AI-Powered
Container Intelligence

Automated tracking. Real-time visibility.
Every container, every condition, every time.

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0% Faster
Gate Processing
0% Accurate
OCR Recognition
0/7 Operation
All Weather
The Challenge

Your yard is running blind.

Logistics facilities managing containers face critical visibility gaps that cost thousands every month in lost time and penalties.

01

Fragmented Visibility

Separate systems and paper logs create blind spots across your yard, making it impossible to know exactly where assets are at any given moment.

02

Manual Bottlenecks

7-10 minutes per transaction at the gate creates massive queues, backing up local traffic and destroying throughput efficiency.

03

Data Entry Errors

Manual transcription of container codes cascades into disputed records, lost containers, and thousands in demurrage fees.

04

Reactive Management

Problems are discovered hours or days after the fact. By the time you know a container is damaged or missing, the cost has already been incurred.

One platform. Five amazing products.

Gate and Yard OCR

AI-powered container data reading at the gate and across the yard. 82% faster processing.

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Damage Detection

External + Internal AI-Assisted assessment.

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Basic Yard Analytics

Fully customizable real-time dashboards, e.g. detention & demurrage tracking, In & Out flow trends, damage types and costs, etc.

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Advanced Yard Analytics

Agentic-AI predictive insights. Data audits for error detection and correction based on GateIn.AI's proprietary Physical Truth Engine. Natural Language Processing for Text-to-SQL queries.

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Theft and Fraud Prevention

GateIn compares equipment data with authorized records. Gate staff do driver checks before cargo release. Every decision, including each approval and exception, has an owner, evidence and a timestamp. These records show the chain of custody.

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EGHU 826260-645G1 · 40ft HC · TARE 3,800kgEGHU 826260-6 · 45G1 · 40ft HCISO: 45G1 | CONF: 0.997VALIDATEDT+00:00 · FRM 0000GATE-01 · CAM-A/B◇ TRACKINGSYSTEM ACTIVE
TGHU 715392-145G1 · 40ft HC · TARE 3,800kgMSCU 447291-345G1 · 40ft HC · TARE 3,750kgCMAU 582910-445G1 · 40ft HC · TARE 3,900kgISO: 45G1 | CONF: 0.998VALIDATEDT+00:00 · FRM 0000DRONE-X1 · AERIAL-CAM◇ PATROLSYSTEM ACTIVE

From camera to dashboard in under 8 seconds.

STEP 01

Image Capture

Multi-camera array captures every angle

STEP 02

AI Processing

Edge AI processes locally, no cloud needed

STEP 03

Validation

Automatic validation against databases

STEP 04

Output

Real-time results via API or dashboard

Containers Stored longer than 30 days (not Exited)

Container NumberStorage Dura...Event Day: DayEvent TimeExit StatusImage LinkFrame #
TEBU761272034.5224/9/202517:19Nohttp://localho...21
TRHU530443234.5024/9/202517:51Nohttp://localho...15
MILE100073034.0425/9/202504:50Nohttp://localho...26
ICNU615058033.9925/9/202506:07Nohttp://localho...16
MSBU552166334.0025/9/202506:01Nohttp://localho...24
SZLU981195333.9425/9/202507:25Nohttp://localho...25
CSUZ325832233.8725/9/202509:09Nohttp://localho...20
MSKU950161033.8625/9/202509:19Nohttp://localho...12

Showing first 2,000 rows

Containers Stored longer than 60 days (not Exited)

Container NumberStorage Dura...Event Day: DayEvent TimeExit StatusImage LinkFrame #
MSAU347134092.995/11/202506:14Nohttp://localho...20
MNBU912406992.935/11/202507:41Nohttp://localho...15
SUDU898950492.885/11/202508:50Nohttp://localho...18
CIMU023899492.795/11/202510:54Nohttp://localho...21
MEDU989623092.775/11/202511:26Nohttp://localho...33
CAAU654932192.695/11/202513:20Nohttp://localho...69
WNGU303382292.695/11/202513:21Nohttp://localho...38
COCU699511292.605/11/202515:35Nohttp://localho...15

Showing first 2,000 rows

Accumulated Detention&Demurrage Total Days Count

Total Days of Detention&Demurrage03006009001200150018001/9/20251/10/20251/11/20251/12/2025Calculation Date

Accumulated Detention and Demurrage Cost

Total Daily Accumulated Cost$0$30K$60K$90K$120K$150K$180K1/9/20251/10/20251/11/20251/12/2025Calculation Date

Rain. Night. Shine. Any Condition. Doesn't matter.

