Freight & Logistics

AI that clears your freight and supplier paperwork.

We capture the documents, validate them against your contracted rates and purchase orders, and post clean records to your ERP and TMS.

Deeply trusted by enterprises globally

  • IBM
  • AWS
  • Cisco
  • EY
  • Samsung
  • Graphcore

Lower cost per document

A single invoice costs $9.40 to process on average. Best-in-class teams that automate process the same invoice for $2.78.

Errors stop compounding

Industry estimates put the share of freight invoices containing errors at 5% to 15%. At high shipment volumes that is six-figure leakage every year.

Weeks, not months

We tailor a proven agent from a library built across 100+ production projects rather than starting from scratch.

Your operations team is buried in documents

Every week your people process invoices, shipment documents, and supplier paperwork by hand. Most of that work runs on manual effort or outsourced teams, and the errors inside it compound.

The documents in scope

  • Permits
  • Timesheets
  • Scanned certificates
  • Financial statements
  • Tax forms
  • Onboarding documents
  • Annotated PDFs
  • Email threads with attachments
$9.40

Average cost to process one invoice by hand

$2.78

Best-in-class cost per invoice once automated

5–15%

Share of freight invoices that contain errors

Five jobs AI does for your team

Start where the backlog is visible and the cost is measurable. The same agents cover the adjacent work once the first one is live.

/01

Freight invoice processing and audit

We capture carrier invoices, validate them against contracted rates, flag errors and overcharges, and post to your ERP. This is where the 5% to 15% error rate turns into recovered cash.

/02

Accounts payable automation

We capture invoices, match them to purchase orders, code them, and post to your ERP. Automation moves cost per invoice toward the best-in-class $2.78.

/03

Supplier and carrier onboarding

We collect documents, validate the data, and file it where your team needs it.

/04

Shipment and customs document processing

We read bills of lading, proofs of delivery, and customs paperwork, then verify the data and route it to the right queue.

/05

Quote and rate response

We draft quotes and rate replies from inbound requests.

Works inside the systems you already run

  • Freight invoice
  • BOL / POD
  • Shipment record
  • Rate or PO data
  • ERP / TMS
  • Email and portals

How we deliver it

01

Process redesign

Senior engineers map your document workflow and find the highest-return automation. They redesign the workflow around AI-first processes, then build the automation into it.

02

Solutions

We deploy AI agents from a library built across 100+ production projects. Tailoring a proven agent to your documents takes weeks. Building one from scratch takes months.

03

Managed delivery

We run the system after launch. We monitor accuracy, handle exceptions, and keep the integration to your systems of record current.

The production patterns behind the freight workflow

Swarm’s current proof comes from adjacent document-heavy operations: extraction, decision routing, and enterprise workflow integration. These are the same production patterns the freight solution uses.

Designed for risk-first freight buyers

Built to fit the stack, controls, and buying group you already have.

Works around ERP, TMS, and EDI

Swarm acts as an operations layer across the systems, portals, inboxes, and spreadsheets already running the business.

Human review is explicit

Define which records can move automatically, which require approval, and what happens when data is missing or uncertain.

Every decision has evidence

Keep extracted fields, matching context, exception reasons, approvals, and system updates together for audit and dispute review.

Clear data and system boundaries

Document where data enters, what the agent can access, where records are stored, and which actions it can take.

Ready for the buying group

Give operations, IT, procurement, finance, and AP a shared workflow scope instead of five different interpretations of the project.

One measurable workflow first

Start with a bounded queue and agreed metrics, prove the operating model, and expand only after quality and control are visible.

Put AI to work across your organization

Book a demo