# Gather AI

**Canonical:** https://apis.io/providers/gather-ai/  
**Website:** https://www.gather.ai/  
**APIs profiled:** 0

Gather AI is a Physical AI platform for logistics that gives warehouses dock-to-dock inventory visibility. Cameras mounted on autonomous drones and forklifts capture inventory, and computer vision extracts structured data (LPNs, UPCs, lot codes, and free text) from the imagery. Its Sage AI engine analyzes operations and surfaces prioritized actions before each shift, while automated Workflows route tasks to the right personnel across integrated systems. The plug-and-play solution deploys in hours alongside existing warehouse management systems, serving manufacturing, healthcare, food & beverage, retail, and 3PL operations. Surfaced as a portfolio company of bain-capital-ventures and bloomberg-beta.

## Kin Score — 9.7 / 100 (minimal)

Scored 2026-08-21 under rubric 0.12.0. Trend: flat (+0.0 from 9.7).

| Facet | Score |
|---|---|
| Discoverability | 50.0 |
| Contract Quality | 0.0 |
| Governance | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 2.4 |
| Commercial Clarity | 21.1 |
| Access Clarity | 21.1 |

## Agent readiness — 0.0 (human-only)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | no |
| Idempotency | no |
| Error Semantics | no |
| OpenAPI Examples | no |
| Rate Limit Signal | no |
| Event Surface Described | no |
| Agent Skills | no |
| Well Known Catalog | no |
| Consent Identity | no |
| Agent Card | no |
| Dry Run Mode | no |

## Access

Unknown — onboarding: unknown, pricing: unknown, trial: no (confidence: low).

## Security (1)

- **Gather Ai Domain Security** — TLSv1.3 · HSTS · DMARC

## Tags

Company, Physical AI, Logistics, Warehouse Inventory, Computer-Vision, Drones, Supply Chain, Robotics

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Profiled by [API Evangelist](https://apievangelist.com) and published on [APIs.io](https://apis.io/providers/gather-ai/). Scores are computed from the provider's own public artifacts under a published rubric.