DAY

Clear conditions, full accuracy

RAIN

Wet weather, no degradation

NIGHT

Complete darkness, infrared capable

Live damage detection — bounding box + classification

Container Damage Detection

Global deployments across USA, Europe, and Mexico.
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From paper forms to pixel-perfect detection.

Today's damage audits rely on clipboards, handwritten codes, and the inspector's criteria. GateIn AI scans every surface in minutes and delivers a digital record of what it found.

Damage assessment today · Slow & manual

Clipboards, codes, and best-guess visibility.

Inspectors walk the container, eyeball the damage, and mark handwritten codes on a paper form. Photos live on someone's phone. The record needs to be reconciled and digitized which leads to errors and misinterpretations.

Dent damage
Rust / corrosion
Panel hole
Door damage
Floor damage
Roof damage
Paper container inspection survey form — the handwritten record inspectors fill out at the gate today
Container Survey Form — still filled by hand at most facilities
Time per audit
~20 minutes
Time for image reconciliation and report generation
~60 minutes
Damage assessment now · GateIn AI

Every finding mapped in minutes, not hours.

Same container, same CEDEX and IICL damage codes. Now every finding is a hotspot on the asset — with photo, position, and a structured severity score. Each digital report is delivered with pre-defined damage categories and customer defined damage assessment scores. Tap any zone to see the record.

Scan complete — 3 findings
Tap any marker to inspect

Repair Management Dashboard Across Your Fleet

Weekly container repairs

Last 8 weeks

Jan 8 · 8 repairsJan 8Jan 15 · 14 repairsJan 15Jan 22 · 22 repairsJan 22Jan 29 · 11 repairsJan 29Feb 5 · 17 repairsFeb 5Feb 12 · 24 repairsFeb 12Feb 19 · 13 repairsFeb 19Feb 26 · 18 repairsFeb 26

Monthly damage by category

Trailing 12 months

Frame Distortion · Jan · 18Panel Puncture · Jan · 12Rusted Floor · Jan · 9Corner Post · Jan · 7Others · Jan · 5JanFrame Distortion · Feb · 14Panel Puncture · Feb · 11Rusted Floor · Feb · 8Corner Post · Feb · 6Others · Feb · 4FebFrame Distortion · Mar · 16Panel Puncture · Mar · 10Rusted Floor · Mar · 7Corner Post · Mar · 5Others · Mar · 4MarFrame Distortion · Apr · 12Panel Puncture · Apr · 9Rusted Floor · Apr · 8Corner Post · Apr · 6Others · Apr · 5AprFrame Distortion · May · 13Panel Puncture · May · 10Rusted Floor · May · 9Corner Post · May · 7Others · May · 4MayFrame Distortion · Jun · 17Panel Puncture · Jun · 11Rusted Floor · Jun · 10Corner Post · Jun · 6Others · Jun · 5JunFrame Distortion · Jul · 22Panel Puncture · Jul · 15Rusted Floor · Jul · 13Corner Post · Jul · 9Others · Jul · 6JulFrame Distortion · Aug · 24Panel Puncture · Aug · 14Rusted Floor · Aug · 12Corner Post · Aug · 10Others · Aug · 7AugFrame Distortion · Sep · 26Panel Puncture · Sep · 16Rusted Floor · Sep · 14Corner Post · Sep · 11Others · Sep · 8SepFrame Distortion · Oct · 23Panel Puncture · Oct · 14Rusted Floor · Oct · 11Corner Post · Oct · 9Others · Oct · 6OctFrame Distortion · Nov · 19Panel Puncture · Nov · 12Rusted Floor · Nov · 9Corner Post · Nov · 8Others · Nov · 5NovFrame Distortion · Dec · 16Panel Puncture · Dec · 11Rusted Floor · Dec · 8Corner Post · Dec · 7Others · Dec · 4Dec

