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Obsilient vs Rulebook

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Obsilient compared with Rulebook
DetailObsilient logo ObsilientRulebook logo Rulebook
What it doesReliability monitoring for autonomous agent systems Take your AI support bot from 4/10 to 10/10
StageNot given MVP
FoundedNot given 2026
Based inNot given Not given
Pricing modelPaid Free trial
PricingFixed-fee pilot of about a month credited against the first year if continuing. Annual subscription after pilot in three tiers: Map, Gate, or Continuous. Free during beta. After beta: $29/month (your own AI keys, unlimited runs) or $59/month (AI included, 50 runs/month).
Key features
  • Detects agents built but never connected
  • Identifies work that silently stops between agents
  • Catches judges that grade incorrectly
  • Prevents changes shipping past broken tests
  • Detects identity and data drift
  • Measures self-repair behavior
  • Works with any model and framework
  • Read-only connector with no system changes
  • Deployment pipeline gate with pass/fail status
  • Encrypted data transmission and on-premises options
  • Bot Score: rates bot performance across five dimensions (rules, facts, solutions, tone, trick resistance)
  • Break my bot: 15 adversarial customer scenarios test for vulnerabilities
  • Fix it for me: automatically rewrites rule sheet and tests against saved situations
  • Train my bot: 30-minute automated training on weak spots with test validation
  • GitHub integration: sends improvements as pull requests for engineer approval
  • Real chat analysis: identifies problems in actual customer conversations with privacy masking
  • Knowledge check: validates bot replies against FAQ and policy documents
  • AI comparison: test bot performance across Claude, ChatGPT, and Gemini with costs and speed
  • Open source engine: public GitHub implementation of scoring and testing algorithms
What makes it different
  • Finds failures that never raise an alarm
  • Built and proven on real production systems, not theory
  • Read-only connector never changes your system
  • Works with any model without depending on model vendor
  • First findings within a week of pilot start
  • Nothing ships without engineer approval: all changes go through GitHub pull request review
  • Privacy by default: customer data anonymized, keys encrypted, uploads not stored
  • Open source testing engine: full algorithm transparency available on GitHub
  • Works with your existing AI: supports Claude, ChatGPT, and Gemini with user's own keys
  • Unified team experience: one plan covers support, product, and engineering roles
Community votes00
DR (Domain Rating by Ahrefs)Not checked yet no change since last checkNot checked yet no change since last check
Trust Flow (Majestic)00
Citation Flow (Majestic)00
Referring domains (Majestic)00

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