Command Centre
One overview of material, stock, supplier and order signals.
Sanhima Innovations / Products / FactoryMind
In development · working nameAI for the people who make, move and supply.
From the shop floor to the boardroom, the same intelligence.
A developing AI-native manufacturing and supply-chain intelligence product, intended to help smaller and mid-sized manufacturers turn fragmented operational data into better-informed decisions.
The manufacturing problem
Six candidate problem areas.
These are candidate problem areas. We have not yet validated customer demand or willingness to pay, and we do not claim that every business faces all of them.
01
Raw-material availability
Uncertainty about whether the right materials will be there when production needs them.
02
Demand uncertainty
Forecasting is hard, and plans built on a poor forecast ripple through buying and production.
03
Stock and working capital
Excess inventory ties up cash, while stockouts stop production or miss orders.
04
Supplier delays
Late or disrupted supply that is noticed too late to act on calmly.
05
Disconnected records
Spreadsheets, stock records, purchase orders and invoice workflows that do not talk to each other.
06
Hidden ripple effects
Difficulty seeing how one operational issue can affect production, supply and business outcomes.
Why it is hard
Why fragmented data makes decisions harder
When purchase orders sit in one file, stock in another and supplier promises in someone’s memory, nobody sees the whole chain at once. A supplier delay can become a material shortage, a production re-plan, a late dispatch and a cash squeeze before anyone connects the dots.
- Supplier delay
- Material shortage
- Production plan
- Dispatch
- Cash and customers
Illustrative chain of effects. Not data from any business.
Intended workflow
How FactoryMind is intended to work
- Bring the data togetherUpload operational data from CSV or Excel files and check it for gaps and errors.
- See the pictureDemand outlook and material-shortage visibility in one place.
- Understand whyPlain-language explanations grounded in the business’s own data.
- Compare optionsInventory and ordering options, with their trade-offs.
- Decide, with people in the loopA person reviews and approves. Anything that commits money needs human approval.
Intended workflow. The first focus is files a business already has; no ERP connectors are claimed.
Capabilities
Capability modules
Concept modules explored so far. All are planned; none is claimed as built. The phase shows where each is intended to sit in a proposed sequence.
Demand Sensing
Compare forecasting approaches for each item and show why one was chosen.
Supplier Risk
A view of supplier reliability built from delivery performance and other signals.
Inventory Optimizer
Suggested stock levels based on demand and lead times.
Digital Twin
A connected map of how materials, suppliers and production relate.
Stress Test Simulator
Explore “what if” scenarios, such as a late supplier or a disrupted route.
AI Copilot
Ask questions in plain language and get answers grounded in the business’s own data.
Planned concept: not built. Early phase and later phase are proposals and may change.
Example
An example decision journey
Illustrative sample text, not a real customer, real data or live output.
Spot
A purchase order file shows a key raw material now has a longer lead time than the plan assumes.
The data check flags the change; a person is told what changed and where.
Understand
The material feeds three planned production runs next month; stock cover looks short for the third.
An explanation is shown in plain language, with the rows it came from.
Explore options
Order earlier, ask for a partial delivery, or move one production run.
Each option shows its trade-off, for example extra carrying cost against the risk of a stoppage.
Decide
The buyer and plant head choose one option.
A person confirms. Nothing is sent or ordered automatically.
Roadmap
A proposed roadmap
Proposed sequence only. It may change after conversations with businesses. Nothing below is live.
- Phase 1 · proposedUpload and validate CSV/Excel operational data.
- Phase 2 · proposedDemand forecasting and material-shortage visibility.
- Phase 3 · proposedInventory optimisation and decision support.
- Phase 4 · proposedAI-assisted explanations grounded in the available business data.
- Phase 5 · proposedSupplier-risk, scenario simulation and digital-twin capabilities as the product matures.
Intended value
What it is intended to help with
We have measured no results yet, so we publish no figures and promise no outcomes.
Earlier visibility
Seeing likely shortages and supplier problems sooner.
Calmer planning
Fewer surprises when demand or supply changes.
Better use of cash
Less money tied up in stock that is not needed.
Less manual stitching
Less time spent reconciling spreadsheets by hand.
Shared understanding
Buying, stores, production and accounts looking at the same picture.
Trust
Responsible, human-supervised decisions
People decide
The product prepares and explains. A person approves any action that commits money.
Grounded explanations
Answers should point back to the business’s own data, not to guesses.
Honest about gaps
Missing or doubtful data should be flagged, not quietly filled in.
Traceable
The aim is a record of what was suggested, what was decided and by whom.
No autonomous actions
No continuously running agents, live ERP write-backs or real-time monitoring are claimed.
Interested in shaping FactoryMind?
If you run a manufacturing or supply-chain business and would like to shape this product, tell us. Expressing interest is a conversation, not a commitment.