Agentix intelligence
Field notes for teams putting AI to work. Production patterns, governance controls, and practical automation playbooks.
Build an account research agent that gives sellers timely, cited briefs while protecting CRM data quality, controlling costs, and keeping humans in control.
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Learn how to design a governed next-best-action journey with CRM context, eligibility rules, human approvals, measurement, and a phased rollout.
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Use this practical audit to assess content quality, permissions, retrieval, governance, and cost before deploying reliable enterprise AI agents.
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Build a governed CRM data enrichment loop with source rules, confidence thresholds, human review, monitoring, and a practical 30-day RevOps pilot.
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Build a governed CRM data enrichment loop that detects stale records, resolves conflicting evidence, controls writeback, and improves data quality over time.
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Build a production RAG control loop for retrieval quality, permissions, freshness, observability, safe fallbacks, and cost per useful answer.
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Build sales follow-up automation with reliable CRM state, event triggers, approval gates, stop rules, and a practical RevOps pilot scorecard.
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Build reliable agent handoffs with explicit context, ownership, permissions, acceptance rules, recovery paths, and end-to-end traces for production AI.
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Learn a seven-step framework for building tool-using AI agents with scoped permissions, approval gates, safe retries, observability, and clear escalation.
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A practical playbook for platform teams to control multi-agent handoffs, budgets, observability, failure recovery, and production promotion.
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