The Stack — MarTech & Revenue Operations Insights

Expert insights on MarTech modernization, revenue operations, AI-powered GTM strategy, and enterprise data strategy from The Katalor Group.

• Small Business Focus: Where AI Actually Helps (and Where It Just Creates More Work)

  Practical ways small teams can use AI to save time, reduce busywork, and keep workflows simple without overhauling how the business runs.

• From AI Pilots to AI Strategy: Creating a Long-Term Roadmap

  Learn how organizations move from isolated AI pilots to a long-term AI strategy that delivers sustainable business value.

• Building an Internal AI Center of Excellence: How Organizations Scale AI Successfully

  Learn how organizations build an AI Center of Excellence to scale AI initiatives, align teams, and turn AI pilots into real operational impact.

• AI Governance: Managing Risk, Compliance, and Responsible AI

  Learn how mid-market organizations can implement practical AI governance to manage risk, compliance, bias, and accountability in production AI systems.

• AI Readiness Assessment for Mid‑Market: A Practical Framework

  Before investing in AI, assess your readiness. Use this practical framework to evaluate data, infrastructure, and governance for successful AI projects.

• AI Integration: Connecting Models to Real Business Systems

  Learn how to integrate AI models with CRM, ERP, and operational systems so AI insights actually drive real business decisions.

• AI Model Monitoring: Save The Drift For Vacation

  AI models often fail after deployment due to model drift, data changes, and lack of monitoring. Learn practical strategies for monitoring AI systems in pro

• AI Cost Control on AWS: How to Avoid the $50K Experiment

  Learn practical strategies to control AI infrastructure costs on AWS, including GPU optimization, spot instances, training efficiency, and monitoring for A

• The AI Infrastructure Stack on AWS: What You Actually Need (And What You Don’t)

  Understand the essential AWS services required for AI infrastructure and avoid unnecessary complexity when building machine learning systems in the cloud.

• Securing AI Workloads in AWS: The Practical Guide

  Learn how to secure AI workloads in AWS, including data protection, model security, access control, and compliance practices for production AI systems.

• Why Your AWS Setup Is Sabotaging AI Deployment (And How to Fix It)

  Many AI initiatives fail because cloud infrastructure wasn't designed for AI workloads. Learn the AWS architecture patterns that support scalable AI deploy

• The Three Hidden Barriers to AI Value (That No Vendor Tells You About)

  Learn the 3 most common barriers to AI success & how to overcome them for real value. Discover practical steps to ensure your initiatives deliver results.

• From AI Hype to AI Value:  Practical AI Implementation Guide

  Up to 95% of AI pilots never reach production. Learn the five reasons AI initiatives fail and what successful mid‑market companies do differently.