Launched this week

CRM Health Doctor — Agent Readiness

Launched this week

Know what your CRM evidence actually justifies automating

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Know what your CRM evidence actually justifies automating

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CRM Health Doctor combines deterministic CRM health checks with GPT-6 Astra to assess what AI agents can safely rely on. It distinguishes what is viable, conditional, unsupported, or still unknown — while keeping every conclusion tied to supplied evidence and human review in control.

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Launch tags:Artificial Intelligence•CRM•Marketing automation

Launch Team / Built With

ClarifyThe autonomous CRM that helps you sell more

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OpenAI

GPT-6 Astra Challenge

How did Astra change the scope or ambition of what you built?

Maker

CRM Health Doctor began as a deterministic, read-only CRM diagnostic: identify data-quality issues, prioritize them, and provide traceable remediation guidance. GPT-6 Astra expanded the ambition from “what is wrong with this CRM?” to “what does this evidence actually justify automating?” We built an Agent Readiness layer that reasons over deterministic findings and distinguishes what is viable, conditional, unsupported, or still unknown. During adversarial testing, we found that valid citations alone do not prove that evidence supports a model’s claim, so we added evidence-support validation, score admissibility rules, explicit evidence gaps, and human review as the final authority. Astra turned the project from a CRM health checker into a governed pre-agent readiness system.

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1d ago

Maker

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I built CRM Health Doctor after seeing a recurring gap: companies are moving quickly toward AI agents, but clean-looking CRM data does not prove that an organization is ready for autonomous decisions. This Agent Readiness Edition starts with deterministic, read-only CRM checks and passes structured evidence to GPT-6 Astra. Astra then evaluates what that evidence actually justifies — what is viable, conditional, unsupported, or still unknown — while human review remains in control. One of the most valuable lessons came from adversarial testing: a model citing valid evidence does not necessarily mean that the evidence supports its claim. That led us to add separate evidence-support, traceability, and human-authority validation rather than treating citations alone as grounding. The current demo uses synthetic CRM records and preserved real GPT-6 Astra assessments. I’d especially value feedback on the core idea: could evidence-bounded readiness and governance become a useful layer between CRM data and production AI agents?

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1d ago

OpenAI

GPT-6 Astra Challenge

How did Astra change the scope or ambition of what you built?

Maker

Report

1d ago

Maker

📌

Report

1d ago