AI · AX
AI & AX
We graft AI onto the workflow you already run, with acceptance criteria and exception handling fixed in writing at kickoff.
Overview
What we deliver, and how
AI projects tend to fail in the same place. The demo goes well, and then nobody in the business uses it. At that point the person who approved the budget has to explain themselves.
So we do not open with the model. We start by watching who does the work today, over how many hours, in what order. If there is nothing worth automating, we say so. Making something look workable when it is not leaves your team holding it.
We pick the single task with the clearest payoff and attach AI to it within four to six weeks. Once the hours saved show up as a number, we widen to the task next door.
We do not promise an accuracy figure up front. Instead we agree, in writing, what counts as passing for which inputs and who picks it up when it is wrong. Acceptance runs against that document. Without it you spend the project arguing about the gap between "seems to work" and "usable".
The problem
Where projects usually start
These situations recur in outsourced development. If any apply, we recommend talking to us before kickoff.
Check whether any of these apply to the project you are preparing.
- 01
The document exists but nobody can find it
Rules and manuals are scattered across teams, so every handover starts the search over again.
- 02
Work that is just retyping
Reading quotes, reports and slips by eye and re-entering them elsewhere eats a working day.
- 03
Adopted, then quietly abandoned
A tool that sits outside the existing workflow gets used for a few weeks, then everyone goes back.
How it works
Measure the work → Pilot one task → Run on confidence thresholds
Today
Rules and manuals scattered by department
A staff change means hunting for them all over again
Read by eye, then typed again
A day goes into copying quotes and slips across
Tools that sit outside the work
Used for a few weeks, then everyone goes back
02What we deliver
Start by watching the work
Measure which step takes how many hours
Pilot on a single task
Attached within four to six weeks, verified in numbers
Evaluation criteria in writing
Pass thresholds and exception handling agreed at kickoff
03After delivery
Answers arrive with their sources
Nothing outside your own documents gets answered
Branch on a confidence threshold
Low-confidence cases route to a person automatically
Inside your ERP and groupware
No new habits to build
- RAG
- On-premise option
- Retraining procedure handed over
Built to be used for real, not demoed once
Our approach
How GENIESOFT responds
One response to each of the three situations above.
- Before
- Scattered documents
- After
- knowledge that answers questions
Answers are grounded in your own documents and shown with their sources, scoped so nothing is invented.
- Before
- Manual re-entry
- After
- a review step
Fields are extracted and pushed into your existing system for a human to confirm, with low-confidence cases flagged.
- Before
- A separate tool
- After
- the screen they already use
It goes inside the systems already in use — ERP, groupware — so no new habit is required.
Project flow
How a project runs
The actual sequence a project moves through, step by step.
- 01
Observe the work
We count where the hours actually go today. Model choice comes after that.
- 02
Pilot
We attach AI to the single highest-payoff task within four to six weeks. Low-confidence cases route to a person.
- 03
Verify, then scale
We confirm the time saved in numbers, then widen to the adjacent task. Never company-wide from day one.
Typical projects
Where this applies
The kinds of projects we are most often asked to take on in this field.
01
Manufacturing and inspection
Replacing visual defect classification and counting with cameras and models. We first confirm whether it can be attached without stopping the line, and how it ties into existing equipment.
- Before
- Every unit inspected by eye
- After
- Camera screens first, people handle edge cases
02
Administrative document review
Extracting values from submitted documents and checking them against rules. Ambiguous cases route to a person, so automation never quietly shifts accountability.
- Before
- Fields retyped one page at a time
- After
- Values extracted automatically, only unclear cases reviewed
03
Support and internal knowledge search
Answering questions across scattered policies and manuals. Retrieval quality depends more on document hygiene than on the model, so we assess volume and format first.
- Before
- Ask whoever knows the policy
- After
- Ask a question, get the source document with it
Work
What we built here
Projects GENIESOFT has delivered in this field.
FAQ
Common questions
Questions we often receive while clients are evaluating a project.
We do not have much data — is that workable?
It depends. Some tasks work with little data on top of a pretrained model; a niche domain needs data collection first. We tell you which case you are in during review.
What accuracy can we expect?
We do not promise a number up front. Instead we agree what counts as passing for which inputs, and what happens when it is wrong. Acceptance runs against that.
Does using an external API send our data out?
Yes. For sensitive data we evaluate self-hosted models instead. Performance, cost, and whether data may leave your network are decided before kickoff.
Principles
What is different
Problems clients commonly hit with outsourced development, and what we do about each.
| Common problem | Our approach | What changes |
|---|---|---|
| "Done" means different things to each side, and it surfaces at handover | Deliverables and acceptance criteria are agreed in writing before kickoff | Nothing left to argue about at acceptance |
| Progress is reported on paper; the real thing appears only at the end | We show working software every two weeks | A wrong turn is caught within two weeks |
| Once delivery is done, the vendor goes quiet | Deployment procedures and incident runbooks are handed over with the code | Operation continues even when staff change |
| Cross-domain work needs multiple vendors, and blame moves between them | XR, AI, web and app, and games sit in one organization | One contract, one party accountable |
Responsibilities
Who does what
What we do at each stage, and what you confirm. Most delays come from late confirmation, so we make both sides explicit before kickoff.
| Stage | GENIESOFT | Client | Deliverable |
|---|---|---|---|
| 01Scoping | Requirements analysis, feasibility review, scope and schedule estimation | Confirm priorities, share budget range | Proposal and quote |
| 02Design | Screen design, data modelling, prototypes for risky areas | Review and approve the design | Design document and prototype |
| 03Build | Two-week iterations, demo every other week, progress updates | Feedback on demos, hand over content and source material | Working build and source code |
| 04Acceptance | Acceptance testing support, defect fixes, staff training | Verify against acceptance criteria and sign off | Acceptance record and operations manual |
| 05Operate | Warranty support, incident response, maintenance | Assign an operations contact | Deployment procedures and incident runbooks |
Contact
Start your project
Requirements still taking shape? That's fine. An engineer reviews your inquiry and replies within two business days.
- No brief needed
- Scope and timeline reviewed first
- Reply within two business days
