Opportunity audit
Interviews with the people doing the work, a walk through the systems, and a ranked map of where AI and automation would remove real cost or unlock real revenue.
AI Consulting
Know exactly where AI helps
before you spend the budget
A short, focused engagement that turns the noise into a plan. We audit your operations and systems, find the places where AI and automation genuinely pay, size the effort and the cost, and hand you a roadmap you could execute with us or without us.
Opportunity AuditArchitectureRoadmapTeam Training
2 to 4
Weeks for a full audit and roadmap
Fixed
Fee agreed before we start
Yours
Roadmap, whoever ends up building it
Why It Matters
The expensive mistake is not picking the wrong model. It is picking the wrong problem.
Boards are asking what the AI strategy is. Vendors are promising everything. Somebody has run a pilot that impressed nobody. Meanwhile the genuinely valuable opportunities are usually unglamorous and sitting in plain sight inside operations.
We come in as engineers rather than as a slide factory. We look at how work actually moves through your company, where the hours and errors accumulate, what your data really looks like, and which systems can be integrated without a nine month project.
You get a ranked list of opportunities with effort, cost, risk, and expected return attached, a reference architecture, a build or buy recommendation for each, and a first project scoped tightly enough to start on Monday. If the honest answer for something is that AI is the wrong tool, we say so in writing.
How we keep it honest
- Findings grounded in your workflows and your data, not in industry benchmarks
- Every opportunity ranked by return, effort, and risk so the sequence is obvious
- Build, buy, and do nothing recommended honestly, case by case
- A roadmap written to be executed by any competent team, including your own
Capabilities
What the engagement covers
Scoped to your size and urgency, from a two week audit to an ongoing technical advisory relationship.
Data and readiness review
An honest look at what your data can support today, what needs cleaning or connecting first, and what that groundwork actually costs before anything clever is built.
Architecture and vendor strategy
A reference architecture for how AI fits your stack, plus model, platform, and vendor recommendations chosen on your constraints rather than on partnership deals.
Roadmap and business case
A phased plan with timelines, budgets, and expected return per phase, written so a finance director and an engineer can both use the same document.
Governance and risk
Practical policy on data handling, privacy, human oversight, acceptable use, and evaluation, sized for a real company instead of copied from a compliance template.
Team enablement
Workshops and hands on training so your developers and operators can build, run, and extend AI systems confidently instead of depending on an agency forever.
How We Work
From first conversation to production
No six month discovery phase. We move in short cycles and you see working software early.
01
Kickoff and goals
We agree what success means for this engagement, who we need to talk to, and which parts of the business are in scope. Usually one call and a short questionnaire.
02
Discovery interviews
Structured conversations with the people who do the work and the people who own the numbers, because the gap between those two views is where the opportunities hide.
03
Systems and data review
We look at your stack, integrations, and data quality directly, so recommendations are grounded in what can actually be built rather than what sounds good.
04
Analysis and roadmap
Opportunities scored on value, effort, and risk, then assembled into a phased plan with budgets, a reference architecture, and a clearly scoped first project.
05
Presentation and handover
A working session with your leadership and technical team, the full written report, and an open offer of advisory support while you execute.
Tools we build with
Process MappingData AuditsSolution ArchitectureOpenAIClaudeOpen Weight ModelsLangChainVector DatabasesAWSAzureGCPSecurity Review
Let's Talk
Get the honest technical read before you commit the budget
Tell us where your company is with AI right now, whether that is nowhere or halfway through a stalled project. We will scope an audit that answers the question properly.
We reply within 24 hours with a clear plan, a timeline, and a number.
Use Cases
When companies bring us in
Patterns we have shipped before, so we already know where the traps are.
The board wants an AI strategy
You need a credible, costed plan rather than a slide deck of buzzwords, and you need it to survive scrutiny from people who will fund it.
A pilot went nowhere
Something was built, it impressed in a demo, and it never reached production. We diagnose why and tell you whether to fix it, rebuild it, or drop it.
Choosing between vendors
Three suppliers are quoting wildly different numbers for the same brief. We give you an independent technical read so you can compare like with like.
Cost is climbing
AI features are live but the invoice keeps growing. We audit usage, architecture, and model choice and show you where the spend is actually going.
Before a large build
You are about to commit serious budget and want the architecture, the risks, and the sequencing checked by people who have shipped this before.
Upskilling an internal team
You would rather build the capability in house. We train your engineers, set the standards, and stay available while they take the wheel.
What You Get
Everything handed over, nothing held hostage
You finish the engagement owning the system, the code, and the knowledge to run it without us. That is the point.
- A written audit of your workflows, systems, and data readiness
- A ranked opportunity map with effort, cost, risk, and expected return
- A reference architecture and a build or buy recommendation per opportunity
- A phased roadmap with budgets and timelines your finance team can use
- A tightly scoped first project ready to start immediately
- A live presentation to leadership plus follow up advisory time
FAQ
AI Consulting, answered straight
The questions every serious buyer asks us before the first invoice.
What do we actually receive at the end?
A written report with the audit, a ranked opportunity map, a reference architecture, a phased roadmap with budgets, and a scoped first project. Plus a working session where we walk your team through all of it.
How long does an engagement take?
Two to four weeks for most companies. A single department can be done faster, and a group with several business units and messy systems takes longer. We agree the window before we start.
Do we have to build with you afterwards?
No. The roadmap is written so any competent team can execute it, including yours. Plenty of clients do hire us for the build, but that is a separate decision made after you have the plan.
Will you tell us if AI is not the answer?
Yes, and it happens. Sometimes the honest recommendation is better integrations, a cleaner process, or plain software. Saying so is the most valuable thing we can do for you.
How much does consulting cost?
A fixed fee agreed after a short scoping call, based on the size of the audit. It is a small fraction of the budget you are deciding how to spend, which is precisely the point.
Can you work with our existing technology partner?
Yes. We regularly work alongside internal teams and incumbent vendors, providing the independent technical view rather than trying to displace anyone.
Keep Exploring
The rest of what we do
Most projects touch more than one of these. We can take the whole thing or slot into the part you need.
Ready to Start?
Let's build the version of this
that actually ships
Tell us the problem in plain language. We will tell you whether it is worth building, what it takes, and what it costs, before you spend a rupee or a dollar.
We reply within 24 hours with a clear plan, a timeline, and a number.