3D Bin Packing API

Name: 3D Bin Packing API
Brand: 3D Bin Packing API
Availability: InStock

★ Only Publicly Available OpenAPI DocumentE CommerceShipping LogisticsapiKey6 EndpointsREST

For Agents

Compute optimal 3D placements of items into bins, pallets, or containers, find the smallest bin that fits a load, and validate maximum-load constraints.

Install Jentic One Beta

Connect the 3D Bin Packing API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the 3D Bin Packing API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with 3D Bin Packing API.

Pack items into multiple bins with configurable goals — minimize bin count, maximize space usage, or minimize cost

Compute optimal pallet packing layouts with item rotation and weight stacking constraints

Find the smallest stock bin from a catalogue that fits a list of items

GET STARTED

Start building with 3D Bin Packing API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI specification for 3D Bin Packing API, keeping it validated and agent-ready. The 3D Bin Packing API computes optimal placements for items inside bins, pallets, or shipping containers. It supports multiple optimisation modes (minimize bins, maximize utilisation, minimize cost), 3D coordinate placement, weight constraints, and visual SVG/PNG output. The API exposes six endpoints covering multi-bin packing, pallet packing, smallest-bin search, dimension lookup, box-size try-out, and maximum-load checks, with a hard limit of 4,999 items per request.

Use Cases

Patterns agents use 3D Bin Packing API for, with concrete tasks.

★ Carton Optimisation for E-Commerce Fulfilment

When a customer orders multiple items, decide which standard carton sizes to ship them in. The packIntoMany endpoint takes the order's items and the available bin catalogue and returns a packing plan that minimises bin count or maximises utilisation. Warehouses use this to cut shipping cost and reduce dimensional weight charges.

Pack a 12-item order into the smallest combination of three available carton sizes (Small/Medium/Large) using packIntoMany with the goal of minimizing bin count, and return per-item 3D coordinates.

Pallet Build for Wholesale Shipments

Compute pallet layouts for wholesale or B2B shipments where items must stack within a maximum height and weight. The palletPack endpoint accepts the pallet dimensions, items with weights, and stacking rules, and returns a 3D placement plan plus utilisation metrics so warehouse staff can build the pallet correctly the first time.

Build a EUR pallet (1200x800x1500mm, 1000kg max) layout for 80 cartons of mixed sizes using palletPack with weight-aware stacking.

Smallest Bin Lookup for Single-Item Orders

For single-SKU orders, pick the smallest available shipping bin that the item fits into. The findSmallestBin endpoint searches a catalogue of bins and returns the smallest one that can hold the supplied items — useful in real-time at the warehouse pick-and-pack station to reduce void fill.

From a catalogue of 10 bin sizes, find the smallest bin that fits a single item measuring 250x180x60mm at 1.2kg using findSmallestBin.

Agent-Driven Packing Optimisation

Let an AI agent select the right packing strategy by intent — choose between pack-into-many for ecommerce orders, pallet-pack for B2B shipments, or smallest-bin lookup for single-SKU orders — through Jentic. The agent supplies items and constraints, and Jentic injects the username API key transparently.

Through Jentic, search 'pack items into bins', load the packIntoMany schema, supply the order's items and the bin catalogue, and return the optimal packing plan.

Key Endpoints

6 endpoints — jentic publishes the only available openapi specification for 3d bin packing api, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

POST

/packer/packIntoMany

Pack items into multiple bins with optimisation goals

POST

/packer/palletPack

Compute optimal pallet packing layout

POST

/packer/findSmallestBin

Find the smallest bin that fits items

POST

/packer/findBinSize

Look up bin dimensions

POST

/packer/tryOutBoxSizes

Test a candidate box size against representative items

POST

/packer/checkMaxLoad

Check whether a load exceeds a bin's max weight

POST

/packer/packIntoMany

Pack items into multiple bins with optimisation goals

POST

/packer/palletPack

Compute optimal pallet packing layout

POST

/packer/findSmallestBin

Find the smallest bin that fits items

POST

/packer/findBinSize

Look up bin dimensions

POST

/packer/tryOutBoxSizes

Test a candidate box size against representative items

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

The 3D Bin Packing username query-string credential is stored encrypted in the Jentic vault. Agents call packIntoMany and other operations through Jentic, which injects the username parameter at execution — the credential never enters the agent's context.

Intent-based discovery

Agents search Jentic by intent (e.g., 'pack items into boxes' or 'find smallest bin') and Jentic returns the matching 3D Bin Packing operation along with its input schema, so the agent calls the correct endpoint without reading the vendor docs.

Time to first call

Direct 3D Bin Packing integration: 1-2 days to model items, bins, and goals plus map response coordinates. Through Jentic: under 1 hour — search, load, execute.

FAQs

Specific to using 3D Bin Packing API through Jentic.

Why is there no official OpenAPI spec for 3D Bin Packing API?

3DBinPacking.com publishes HTML reference documentation but no OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call 3D Bin Packing API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the 3D Bin Packing API use?

It authenticates by passing a username as the query parameter username on every request to https://global-api.3dbinpacking.com. Through Jentic, the username key is stored encrypted in the vault and injected at execution — the agent never sees the credential.

How many items can I pack in a single request?

The vendor enforces a hard limit of 4,999 items per request across packIntoMany, palletPack, and the other endpoints. For larger orders, split items into batches and combine the resulting plans on the client side.

Can I get a visual representation of the packing layout?

Yes. packIntoMany and palletPack support visual output in SVG or PNG format, which most developers use to render a per-bin layout for warehouse pickers. Item placements are also returned as 3D coordinates for programmatic processing.

How do I find the smallest box for a set of items through Jentic?

Run pip install jentic, then search 'find smallest bin', load the findSmallestBin operation, supply items with dimensions and weights plus the candidate bin catalogue, and execute. Sign up at https://app.jentic.com/sign-up to receive an agent API key.

What optimisation goals does the packing engine support?

packIntoMany supports goals including minimise bin count, maximise utilisation, and minimise total cost given per-bin price. The choice of goal is passed in the request body and changes which bins the engine prefers when several feasible plans exist.

3D Bin Packing API

Connect the 3D Bin Packing API to your agent

Capabilities

Start building with 3D Bin Packing API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs