AI Implementation
Two Years of SAP. Two Months Here.
ERP implementation is a consulting business wearing a software costume. We replaced the consultants with AI — it reads your data and documents, builds the configuration, migrates your records and runs the rollout. Live in about 8 weeks.
Why ERP projects are the reason people stay on spreadsheets
The software was never the expensive part
Implementation costs more than the licence
Six-figure implementation fees against a five-figure subscription is normal in this industry. You are buying consulting hours and receiving software as a side effect.
Twelve to twenty-four months of nothing improving
A long project means the problems that made you buy are still there a year later, while the requirements you gathered at the start have quietly gone stale.
Consultants learn your business on your budget
Months of workshops transfer your process knowledge into someone else's head. Then the engagement ends and it walks out of the building with them.
What the AI actually does
Four specific jobs that used to be billed by the hour.
It configures the system
Instead of workshops that turn your processes into slides and then into someone's task list, the AI reads what you already have — exports, spreadsheets, standard operating procedures, part drawings, your chart of accounts — and builds the real configuration. Items, bills of materials, routings, custom fields, workflows and approval rules land in a working system you can log into and argue with.
- •Reads your existing data and documents
- •Builds items, BOMs, routings and workflows
- •You review a working system, not a specification
An AI project manager runs the rollout
The rollout backlog has an owner that does not bill hourly. It tracks every open item, implements the changes, verifies them in a real browser against the real system, and reports what moved and what is blocked. When your production manager asks for a different approval path on Tuesday, that is a task, not a change order.
- •Owns the backlog end to end
- •Verifies its own work in a real browser
- •Changes are tasks, not change orders
It migrates your data
Legacy exports and years of spreadsheets get mapped, cleaned and validated by the AI rather than by a separately quoted migration project. Duplicates, broken references, inconsistent units and missing required values surface as a reviewable list before anything is loaded — so the first day on the new system is not spent discovering that the item master came across wrong.
- •Field mapping from legacy exports
- •Cleanup and validation before load
- •Not a separately quoted project
And it stays after go-live
The AI does not pack up when you switch over. The same project manager keeps taking change requests — a new approval path, another custom field, a report nobody thought of during implementation — and implements them without a support ticket becoming a quote. Meanwhile the forecasting keeps scoring itself against what actually sold, and anyone can ask the system a question in plain English rather than hunting for the right report.
- •Change requests stay tasks, not quotes
- •Forecasts graded against real demand
- •Ask questions in plain language
Where the time goes
The same phases every ERP project has. The difference is who does the work.
| ianaiERP | Legacy ERP project | |
|---|---|---|
| Discovery & requirements | Days — the AI reads your existing data and documents | 2–4 months of workshops |
| Configuration | AI-generated, then reviewed with your team | 3–6 months of consultant build |
| Data migration | AI-mapped, cleaned and validated | Separately quoted project |
| Customization | Configuration your team owns | Change orders and developer time |
| Testing & training | Parallel run against your live system | Compressed at the end when budget is gone |
| Go-live | About 8 weeks | 12–24 months in |
Typical mid-market scope. Regulated deployments requiring installation and operational qualification documentation run 8–12 weeks.
How we keep it from going wrong
Parallel run, not a big bang
The new system operates alongside your existing one until you decide to switch. Nobody bets the quarter on a single cutover weekend, and there is always a way back.
One line or product family first
We deliberately avoid big-bang implementations, because they fail. Go live on a narrow, real scope, prove it against your own numbers, then widen.
Your team keeps the knowledge
Because configuration is something your people do rather than something done to them, the understanding of how your system works stays with the company.
How long would yours take?
Tell us what you run today and we will scope the 8 weeks against your actual business — not a generic template.
Questions worth asking
A mid-market scope on a single legal entity, with your data available for export and someone on your side who can make decisions. Multiple entities, heavy integration work, or validated environments take longer — regulated deployments needing installation and operational qualification documentation typically run 8–12 weeks. We would rather tell you 12 weeks up front than discover it in month four.
Exports of your current data, whatever process documentation exists even if it is out of date, and a decision-maker who can spend a few hours a week reviewing what the AI has built. What we do not need is months of your team's time in requirement workshops.
It will get things wrong — every configuration does. The difference is the correction loop: the AI project manager implements the fix and verifies it in a real browser, usually the same day, and there is no change order because nobody is billing hours.
No. Templates are why implementations fail slowly — you spend a year discovering the ways your business is not the template. The configuration is generated from your own data and processes, and the customization tools stay in your hands afterwards.
You own the configuration. Custom fields, scripts, workflows, page building and product option templates are all in the product, so ordinary changes do not require us at all. That is a deliberate choice: permanent partner dependency is the thing we are trying to eliminate.
Ask us how long it would take
Bring your current system and your data. We will walk you through what the first 8 weeks would actually look like.