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Nango Human-Dependent

AUDIE Score: 63/100 · Audited 2026-04-15 · Website: https://nango.dev · Machine-readable: JSON

Pillar Scores

P1 Signal Architecture — 19/25
P2 Clarity Stack — 15/25
P3 Trust Envelope — 12/20
P4 Velocity Triggers — 7/10
P5 Gravity Design — 10/20

Executive Summary

Nango lands at 63/100 (Human-Dependent, just 2 points shy of Emerging) — the closest thing to agent-ready in the integration platform category. The pricing clarity is exceptional, the free tier removes human friction at activation, and the public status page with real incident data is a model for verifiable trust. The gaps are structural: ToS allows changes without notice (a hard stop for autonomous procurement), there are no fallback rules for agents navigating degraded integrations, and the lack of an agent memory layer leaves significant gravity potential unrealized. Three low-effort fixes — schema.org pricing markup, structured fallback rules, and a minimum ToS notice period — could push Nango into the Emerging tier within a sprint.

Strongest Signals

Critical Gaps

Priority Actions

  1. Add schema.org Offer markup to pricing page — +2 pts · P1 · Effort: Low
  2. Publish agent-legible fallback/substitution rules — +3 pts · P2 · Effort: Low
  3. Establish a minimum API change notice period in ToS — +2 pts · P3 · Effort: Low
  4. Build an agent memory / session context layer — +3 pts · P5 · Effort: High
  5. Publish a machine-accessible compound value signal — +2 pts · P5 · Effort: Med

All 20 Criteria

P1-A Structured Data — 3/5
robots.txt explicitly allows all major AI crawlers (GPTBot, ClaudeBot, anthropic-ai, PerplexityBot, Amazonbot, ChatGPT-User). Google Analytics/GTM present. No rich schema.org Offer/Product/AggregateRating markup found on homepage or pricing page.
P1-B Machine-Readable Pricing — 4/5
Pricing page is exceptionally detailed: four tiers with exact prices ($0, $50/mo, $500/mo, custom), per-unit overage costs ($0.0001/extra request, $0.0000002/ms compute, $0.00001/extra log), and precise per-tier limits for 7 distinct dimensions. Highly parseable from HTML; not encoded in schema.org/Offer but among the best plain-HTML pricing clarity observed.
P1-C llms.txt / Agent Layer — 4/5
docs.nango.dev/llms.txt confirmed present and referenced in API documentation responses. Provides structured index of 700+ integration docs for LLM consumption. Not at root domain but docs subdomain llms.txt is a clear agent-facing signal.
P1-D API / MCP Availability — 4/5
Built-in MCP server for agent integration. Compatible with LangChain, Claude Code, Cursor, and MCP SDKs. TypeScript-first SDK. 700+ pre-built integrations accessible via standardized tool calls. Full REST API with docs. OpenAPI spec availability unconfirmed from public pages.
P1-E Discoverability (GEO) — 4/5
Explicit AI crawler allowance in robots.txt (named list), docs llms.txt, 7k+ GitHub stars driving organic AI retrieval signals, G2 listing, active engineering blog.
P2-A Offer Completeness — 4/5
Single pricing page contains all four tiers with prices, per-unit overage rates, and feature lists. Free tier makes entry-point evaluation trivial. Near machine-parseable from one URL. Enterprise custom pricing is the only gap.
P2-B Scope & Limits — 4/5
Per-tier limits stated precisely for: API auth connections (10/20/100/unlimited), proxy requests (100k/200k/1M/unlimited), compute hours (10/20/100/unlimited), function runs, custom logs, sync storage records, and API webhooks — all with exact overage costs. Explicit and structured; not in schema.org format but highly machine-readable.
P2-C Substitution Rules — 1/5
No agent-legible fallback or substitution rules found. Status page exists and shows incident history, but no documented behavior for agents when an API integration is degraded or rate-limited.
P2-D Conditional Logic Transparency — 3/5
Free, Starter, and Growth tiers fully disclosed with all conditions on the pricing page. Enterprise requires custom pricing contact. RBAC, SAML SSO, HIPAA, and self-hosting gated to Enterprise. Conditions mostly transparent for lower tiers.
P2-E Semantic Precision — 3/5
Strong technical precision on infrastructure metrics ("sub-100ms execution latency," "99.9% uptime SLA," "OpenTelemetry observability," "per-tenant isolation"). Some marketing language ("Build integrations with AI") but overall high semantic quality.
P3-A Verifiable Performance Data — 4/5
Public status page at status.nango.dev with 90-day uptime history. Two incidents documented in Q1 2026 with full timeline (April 11–12: webhook flood ~8 hours; March 4: functions degraded ~70 min). 99.9% uptime SLA stated on homepage. G2 reviews positive. SOC 2 Type II certified.
P3-B Scoped Permissions — 3/5
RBAC available in Growth and Enterprise tiers. Per-tenant isolation architecture. Bearer token authentication via environment-scoped secret keys. No explicit "agent-scoped" time-bounded or action-bounded permission model found; RBAC is human-team oriented.
P3-C Audit Trail — 3/5
OpenTelemetry export available (Growth+). Per-tier custom log quotas (100k to 1M+). Infrastructure processes "billions of API requests" with observability built-in. No dedicated machine-accessible audit log API specifically designed for agent systems found.
P3-D Behavioral Consistency — 2/5
Status page and changelog exist. Auto-renewal documented in ToS. However, ToS allows service modification or discontinuation "at any time without notice" — only a pro-rata refund is guaranteed on material change. No API versioning commitment or minimum notice period published.
P4-A Friction-Free Activation — 4/5
Free tier at $0 requires no credit card (not stated but implied by self-serve model and free tier existence). Paid plans self-serve starting at $50/month with no sales gating mentioned. Strong self-serve activation signal. No explicit "API key in 60 seconds" guarantee found but free tier + no-sales-touch is near best practice.
P4-B Agent Decision Signals — 3/5
Free tier with hard limits (10 connections, 100k requests) creates clear, agent-legible upgrade triggers. Usage-based overages provide pricing signals for autonomous decision-making. No explicit agent-native decision documentation (e.g., "when you hit X, upgrade to Y") but the structure itself is agent-parseable.
P5-A Integration Depth — 4/5
700+ API integrations with custom TypeScript sync functions, checkpoint-based state management, tenant isolation, and CI/CD-deployed custom logic. Migrating would require rebuilding all custom syncs, auth configurations, and state checkpoints. Deep technical lock-in.
P5-B Agent Memory Layer — 2/5
Data syncs enable RAG use cases (mentioned explicitly). Connection tagging and attribution provide some account-level history. Checkpoint-based state management means sync state persists. But no dedicated agent memory layer — no per-agent context, preferences, or interaction history accessible to agents programmatically.
P5-C Programmatic Renewal — 2/5
Auto-renewal documented in ToS ("auto-renewal on the same terms"). Usage-based billing creates natural renewal signals. No agent-accessible renewal API or programmatic subscription management endpoint found.
P5-D Compounding Value Signal — 2/5
Integration value grows as more syncs, custom functions, and connection state accumulate. But no agent-readable signal exposes this compounding value — agents cannot query "how much state/value has been built here" to evaluate switching cost.

Rubric v1 (April 2026). Scores reflect the company's state on the audit date and may have improved since.