws. We do serve U.S. companies with international operations, and we can advise on GDPR implications, but a business with no U.S. presence is usually better served by a local firm.
Can you help us evaluate a proposal from another vendor?
Yes. Independent proposal and architecture review is one of the more common reasons companies engage us. We assess scope, pricing, technical approach and lock-in risk, and produce a written opinion with specific questions to put back to the vendor.
What happens if the roadmap concludes AI is not worth it for us?
That is a legitimate outcome and we deliver it plainly. In those cases the roadmap usually still identifies process or integration improvements worth making, because the workflow mapping exposes waste regardless of whether AI is the right fix. You keep the analysis either way.
Services that pair well with this one
Most clients combine two or three of these. We will tell you the right sequence during discovery.
Ready to scope your AI consulting project?
Book a free 30-minute consultation. Bring one workflow and leave with a realistic estimate of what it would cost to automate and what it would save.