Ninety-five out of every hundred enterprise AI pilots never move the bottom line. That is not pessimism. MIT's 2025 study of generative AI in the enterprise found that roughly 95% of GenAI pilots show no measurable impact on the bottom line. The technology itself is fine. What breaks is everything around it: choosing a use case that matters, getting data into shape, shipping to production, and keeping the system alive after the consultants pack up.
Closing that gap is the entire job of AI consulting services. Most of them never get there. They sell strategy decks. We sell systems that run.
AI consulting services help organizations identify high-value AI use cases, build the systems that deliver them, and operate those systems in production. The best engagements span strategy, build, and run, so the work reaches measurable results instead of stopping at a recommendation.
This page is written for one kind of reader: a leader who already believes AI matters but is stuck between ambition and execution. Maybe a pilot stalled. Maybe an off-the-shelf tool came in flat. Maybe the board wants "something with AI" and there's nobody in-house to scope it. If that sounds like your week, here is what an engagement with us delivers, how fast, and at what price.
Get an AI Readiness Snapshot — a free 30-minute call to map where AI pays back fastest for you.
What you get
You walk away with concrete artifacts, useful whether or not you keep working with us:
- A prioritized use-case roadmap ranking opportunities by value and feasibility, so the first project is the one most likely to pay back.
- A data and AI-readiness assessment covering data quality, access, security posture, and the gaps that sink pilots before they start.
- A working pilot or proof of concept that runs on your real data, not a sanitized demo.
- Production deployment with MLOps so the system survives contact with real users and real load.
- Governance and responsible-AI guardrails built in from the start, not bolted on after an incident.
- Enablement and handover so your team can run and extend what we build.
Best for mid-market teams scaling their first one to five AI use cases who want a partner that builds and operates, not just advises. Not for pure staff augmentation, one-off prompt tweaks, or anyone who only wants a strategy document.
Services and capabilities
The work splits into three groups. Most engagements run through all three, though you can start wherever your situation pushes you.
Strategy
We open with use-case discovery. Where does AI actually move a number you care about? From there we build an AI roadmap that sequences projects by value and readiness, and we model the ROI of each one so the business case is honest before anyone writes a line of code. This is the step that separates what pays back from what only sounds good in a meeting.
Build
Our engineers handle the whole build: machine learning, large language model, and agentic AI development, plus the data engineering and integration work that makes a model useful inside the stack you already run. A model sitting in a notebook proves nothing. We build the pipelines, interfaces, and integrations that turn a promising result into something your team actually opens on Monday morning.
Operate
Shipping is the start, not the finish. We run deployment, monitoring, and MLOps so performance doesn't quietly rot, alongside governance, security, and steady optimization. For teams with no AI talent in-house, our Fractional Agentic Team embeds strategy, build, and operate capacity straight into your organization without permanent hires.
How it works
Four phases carry you from a first conversation to a system in production. Each phase has a clear input and a clear output, so you always know what you are paying for.
- Snapshot — a free 30-minute call to assess fit and surface the highest-value opportunities. Output: a shortlist of candidate use cases and an honest read on readiness.
- Discovery — a roughly one-week sprint that turns the shortlist into a value-ranked roadmap, a data-readiness assessment, and a scoped first build. Output: a plan you could hand to any team.
- Build — we develop the prioritized use case against your real data and integrate it into your stack. Output: a working pilot, typically in a few weeks.
- Operate — we deploy, monitor, govern, and optimize, then enable your team to run it. Output: a production system with handover.
The order is not decoration. Skip the readiness check and you join the 95%. That failure pattern is what the next section maps.
How we avoid the 95% failure trap
The MIT 2025 finding that most GenAI pilots produce no P&L impact isn't a reason to wait. Read it as a map of the failure modes instead. Each one has a safeguard.
| Failure mode | Our safeguard |
|---|---|
| No clear use case | A value-ranked roadmap delivered in week one, not a vague "AI strategy" |
| Pilot never reaches production | We build and operate, so the work doesn't die at the demo |
| No in-house skills to sustain it | An embedded fractional team plus enablement and handover |
| Data isn't ready | A readiness assessment up front that fixes the gaps before the build |
| Governance added too late | Responsible-AI guardrails designed in from phase one |
The thing separating the 5% that work from the 95% that don't is rarely the model. It is whether someone owned the path from idea to production. We own that path.
Typical project timeline
These are ranges, not guarantees. Your data and goals shape the real numbers.
- Snapshot: free, 30 minutes.
- Discovery sprint: about one week.
- First working pilot: usually a few weeks after discovery, depending on data readiness and integration complexity.
- Operate: ongoing, set up so your team can take the wheel whenever you are ready.
Speed comes from a tight first scope, never from cutting corners on data or governance.
Pricing
We are open about the model before any detailed quote:
- AI Readiness Snapshot: free, 30 minutes.
- AI Transformation Discovery : $5,000 for a one-week sprint that produces your roadmap, readiness assessment, and scoped first build.
- Fractional Agentic Team: from $8,000 per month for embedded strategy, build, and operate capacity.
Most engagements open with the Snapshot or the Discovery sprint. Both are low-risk ways to learn whether the value is real before you commit to a larger build.
Start with the lowest-risk step
The most expensive mistake in AI is burning a quarter and a budget only to confirm a use case was never going to pay back. A short, structured first step heads that off.
AI Readiness Snapshot — a free 30-minute call that maps where AI delivers the fastest return for your business, with no commitment and no deck.
Ready to move faster? Book an AI Transformation Discovery sprint and have a value-ranked roadmap in about a week.
