COO · Leads the reviewSergiiShmakov
The process
Runs the interviews, maps how the work actually happens, takes the baseline, and sets the success criteria and the roles.
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Lazy Ants · AI · Fixed-price review
Where to start with AI, and whether you should start at all.
The AI Readiness Review costs $4,500 and ends with a decision you can take to your board.
How most AI projects end
Not with a failure. With a pilot that worked and a production launch that never got scheduled.
- The demoConvinces everyone in the room
- The pilotRuns a quarter, on a slice of the work
- ProductionNever gets scheduled
Most AI projects do not fail on the model. They meet a process nobody owns, a success metric nobody agreed on, and approval rules that live in three people’s heads. This review looks at the process before it looks at the technology. Sometimes the answer is that no AI should touch it yet. We say that too.
- $4,500
- fixed price
- 3 weeks
- from day zero
- 3
- possible answers, including not yet
When this is worth doing
Stalled pilot
A pilot worked and never reached production, and nobody can say precisely why.
Too many candidates
Several processes look like candidates, and there is no agreed way to choose between them.
Mandate from above
Someone above you has asked for AI without saying where, and the answer has to be defensible.
Second opinion
A vendor has proposed something, and you want a read from someone who is not selling that build.
Undocumented
The process you have in mind is done differently by each team, and nobody has written it down.
If none of these describe your situation, this review is early.
Why AI projects stall before production
Almost everything that stops them is organisational. The technology is rarely the hard part.
A process with no owner
After launch, someone has to decide what happens when the system gets it wrong. If that person is not named before you start, they do not appear afterwards.
No baseline
If nobody measured what the process costs today, in hours, in errors, in delay, there is no way to show later that anything improved. Projects that cannot prove improvement get quietly defunded.
Approval rules that were never written down
A system can only be given permissions that exist as rules. “Check with Marina if it is a large order” is not a rule until someone says what large means.
One process that is really three
Two departments do the same job differently, and the version that gets automated turns out to be the one nobody actually uses.
Context the system cannot reach
The information it needs sits across three systems, and there is no read path into any of them.
None of these show up in a demo. All of them show up in month two.
This is what the report looks like
Two pages out of about twenty. Structure is what every review produces; the figures here are illustrative.
Every step measured, so the constraint is a number rather than an opinion. The step that costs most is usually the one nobody owns, and that is what decides the order of work.
What we recommend, what we rejected, and why. The rejected options matter as much as the chosen one: they are what you will be asked about internally.
What you get
Process map
The process as it actually runs, not the version in the documentation. Built from interviews with the people who do the work, including the workarounds they never mention in meetings.
Baseline
What the process costs you now, in hours, headcount, error rate and delay. This is what makes any later claim of improvement checkable.
The choice
The recommended first process, with the reasoning, and what was considered and rejected. The rejected options matter: they are what you will be asked about internally.
Success criteria
What “working” means, as numbers, agreed before anything is built, so the result is not a matter of opinion.
Roles
Who owns the process at launch, who answers when the system is wrong, and who decides to widen or roll back.
Boundaries
What data the system may read, what it may act on by itself, and where a person approves. Plus where your data may and may not go.
Plan
An implementation plan with a budget and timeline range for the first release.
The report is written to be forwarded. Your finance lead should be able to read it without you translating it first.
Three weeks, from day zero
Day zero is the day access is granted and one person on your side is named as the owner. It is not the day the invoice is signed.
What day zero requires
- One named person who can answer a question within a working day
- Interview slots with four to six people who actually run the process
- Read access to the systems carrying that process data
- Agreement on what may be shared with us and what may not
Access to people matters more here than access to systems. Most of what we need is not in a database. It is in the heads of the people doing the work, and it takes their calendars, which is why this review runs three weeks rather than two.
Two people run it
The process work and the technical boundaries are set on the same calls, so nothing gets recommended that cannot be built for sensible money.
COO · Leads the reviewSergiiShmakov
CTOAlexHarmatenko
The boundaries
Systems of record, access paths, permissions and data limits, and whether the chosen process can be built at a price worth paying.
Partner program
Partner Network
Lazy Ants is part of the Claude Partner Network, Anthropic's partner program for organizations helping businesses adopt Claude.
What it costs
$4,500, fixed. No hourly billing and no scope negotiation after the fact.
If you go ahead with the work we recommend
$4,500
credits in full toward that project, on any project from $15,000.
Not a percentage · No cap
The credit does not depend on what we recommend. We have no financial reason to point you at a larger build, which is the point of paying for the review rather than asking a vendor for a free opinion.
How it ends
Three endings, and we commit to all three.
Build this one
The process, the success criteria, the roles, the boundaries, and a scope with a range. That package works with any vendor. We would like it to be us, and it does not have to be.
Build a different one
Often the process a team arrives with is not the best first step. Another one is smaller, measurable sooner, and proves the case internally at lower risk.
Fix the process first
Sometimes the bottleneck is not something a model solves. Automating undefined work makes the mess faster. We say so, and you have saved a year of building the wrong thing.
You are buying a decision. What you do with it is yours.
Where the evidence comes from
Thin slice to productionOne operational workflow narrowed to a first production slice, with acceptance criteria and a verification step before anything reached the ERP. This is the shape of project the review leads into.Read the case
RAG in productionVector search and candidate filtering turning internal data into a stable planning workflow, with cost and latency held under real load.Read the caseObservability and incident responseOur own production system. What happens after launch, when live behaviour drifts: the signals worth watching, and who answers when quality moves.Read the caseAI summaries inside the ERPSummary generation turned into a live ERP workflow with saved state, freshness checks and admin controls. AI working inside an existing system of record, not beside it.Read the caseThese are delivery cases, not reviews. The review product is new and we will not pretend otherwise. What they show is that the recommendation comes from people who have taken this kind of work to production.
Book a 30-minute scoping call
We confirm the review fits your situation, agree what day zero needs from your side, and send the invoice. If it does not fit, we say so on the call and you have lost half an hour.
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