Explore business-wide programmes and department systems across logistics, engineering, procurement and operations. Every case is anonymised; client names are shared on request.
These programmes connect teams, data and approvals across a complete operating flow, while keeping people responsible for important decisions.
Transport operations
Container logistics · Laem Chabang
Delivery instructions, scheduling, driver hand-offs, proof of delivery, returns and billing were split across messages and files. A TMS and AI agent team are being built to coordinate one end-to-end job flow, with people reviewing approvals and exceptions.
Procurement operations
Steel & construction-materials retail
Low-stock items had to be traced to previous suppliers and purchase prices before an order could be prepared. The system identifies replenishment needs, drafts purchase orders by supplier for user confirmation, and is being prepared to pass confirmed records to their accounting software.
AI adoption programme
Automotive packaging & in-plant logistics
Eight departments need practical AI adoption without replacing the warehouse system they already use. The programme is being set up through training, workflow design and department assistants that will use approved data and accept requests by chat or email.
Each case focuses on one function, its hand-offs and the human review point that keeps the work accountable.
Dispatch
Container logistics · Laem Chabang
A delivery instruction has to become a job order, vehicle plan, driver brief and progress record without losing details between hand-offs. The dispatch workflow is being built around one job record, with approvals and operational exceptions routed to the team.
Proof of delivery & billing
Container logistics · Laem Chabang
Driver photos and completion details need to remain attached to the correct transport job before finance can act. The workflow is being built to collect the evidence, check completeness and queue verified job records for billing review.
Stock replenishment
Steel & construction-materials retail
When a stock tag signals replenishment, the system looks up the last supplier and purchase price, groups items by supplier and prepares draft orders. A user confirms each order before it moves to their accounting software.
Supplier documents
Steel & construction-materials retail
Quotes and supporting files arrive in formats that still require a person to read and compare them. An OCR-assisted intake is being built to extract line items for review, flag unusable files and send workflow notifications through LINE.
Packaging engineering
Automotive packaging & in-plant logistics
Packing standards and past design decisions can be difficult to retrieve when a new request reaches engineering. An assistant is being designed to search approved specifications and help prepare engineering documents, with an engineer retaining final review.
Planning
Automotive packaging & in-plant logistics
Forecasts arrive in different file formats and change while people, materials and returnable packaging still have to be planned. An assistant is being designed to normalise incoming files, compare plan against available inputs and prepare a daily planning summary.
Operations reporting
Automotive packaging & in-plant logistics
Shift forms and daily reports can move through photos, spreadsheets and repeated data entry before management sees them. A workflow is being designed to read standardised forms, validate key fields and prepare summaries from approved operational data.
Accounting documents
Automotive packaging & in-plant logistics
Invoices, billing documents and tax records need to be matched while missing items are followed up across teams. An assistant is being designed to classify documents, flag gaps and draft follow-ups, while people remain responsible for posting and submission.
Human resources
Automotive packaging & in-plant logistics
Attendance, overtime and employee documents create recurring checks across HR, operations and accounting. An assistant is being designed to classify records, reconcile approved sources and prepare exception lists, without making employment decisions.
Show us the repetitive task. We will map the workflow, find the practical AI opportunity, and tell you what is worth building.