Ambi Robotics
Ambi Robotics is a Berkeley, California AI robotics company building parcel-sortation and induction robots for ecommerce, postal, and logistics workflows. Founded in 2018 as Ambidextrous Laboratories — a spin-out of UC Berkeley's Dex-Net Project led by Ken Goldberg — by Jeff Mahler (CTO), Stephen McKinley, David Gealy, and Matt Matl, with Jim Liefer (ex-Walmart, ex-UPS) as CEO. Its flagship products are AmbiSort A-Series (sort-to-sack small parcel sorting), AmbiSort B-Series (sort-to-gaylord parcel induction for middle-mile and reverse logistics), AmbiStack (mixed-case stacking for inbound and outbound), and AmbiVision (3D dimensioning, OCR, defect detection, and visual quality inspection). All robots run AmbiOS, the company's cloud-native "operating system for physical intelligence," comprising the AI Skill Suite (Sort, Stack, Kit, Pack, Induct apps), the PRIME-1 foundation model trained on millions of real-world operations, AmbiVision perception, AmbiAccess fleet management dashboard with heat maps and remote support, and a Sim2Real training pipeline that compresses model training by up to 10,000x. Ambi Robotics' primary commercial deployment is a $23 million expansion with Pitney Bowes, with AmbiSort A-Series and B-Series systems deployed across Pitney Bowes ecommerce hubs in the US (including the Stockton, CA hub that nearly doubled local-direct-delivery throughput in the 2021 peak holiday season, and middle-mile B-Series systems that sorted more than 3 million parcels within four months of deployment). Ambi Robotics does not publish a public developer API, SDK, or open-source release for AmbiOS, AmbiSort, AmbiStack, or PRIME-1; integration with customer WMS/WES systems is performed by Ambi's solutions team. The company's public GitHub org primarily contains forks of infrastructure tooling (Ray, trimesh, FCL, EIPScanner, tinygltf, rapier, jszmq, CVXPYgen, mongoose-delete) and internal CI/CD workflow utilities — no published API spec, SDK package, or developer documentation.
More than an index entry, but the surface is still mostly links rather than artifacts — the cohort most likely to move a full band from modest, well-targeted work.
API Evangelist profiles Ambi Robotics the way a machine reads it — 2 machine-readable artifacts, pulled from the provider's own public surface and indexed so a developer, an analyst, or an AI agent can evaluate it against every other provider on the network.
Every provider in the network is reduced to the same set of machine-readable artifacts — OpenAPI contracts, event specifications, GraphQL schemas, runnable collections, pricing and rate-limit signals, security posture, OAuth scopes, and the agent surfaces (MCP servers and skills) that let software drive the API on its own. We profile them because the interface is the part of a company you can actually inspect: it is a truer signal of what a provider does than any marketing page. From those artifacts we compute the Kin Score — Ambi Robotics scores 13.3/100 (emerging), with a separate agent-readiness read of 0/100 (human only). The full breakdown is below, followed by every artifact we hold — each card links through to its machine-readable definition on apis.io.
Kin Score
This is the API Evangelist rating — a single, repeatable read computed from the artifacts on this page. Green fill is points earned; the red track is points possible, so every bar shows earned-versus-possible at a glance. Every facet and dimension name is a link: it opens that measurement's page on APIs.io, where the rating runs across the whole catalog — the exact checks that feed it, how every profiled provider distributes on it, and who is at the top of it.
Kin Score
How this is scored →scored 2026-09-10 · rubric v0.20.0
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How we profile Ambi Robotics
Each block below is one kind of artifact we hold for Ambi Robotics. For each we say what it is and why it earns a place in the profile, then list every one we've indexed — capped at two rows, scroll within the panel for the rest.
Semantic Vocabularies 1
JSON-LD contexts give the data shared meaning across APIs. We profile them because semantics are what let a machine reconcile 'customer' here with 'customer' somewhere else.
JSON-LD contexts and semantic vocabularies used across these APIs.
Ambi Robotics Context
JSON-LDSecurity Posture 1
Authentication, domain security, vulnerability disclosure, and trust-center signals — the evidence that a provider takes security seriously enough to document it. We profile it because you can't govern what you can't see.
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Every other property we hold for Ambi Robotics — documentation, portals, status pages, policies, and corporate surface — grouped by the job it does, following the integrator's arc from getting started to running in production.
Build 1
SDKs, sample code, and the tooling you integrate with
Access & Security 2
Authentication, authorization, and security posture
Learn 1
Tutorials, courses, talks, and written guidance
Operate 1
Status, limits, changes, and where to get help
Commercial 2
Pricing, plans, and the legal terms of use
Company 8
The organization behind the API
Scroll within the panel for all 8 ·
Other 6
Properties that don't map to a standard resource type
← All providers · Data indexed from github.com/api-evangelist/ambi-robotics · machine-readable index on apis.io
This is an independent, third-party profile of Ambi Robotics, published by API Evangelist. We do not operate, host, resell, or support these APIs, and we are not affiliated with or endorsed by the company unless stated above. Everything here is built from publicly available information — the company's own site, developer portal, documentation, public repositories, and the specifications it publishes for public use. Nothing is obtained by breaching a system, defeating an access control, or using credentials.
The Kin Score and Agent Readiness rating are independently calculated assessments of a company's public API artifacts, scored against a published rubric. They are not certifications, endorsements, security assessments, or audits.
Corrections, re-scores, and removal are free — no partnership or purchase required, and you do not need to justify the request. A removed company is recorded as unrated, never scored zero for having asked. Acknowledgement within one business day; removal within two.
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