Agentix intelligence
Field notes for teams putting AI to work. Production patterns, governance controls, and practical automation playbooks.
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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Build AI agent memory that stays relevant across sessions with clear storage tiers, write gates, retrieval controls, governance, and production metrics.
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