A planner compares options
“Machine 2 is unavailable tomorrow. What schedules are feasible?”
Collects the limits, runs the planning tool, and compares the schedules that work and what each does to due dates.
AI Applications & Copilots
Ask better questions of your business data
Ask “why did downtime go up last week?” inside your own app and get the figures, a chart and a plain explanation. The numbers come from checked queries and planning tools, not from the AI; the AI helps people ask the question and understand the answer.
Priced for your project, in writing, before any work starts.
A production manager looks into a change
“Compare last week’s downtime by line and shift.”
What the assistant does
Runs the checked query, shows the comparison and lists the recorded reasons, without claiming that one caused the other.
What you get
Your definitions first
We write down what “sales”, “downtime” or “on time” mean for you, the date ranges and who may see what, before any AI is involved.
Numbers you can check
Every figure comes from a tested query or calculation, so anyone can check it.
Comparisons and charts
Compare by product, line, site or month, with the figures behind each answer.
What-if planning
Connected to a planning or optimisation tool, so people can compare schedules and options that work within your limits.
Shows its working
Each answer says where the data came from, how up to date it is and what it assumed.
Tested before people rely on it
We check its answers to real questions against results we know are right, and decide with you what it says when data is missing.
Analysis tools we can build
- An analyst inside your app
- Plain-English questions, comparisons and explanations on top of a checked model of your business data.
- Planning assistants
- Try scenarios around a scheduling or optimisation tool, with the limits and trade-offs shown.
- Front ends for engineering tools
- Guided inputs and side-by-side results around a calculation or simulation tool you already trust, checked by someone who knows the field.
Another example
Illustrative, not a client project. What it does, which data it uses and how we judge it are settled with you before we build.
How it works
Pick the questions or planning decisions that matter, and find the data you already have.
Write down the definitions, the calculations and a set of answers we know are right.
Build it and test it with the people who will use it, on their real questions.
Put it live with its limits written down, and keep checking the quality of its answers.
Questions people ask
Will AI make up the numbers?
No. The numbers come from tested queries, calculations or planning tools, not from the AI. When a question cannot be answered from your data, it says so.
Can it forecast demand or equipment problems?
Sometimes. Forecasting is a separate piece of work: it needs enough history, a simple forecast to compare against, and testing. Adding a chat window does not make a forecast.
Can it explain why a number changed?
It can compare what was recorded and show what changed alongside it. Finding the real cause may need more data or a person to investigate, and the answer says which it is.
Do we need a new dashboard first?
Not necessarily. We look at the data, reports and systems you already have and suggest the simplest first step.
Also in AI Applications & Copilots
- AI applications and copilotsContext-aware AI features, product assistants and approved app actions.
- AI for learning and trainingTutoring, targeted practice, answer feedback and voice roleplay.
- Technical copilots and AI workflowsTroubleshooting, field assistance, document understanding and AI actions.
Need ongoing care? Explore support and maintenance.
Tell us what you need
We reply within one working day, and you get a price in writing within 48 hours of our call. No obligation.