AvaroLabs
Independent Research Lab · AI Infrastructure

The raw data behind AI agent platforms

Avaro Labs audits automation orchestrators and AI agent infrastructure against a fixed 15-point matrix: true cost at scale, undocumented API limits, security posture, reversibility. No opinions — measurements.

LAST VERIFIED · JUL 4, 2026 PROTOCOL · 15-POINT MATRIX FUNDING · AFFILIATE, DISCLOSED

Infrastructure comparisons

Orchestrators · 2026

Make vs n8n

Credit vs execution billing, native LLM agents, RAG, TCO at 100,000 tasks/month, reversibility. Verdict by team profile.

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Our methodology

Sandbox accounts, 10,000-request stress tests, TCO modeling, verified certifications, exclusion criteria.

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What we measure

CategoryAudit points
EconomicsReal billing unit, B2B entry cost, 100,000 tasks/month benchmark, hidden rate limits
AI engineLLM agnosticism, memory & RAG (vector stores), multi-agent orchestration
ConnectivityNative B2B connectors, real-time webhooks, custom Python/Node.js code injection
InfrastructureCloud / VPC / self-hosted options, audited certifications (SOC 2 Type II, GDPR), resilience
Strategic riskLearning curve, vendor lock-in, workflow exportability

Any figure we cannot verify through testing or official vendor documentation is flagged [UNVERIFIED] and excluded from scoring. Full protocol →