# BoothIQ

**Canonical:** https://apis.io/providers/getboothiq-com/  
**Website:** https://getboothiq.com/  
**APIs profiled:** 0

BoothIQ provides an AI‑powered lead capture application for trade shows and other in‑person events. The app lets exhibitors, attendees, and organizers scan badges or business cards, enrich contacts, and generate AI‑driven follow‑up emails and event insights without hardware rentals or per‑scan fees. It integrates with CRM systems on its Enterprise plan and works offline, syncing data when a connection is available.

## Kin Score — 15.2 / 100 (emerging)

Scored 2026-11-13 under rubric 0.28.0.

| Facet | Score |
|---|---|
| Discoverability | 48.2 |
| Contract Quality | 0.0 |
| Contract Governance | 0.0 |
| Operational Transparency | 0.0 |
| Developer Ergonomics | 2.4 |
| Access Clarity | 51.1 |

Regulatory layer — **Horizontal (data, software, accessibility, platform)**: 12.7 (matched via fallback).

## Agent readiness — 18.7 (agent-aware)

| Dimension | Value |
|---|---|
| Spec Presence | no |
| Agentic Access | no |
| Reversibility Documented | no |
| MCP Server | no |
| Auth Clarity | served |
| 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 |
| Delegated Identity | served |
| Protected Resource Metadata | verified |
| Dynamic Client Registration | yes |
| Agentic Commerce | no |
| Pagination Ratio | na |
| Operation Distinctiveness | na |
| MCP Tool Quality | na |

## Access

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

## Security (1)

- **BoothIQ Domain Security** — TLSv1.3 · HSTS · DMARC

## Plans (1)

- **BoothIQ Plans Pricing**

## Tags

Lead Capture, Trade Shows, Artificial Intelligence, CRM Integration, Offline Capture

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