Inspection time by type

Mean ± 1σ (minutes)

REEReefer · 3.00 min ± 1.004HC40' High Cube · 2.70 min ± 0.9040S40' Standard · 2.40 min ± 0.80TNKTank · 2.30 min ± 0.80OPNOpen Top · 2.15 min ± 0.70FLTFlat Rack · 2.00 min ± 0.7020S20' Standard · 1.90 min ± 0.60
Advanced Analytics

The only platform that reconciles physical truth across all your systems data

Competitors read container codes. We verify what actually happened.

Everyone Else

Camera
No reconciliation
Basic OCR
No diagnostics
Terminal Operating System

GateIn AITHE STANDARD

Camera Array

Physical Truth Engine

Reconcile
Diagnose
Audit Trail
Terminal Operating System
Only platform that catches discrepancies before they enter your system.

Theft / Fraud Prevention

Know what leaves.
Prove what happened.

Connect gate images, equipment IDs and timestamps to your release records—so your team can check discrepancies before cargo moves.

Request a Demo Explore the workflow

Every decision has an owner, evidence and a timestamp.

Driver’s license, license plates, a separate shipping container and an empty chassis, joined by a shared line to match an authorized pickup.
Match to the authorized pickup
01See the equipment that arrives
02Check it against the release
03Preserve the chain of custody

At the point of release

A valid appointment.
The right truck?

Compare the truck plate, chassis plate, chassis serial and container code with the expected release. Gate staff scan and check the driver’s license against the driver database. If used, they also scan the GateIn appointment QR code and confirm it against the appointment record.

Explore a release check
Illustrative workflow · sample data
VERIFICATION INPUTSEVENT EV-0482
Four separate verification inputs: driver’s license, license plates, container code and chassis serials.

Driver’s license · Truck + chassis plates
Container code · Chassis serial

Human check at the gate

Scan and confirm the driver’s license

Gate staff scan the license, check the details and confirm they match the authorized driver database record.

REFERENCE WORKFLOW4 INPUTS + OPTIONAL QR
RELEASE CHECK / AP-0482

Physical record comparison

Review needed
Comparison of expected release details and the observed gate event
CheckExpectedAt the gate
Truck plateTRK 204TRK 907 ≠
Chassis plateCHS 318CHS 318
Chassis serialCHS-08421CHS-08421
Container codeGATU 123456 9GATU 123456 9
Driver’s licenseDriver databaseHuman confirmed
Appointment QR (optional)AP-0482Human confirmed
Release ref.REL-0482REL-0482
Plate mismatch. Review before release.

The truck plate differs from the expected record. Assign the exception to a named owner. Record their decision, reason, evidence and timestamp; any release approval must identify its approver.

Every decision has an owner—including exceptions—with linked evidence and timestamps.Release remains subject to your authorization process.

QR appointment confirmation is optional. When it is not used, record “Not used”; it does not create a missing-release exception. All values and human-check results shown here are sample data.

Illustrative configuration, not a live product screen or customer result. Matching rules and release-system connections are scoped for each deployment.

From camera to accountable handoff

The record is only useful
when it stays connected.

Build a chain of custody from arrival to release. Record who hands over custody and who receives it. Link every approval and exception to a named decision owner, supporting evidence and timestamps.

STEP 01

Capture

Capture truck and chassis plates, chassis serial, container code, gate images and timestamps. Gate staff scan the driver’s license and, if used, the GateIn appointment QR code.

STEP 02

Compare

Compare equipment with the expected release. Gate staff check scanned license details against the driver database and any optional QR confirmation against the GateIn appointment record.

STEP 03

Review

Assign every approval and exception to a named owner. Record their decision, reason, supporting evidence and timestamp. Follow your escalation and authorization process before release.

STEP 04

Link

Preserve the chain of custody: link each handoff, its outgoing and incoming custodians, the approval owner, exceptions, evidence and timestamps to the cargo and release record.

