Sector · Logistics
AI for logistics and warehousing
Capacity, receiving, stocktakes, client questions and shipping, using the information your warehouse already has and in each client’s language.
Does this happen in your company?
- “Can we take this load?”The answer depends on space, equipment and shifts, and takes hours to confirm.
- Receiving and counts done by hand?Notes are written in the warehouse and typed up at the end of the shift.
- Is the client asking about stock?And someone has to go and find the answer before replying to the email.
- The truck arrives and a document is missing?Documents and holds are only checked right before the collection.
- “Have we had this case before?”Claims, reports and old emails are scattered and nobody can find them.
- Is the client abroad?Reports and replies need to reach them in their language.
Where FairAI fits in, from order to delivery
- 1 · Plan
“Can we take it?” Answered in minutes
- Today
- When an urgent request comes in, someone goes through spreadsheets and asks several people whether there is capacity. The answer takes time and the impact on other deliveries goes unseen.
- With FairAI
- FairAI simulates the request against the real load and shows options with dates and costs. The planner chooses.
- Faster, firmer answers to clients
- Clashes spotted before they happen
- Impact on other orders shown up front
Builds on our workthe planning assistant that simulates new orders against capacity and cost.
See the example working - 2 · Receiving
Speak it, snap it, and the report is ready
- Today
- In the warehouse, counts and receiving notes are written by hand or typed up at the end of the shift. For foreign clients, they still need translating.
- With FairAI
- Staff speak and photograph the pallets. FairAI reads the labels, counts the units and fills in the report in the client’s language. Anything unclear is flagged.
- Units counted and labels read from the photo
- Spoken in any language, reported in the client’s
- Report ready by the end of the shift
Builds on our workthe service app in use at F. Caixeiro, which turns voice and photos into reports. Read the case study F. Caixeiro
See the example working - 3 · Stocktake
Stocktakes without counting pallet by pallet
- Today
- Stocktakes are counted by hand, area by area. Differences from the system only show up weeks later, when goods are missing from a shipment.
- With FairAI
- Photograph the area with a phone. FairAI counts the pallets, compares them with what the system says and shows the difference. The person in charge decides: recount or adjust the stock.
- Counts in minutes, not shifts
- Differences seen the same day
- Every count is kept with its photo
Builds on our workthe photo reading in F. Caixeiro’s app and image search already tested in a proof of concept. Read the case study F. Caixeiro
See the example working - 4 · Stock and clients
Clients ask, the portal answers
- Today
- Clients email or call to find out how much stock they have, what is reserved or when an order ships. Every question takes someone in customer service.
- With FairAI
- In your portal, an assistant answers each client from their own data. Each client sees only what is theirs.
- Instant answers on stock and shipments
- Fewer routine customer-service emails
- The data can stay on your servers
Builds on our workthe search and assistants that answer from a company’s own data and documents.
See the example working - 5 · Outbound
Everything checked before the truck arrives
- Today
- Only with the truck at the gate does someone find a missing document, a hold or a stock shortfall. The loading slot and the trip are lost.
- With FairAI
- Before each collection, FairAI checks instructions, documents and stock and lists what is ready, missing or blocked. The client follow-up comes out ready to review and send.
- Fewer lost slots and wasted trips
- Holds visible early
- Follow-ups drafted in each client’s language
Builds on our workthe spreadsheet and photo reading we already use in search and field reports.
See the example working - 6 · Claims
“Have we done this before?” Answered in seconds
- Today
- The answer exists, but it is scattered: a quote in a spreadsheet, a drawing in a folder, a decision in an email from two years ago. Only one or two people remember.
- With FairAI
- Ask in everyday words. FairAI searches spreadsheets, PDFs, emails and images and shows every result with its source.
- Past jobs found by anyone with access
- Less reliance on whoever remembers
- Photos found by what they show, even without tags
Builds on our workthe search across years of orders, documents and images we built for a ceramics manufacturer.
See the example working
Not sure where to start? Take the 2-minute assessment