AI for
manufacturing.
We work in the information layer of a manufacturing business — planning, purchasing, inventory, documents, and decision support. We do not build or control production equipment, PLCs, robotics, or safety systems.
Production depends on information moving before the problem does.
Demand changes, material availability, supplier lead times, quality records, and maintenance history all live in different systems — and the cost of finding out late is measured in downtime and expedite fees.
Demand changes ripple slowly
By the time a material shortfall is visible on a schedule, the options have already narrowed.
ERP holds the answer, not the alert
The data is there. Someone still has to go looking for it at the right moment.
Documents are the institutional memory
Specs, SOPs, quality records, and maintenance history are only useful if they can be found.
Purchasing is a lead-time game
Supplier drift quietly changes what your planning assumptions are worth.
Exceptions consume the planners
The plan is fine; the day is spent on the things that deviated from it.
Reporting competes with running the plant
Management visibility is assembled by the same people who are needed on the floor.
The work worth
building around.
Not a menu to buy from. These are the places where connected systems most often remove work, improve a decision, or keep the operation moving.
- 01
Purchasing
Requirements, options, and draft orders prepared from demand, on-hand, and supplier lead time — approved by a planner.
- 02
Inventory & Material Availability
Coverage and shortfall risk evaluated against the current production plan and material requirements.
- 03
Production-Planning Support
Impact of demand or material changes surfaced early, with options laid out for the planner.
- 04
Vendor Communications
Status chasing, confirmations, and follow-ups prepared and tracked rather than remembered.
- 05
Quality Document Workflows
Non-conformance records, corrective actions, and documentation routed through defined paths with an audit trail.
- 06
Maintenance Knowledge
Work-order history, manuals, and prior fixes retrievable at the point the question is asked.
- 07
ERP Retrieval
Plain-language answers over ERP data instead of another custom report request.
- 08
SOP & Technical Documents
Procedures and specifications searchable across formats and locations.
- 09
Exception Management
Deviations detected, contextualized, and escalated to the right person with the history attached.
- 10
Order Status
Customer and internal status questions answered from live system data.
- 11
Forecasting & Capacity Visibility
Demand signals and capacity constraints reviewed together rather than in separate meetings.
- 12
Management Reporting
Operational and financial reporting assembled on a cadence, not on request.
- 13
Training
Onboarding and role material generated from documented procedures and real practice.
Demand shifts. The shortfall surfaces early.
Information moves ahead of the problem. The planner still decides what the plant does about it.
- 01Demand
Forecast or order book changes materially
Observed - 02AI Environment
Affected material requirements identified
Reasoned - 03ERP / Inventory
On-hand, on-order, and allocations checked
Reasoned - 04AI Environment
Shortage risk identified against supplier lead times
Reasoned - 05Purchasing
Sourcing options and draft orders prepared for review
Reasoned - 06AI Environment
Production impact surfaced with the affected schedule
Reasoned - 07Planner
Plan and purchase decision approved by a person
Human authority - 08Vendors & Sales
Communications prepared for suppliers and affected customers
Human authority - 09AI Environment
Decision and inputs written back and logged
Reasoned
One illustrative workflow, not a product. The architecture behind it — how systems, context, and approvals fit together.
What stays
with a person.
This work sits in planning, purchasing, documentation, and decision support. Production control, safety systems, and quality release stay where they belong — with qualified people and the systems certified for them.
- Production schedule changes and what the plant actually runs
- Safety decisions and anything touching machine control
- Quality release, disposition, and regulatory sign-off
- Purchase commitments and supplier terms
- Customer commitments on delivery dates and specification
How Big Timber works
We don't start with
a product.
We learn how the business works, then identify where connected AI creates useful capacity — and where it does not.
See the engagement model →Discover
We learn how the operation actually runs — systems, handoffs, and where work stalls.
Design
We map where connected AI creates capacity, and what stays with a person.
Build
Integrations, context, workflows, approvals, and logging built into your environment.
Train & Maintain
The team is brought with it, and the environment keeps an owner afterwards.
Find where AI fits in yours.
A working session across planning, purchasing, inventory, and documentation. We will be specific about where connected AI helps in the information layer — and where it has no business being.