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AI takes over the routine of logistics and warehouse teams — decisions stay with people

AI for a logistics company: what already runs in ours

We are a logistics company ourselves, and AI runs in our daily work, not in a slide deck: a request e-mail becomes a commercial quote, inbound requests are sorted and get a draft reply, and discrepancies in registers are found by the machine. The rule is the same everywhere: AI proposes, a person checks and confirms. We deploy these same products for you.

Discuss your case What is included
01Who it is for
  • Logistics and forwarding companies that price quotes by hand
  • Warehouses and 3PL operators with a stream of requests, documents and registers
  • Managers who want AI in daily work, not a pilot for the sake of a pilot
02What it replaces
  • Pricing quotes in a spreadsheet and from memory
  • Sorting e-mail and requests by hand
  • Spot-checking registers and carrier documents
AI for logistics and warehousing
03What is included

What is included

Automated quoting

Quotes in minutes, not days
in production

AI parses the incoming request, the calculation runs on current cost and tariffs, and a finished quote comes out. A human checks it and sends it.

The job

Cut the path from a client request to a number in the offer from days to minutes.

What hurt

  • Producing a quote takes days and depends on one person's workload
  • Different managers price the same thing differently

What you get

  • One pricing method, identical for everyone
  • The client gets an answer the same day

What your client gets

  • The offer arrives fast, with a transparent price structure
last change: 20 Aug 2026

AI in client service

Request sorting and draft replies
in production

AI parses inbound mail and requests, classifies them and drafts answers from the knowledge base. The employee receives each request with the context and a draft reply ready.

last change: 16 Sep 2026

Register reconciliation

A machine finds the discrepancies
in production

Reconciliation of registers and settlements across systems: discrepancies are found automatically and land in a work list with the reason attached.

last change: 21 Sep 2026

Smart Yard

Self-service at the warehouse gate
in production

The driver self-registers, the system puts them in a fair queue, assigns a gate and guides them with notifications. No dispatcher at the barrier.

The job

Remove the queue and the manual assignment of trucks at the gate.

What hurt

  • Queues and gridlock at the entrance; trucks wait blind
  • A dispatcher assigns trucks to gates by hand

What you get

  • A fair queue and automatic gate assignment
  • Waiting time is measured, not eyeballed

What your client gets

  • A truck enters on schedule; idle time stops being the norm
last change: 16 Sep 2026

Inbound document verification

Matching carrier documents to what happened
pilot

Collects unposted carrier documents, matches them against operational facts and tariffs and assigns a traffic light with an explanation. Posting stays with a human.

last change: 14 Sep 2026

Freight cost verification

Double payments and wrong tariffs
pilot

Automated checking of actual-cost documents: the carrier tariff on the trip date, the amount formula, mileage, duplicate requests and double payments. The result is a traffic light with an explanation; the decision stays with a person.

The job

Find carrier overpayments before payment, not during the annual reconciliation.

What hurt

  • Tariff-versus-amount mismatches are spotted selectively and late
  • Duplicate requests and double payments get lost in the volume

What you get

  • Every document is checked, not a sample
  • The check explains the reason instead of just flagging

What your client gets

  • Settlements with carriers stay clean and predictable
last change: 14 Sep 2026
04How it works for you

How it works for you

Pick one process

The one with the most manual routine and a clear way to measure the result: quotes, requests, reconciliation.

Connect to your systems

E-mail, 1C, CRM — through a gateway and a set of permitted operations, with no direct database access.

AI proposes, a person confirms

AI prepares the draft, the price or the list of discrepancies; an employee makes the decision. Every action is logged.

Compare and expand

We compare time and errors before and after, then take the next process.

05Comparison

Three ways to solve this

We are not the only option, and we show plainly where we lose.

Build it yourselfOff-the-shelf vendorBIOCARD Tech
Time to first resultQuarters: hiring, learning the domain, architecture from scratchWeeks to install — then months bending processes to fit the boxA demo immediately, a pilot in weeks: the product already exists
Domain contextYou will have to teach the team what a batch and a temperature mode areA generic product with no notion of a shipment or a cold chainWe work in it daily — the context is included
Who carries the riskYou do: for the timeline and for the solution turning out wrongYou do: changes outside the vendor roadmap usually never happenWe do: the product runs in our own company and we use it ourselves
Changes for youAnything is possible — if the team stays and is not pulled elsewhereOn the vendor's roadmap and prioritiesDays rather than quarters: our own delivery pipeline
Where we loseFull control over the code and priorities stays with youA large partner ecosystem, training and certificationWe are a small team and we do not take every job
06Cost

Price on request

There is no price list, and that is not a trick: almost every product needs configuration for your processes and integrations, so the same system costs differently at two companies. We quote after the demo, when the scope is visible — not before it.

01

What you get

A working product rather than from-scratch development. The core already exists and runs in our own company, so you pay for the rollout and the fit-out, not for inventing the solution.

02

What the quote is made of

The amount of fit-out for your processes, the number and complexity of integrations, and the requirements around data and timing. All of it becomes visible after a demo on your own data.

03

When we name a figure

After the demo and a short review of your case. The quote is fixed — not time-and-materials.

Where the work stops

AI does not make decisions for you: it does not send quotes, post documents or approve carrier payments without a person. Everything it did is visible and logged. Products in pilot are marked on the page.

07FAQ

Questions about this solution

Where do we start with AI in logistics?

With one process that has a clear metric — for example, quote pricing or request handling. First we show how it works in our company on a live system, then we run a pilot on your data.

Do we have to replace our TMS or WMS?

No. The AI services sit next to your systems and work through them: e-mail, 1C, CRM, exports.

What if the AI gets it wrong?

That is why the decision stays with a person: AI prepares a draft, a price or a list of discrepancies, and an employee confirms. Every action is logged, so a mistake can be traced.

Can our data stay out of external services?

Yes. Language models can run on your own servers — that is how our own AI platform works.

08Related solutions

Related solutions

See it on your data

Forty minutes, a working product, no slides. Then a pilot in your environment.

Discuss your case +7 499 346 3588

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