# Apryse — API Agent Score

> Score: 49/100 (Grade: F) | Domain: apryse.com | Rubric: 1.0.0 | Checked: July 29, 2026

Apryse scored 49/100 (F), classified "not-ai-ready".

[View full report](https://www.postman.com/ai/ai-ready-apis/company/apryse)
[All organizations](https://www.postman.com/ai/ai-ready-apis/llms.txt)

## Summary

- Overall: 49/100 (F)
- Classification: not-ai-ready

## Category Scores

- API Design: 40/100 (F)
- Developer Experience: 50/100 (D)
- Agent Discovery: 79/100 (B)
- Agent Understanding: 53/100 (D)
- Agent Usability: 40/100 (F)

## Check Results

### API Design

- [fail] Security & governance hygiene — No security.txt at /.well-known/security.txt or /security.txt. Investigated: wellknown 0%.
- [fail] Example coverage — No detectable code samples across 4 sampled docs pages. Investigated: docs 0%.
- [skip] Machine-readable, versioned contract — No surface produced evidence for this capability in this run.
- [skip] Schema coverage & depth — No surface produced evidence for this capability in this run.
- [skip] Auth declared & discoverable — No surface produced evidence for this capability in this run.

### Developer Experience

- [pass] Changelog published — Newest official SDK activity 2 day(s) ago. Investigated: sdk 100%.
- [warn] Quickstart present — Quickstart page reachable (1 variants scanned starting at https://docs.apryse.com/guides/get-started) but no runnable code sample detected in HTML or .md variant. Investigated: docs 50%.
- [fail] Self-service developer portal — Signup page is sales-gated (contact-sales/request-access language detected). Investigated: docs 0%.
- [fail] Code samples in docs — No detectable code samples across 4 sampled docs pages. Investigated: docs 0%.
- [skip] Description completeness — No surface produced evidence for this capability in this run.

### Agent Discovery

- [pass] Registry & SDK presence — Indexed on Context7 (websites/apryse, 67178 snippets). Investigated: docs 100%, sdk 100%, cli 0%.
- [warn] Docs reachable, not hard auth-gated — Server ignores Accept: text/markdown header (0/50 sampled pages return markdown). Investigated: docs 75%.
- [warn] llms.txt present, valid & comprehensive — No llms.txt directive found in HTML of any of 49 sampled pages; 1 failed to fetch. Investigated: docs 44%.
- [pass] Crawlable / AEO — Docs paths crawlable by all monitored AI agents. Investigated: wellknown 100%.

### Agent Understanding

- [warn] Agent-navigable, token-efficient docs — 35 of 48 pages have substantive content differences between markdown and HTML (avg 48% missing). Investigated: docs 65%.
- [fail] Agent instructions file (AGENTS.md) — No AGENTS.md at the site root or /.well-known/. Investigated: wellknown 0%.
- [fail] Docs structured data — Neither JSON-LD nor OpenGraph/meta tags detected across 1 assessed pages (1 JS-rendered). Investigated: docs 0%.
- [skip] Machine-readable errors (RFC 9457) — No surface produced evidence for this capability in this run.
- [skip] Operation purpose clarity — No surface produced evidence for this capability in this run.
- [skip] Description consistency across surfaces — Only 1 surface description(s) with ≥6 tokens available; need at least 2 to compare.

### Agent Usability

- [fail] Runnable collection with test scripts — No public Postman workspace discovered for the org. Investigated: platform 0%.
- [skip] Idempotency documented — No surface produced evidence for this capability in this run.
- [skip] Rate-limit signaling — No surface produced evidence for this capability in this run.
- [skip] Pagination documented & consistent — No surface produced evidence for this capability in this run.
- [skip] Sandbox separation — No surface produced evidence for this capability in this run.

## Executive Summary

Apryse's API program shows strength in documentation reachability and discovery, but partners and their AI agents face significant friction in two critical areas: the API contract itself lacks the security definitions and worked examples needed to build against confidently, and the overall onboarding experience — missing a self-service portal, inline code samples, and runnable collections — means partners cannot get hands-on without a sales conversation. Prioritize hardening the API contract and standing up a self-serve, executable front door first; then close the agent-readiness gaps (agent instructions, structured metadata, and error context) so AI-assisted integrations can proceed without guesswork.