Verticals Global logistics
Global logistics on one shared ontology
Brokerages, forwarders, warehouses, ports, carriers, and shippers don’t share systems — but they must share meaning. Automata turns that meaning into policy, simulation, and software that executes — from a high-volume desk to a capital-scale operating program.
The problem
Logistics AI fails when every party keeps a private picture of the same shipment
Tariff tools speed one desk. Agents encode one team’s SOP. Solvers optimize one feed. The chain still breaks at the seams — documents, partners, terminals, and rules that never became a shared model.
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Shared ontology
Shipments, legs, documents, parties, commodities, lanes, and obligations become first-class entities — the same meaning whether the desk is brokerage, forwarding, the warehouse floor, or a terminal gate.
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Deterministic policy
Tariffs, PGA rules, carrier constraints, terminal cutoffs, SLAs, and customer playbooks become measurable gates — checked before work leaves the desk, with reasons when it cannot.
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Verify, then execute
Model a filing change, routing exception, gate policy, or new SOP against graded knowledge before it hits ABI, TMS, WMS, TOS, or the dock. Humans approve high-impact actions.
Who we build for
Same platform. Different operating party
One ontology, tuned per role — brokers, forwarders, warehouses, ports, carriers, and shippers stop translating the world by hand.
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Customs brokerages
Entries, ISFs, HTS, and PGA work still restart from documents and tribal importer knowledge — while tariff stacks keep moving.
- → Ontology of importer, product, HTS history, and filing obligations
- → Policy packs that encode Chapter 99 / 232 / 301 / AD-CVD stacking logic
- → Draft → validate → release into the ABI stack you already run
Fewer minutes per entry without betting accuracy on a single operator’s memory.
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Freight forwarders & NVOCCs
Quotes, bookings, docs, and exceptions span ocean, air, and last mile — with SOPs trapped in email and senior staff.
- → One shipment graph across modes, parties, and milestones
- → Exception policies that escalate only when constraints break
- → Reuse of lane and customer patterns instead of rebuilding each booking
Forwarding that compounds institutional knowledge instead of resetting every file.
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Warehouses, 3PLs & fulfillment
WMS truth, labor reality, and customer SLAs diverge — modernization freezes because nobody trusts a single picture of the floor.
- → Reconcile SKU, order, wave, dock, and labor into one operational ontology
- → Simulate slotting, wave, or dock changes before committing
- → Connect OT/IT events back to the customer obligation they affect
Continuous improvement without pausing the line for another one-off project.
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Ports & marine terminals
Gate, yard, berth, and hinterland handoffs still run on fragmented systems and institutional memory — while volume, dwell, and partner expectations keep rising.
- → Ontology of vessel call, berth window, container, chassis, appointment, and hinterland mode
- → Policy packs for gate, yard, cutoffs, and partner SLAs — auditable before they hit the floor
- → Agents that draft and validate operating decisions against TOS / PCS / appointment stacks you already run
A living operating model of the terminal — not another dashboard on top of the same seams.
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Freight brokerages
Load boards, carrier matching, and customer service are high-volume and high-variance — accuracy collapses when volume spikes.
- → Entity model for load, tender, carrier capacity, and rate history
- → Guardrails that keep agents inside approved playbooks
- → Touchless paths for clean loads; human loop only on true exceptions
Throughput that scales without teaching every new hire the whole network by hand.
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Carriers — FTL & LTL
Dispatch, detention, claims, and customer updates live across TMS, email, and phone — rarely in one coherent state.
- → Living map of tractor, trailer, driver, appointment, and customer commitment
- → Pre-validate schedule and constraint changes before they hit the road
- → Event replay when a claim or detention dispute needs the real timeline
An operation that stays coherent as volume and network complexity grow.
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Shippers, manufacturers & BCOs
Spend, service, and compliance are split across forwarders, brokers, and carriers — with no durable model of how work actually happens.
- → Cross-party ontology of lanes, partners, and performance signals
- → Policy packs for preferred routing, risk, and cost constraints
- → Visibility into why a decision was made — not just what shipped
Control of the chain without ripping out every partner’s stack.
Engagements
From high-volume desks to capital-scale programs
Attractive work lives on both sides: service providers who need throughput and accuracy now, and operators running multi-year modernization. Same ontology layer — different engagement shape.
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Desk & service-provider automation
Brokerage, forwarding, and 3PL ops where the product is throughput and accuracy — ontology + agents on the files, filings, and exceptions you already run.
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Warehouse & fulfillment programs
WMS/OT modernization where the hard part is trust in the operating model — not another integration map.
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Terminal & network modernization
Multi-year programs for ports, hubs, and shipper control towers — encode how the node or network actually operates before rewriting every adjacent system.
Position
The layer under the tools the market already sells
Entry copilots, agent workforces, and decisional solvers each solve a slice. Automata is the ontology and policy environment those slices need to stay consistent across the chain.
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Not only desk automation
Faster entries and filings matter — but they still fail when the underlying product, party, and policy model is incomplete. We start with that model.
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Not only an agent workforce
Agents that copy SOPs help a team move faster. Ontology makes those SOPs shared, auditable, and reusable across desks, terminals, and partners.
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Not only solvers on a feed
Optimization needs clean objects and constraints. We build the graph and policy layer those decisions sit on — then wire execution back into the systems you already run.
Next
Bring a desk, a warehouse, a terminal, or a network
We’ll map the entities and constraints that already run your operation — then show where ontology, policy packs, and simulation remove the next year of one-off work. Start with a conversation; leave with a scoped outline.