One event. Every decision accounted for.

Chain of custody.
Clear approval ownership.

See who held custody, who approved each movement and when. Every decision, including an exception, has a named owner, a recorded reason, supporting evidence and a timestamp linked to the same gate event.

A single event ID connects visual evidence, equipment IDs, time and location, and operator review.

Built around your gate process

A stronger check.
A clearer record.

Physical evidence supports the people and procedures responsible for protecting each release.

Does a matching plate verify the driver?

No. Matching equipment does not verify the driver. At the gate, a human scans the driver’s license, checks the details and confirms they match the authorized driver database record. Release remains subject to your authorization process.

What happens if a read is uncertain?

Glare, darkness, mud and blocked views can affect capture. Assign the exception to a named owner to review the evidence. Record their decision, reason and timestamp, and identify the authorized approver before release.

How does this connect to our release system?

Compare equipment with your release records and have gate staff confirm scanned license details against your driver database. Optionally, staff scan a confirmation QR code from the GateIn appointment system and check it against the appointment record. Connections are scoped to your operation.

Can gate evidence prevent every theft?

No single control can prevent every theft. A connected physical record supports checks at the handoff and helps reconstruct events afterward. It works alongside carrier vetting, driver verification and your release procedures.

Put a physical check
behind every release.

Walk through your gate process with GateIn. Connect physical evidence, chain of custody and clear approval ownership to strengthen your theft and fraud prevention controls.

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Shipping containers stacked at a port depot

Container Depots

Container OCRDamage DetectionInventory Accuracy
Intermodal container terminal at night with stacked cargo containers

Intermodal Terminals

Rail OCRChassis TrackingCross-dock Flow
Aerial view of a distribution center yard with rows of shipping containers

Warehouse & DC Yards

Dock SchedulingTrailer TrackingWMS Integration
Container vessel docked at a 3PL port terminal with gantry cranes

Third-Party Logistics (3PL)

Multi-tenantCustomer PortalsSLA Tracking
Refrigerated reefer container stack at a cold-chain storage facility

Refrigerated & Cold Storage

Reefer PriorityCold ChainFSMA Compliance
Industrial manufacturing facility with loading bays and production equipment

Manufacturing Facilities

JIT DeliveryVendor ManagedERP Integration
Industrial Versatility

Precision built for the
global supply chain.

Purpose-built AI for every link in the logistics chain. From port terminals to distribution centers, our computer vision platform learns the rhythms of your yard.

Reading container codes, tracking chassis, flagging damage, and feeding every movement into your existing systems.

One platform, trained on the realities of global supply chain operations.

Built by people who've shipped AI at scale.

Bernardo Mendez, CEO at GateIn AI

Bernardo Mendez

CEO

Electrical engineer with an MBA & 18 years of Product Management experience. Product and engineering leader in Energy, Robotics, and Autonomous Vehicles.

Jordi Goni, CPO / COO at GateIn AI

Jordi Goni

CPO / COO

Experience working in IT / Supply Chain engagements and Edge computing helping clients innovate. Working experience across EMEA, US and LATAM.

Paul Miller, CTO at GateIn AI

Paul Miller

CTO

Software Engineer, AI, ML, Autonomous Systems, Robotics, Digital Twin Simulation

Anton Shpak, Computer Vision Engineer at GateIn AI

Anton Shpak

Computer Vision Engineer

Computer vision engineer building models that hold up in production. Previously at a YC-backed high-throughput screening startup. Applied math, USC summa cum laude.

Evan Cooke, Software Engineer at GateIn AI

Evan Cooke

Software Engineer

Software engineer focused on data-driven AI. CS & Engineering at the University of Iowa. Builds computer vision pipelines and reliable production backends.

Partnered with
NVIDIA Inception ProgramGoogle for StartupsAI House

See it in action.

30-minute demo. No commitment. See GateIn AI tracking containers in real-time.

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Email us directly

hello(at)gatein.ai

What happens next?

  1. 1Schedule 30 min discovery call
  2. 2Receive customized ROI analysis
  3. 3On-site proof of value demo
  4. 4Go live in weeks, not months