"Cloud vs. edge" is outdated
The future is cloud + edge.
Real‑time decisions run at the device; heavy training/analytics stay in the cloud.
That means: lower latency, stronger privacy, less bandwidth, better resilience.
Rethink the "send everything upstream" reflex.
💬 Let's talk edge‑centric AI strategy → https://bio.site/dougortiz
What's the ROI of relational AI? Enterprises see $4-7M annual returns: 40% faster opportunity ID, 50% risk reduction, 30% better decisions. Cost of inaction: $12.3M annually in hidden costs.
AI by business goals: Predictive first.
85% ROI from forecasting, churn, pricing.
Retail freed 22% capital. Mfg cut 37% downtime.
Wrong order = 70% budget waste.
P&L → Predictive → Scale.
💬 Roadmap → https://bio.site/dougortiz
AI spectrum: Co-pilot vs Autopilot
CO-PILOT: AI suggests, human decides
• Legal, HR, brand, customer escalations
AUTOPILOT: AI decides and acts
• Spam, alerts, replenishment, routing
Decide by function. Make it your governance framework.
Is your enterprise AI missing the connections that matter? Traditional RAG finds documents but can't trace relationships. Knowledge graphs bridge this gap, cutting compliance risk by 60% and review cycles by 40%. This isn't optional—it's competitive necessity.
95% of enterprise AI projects fail due to 5 preventable mistakes.
70% of failures caused by the same patterns.
Average failure costs $2M per project.
Companies waste 18 months on failed initiatives.
Winning companies avoid failure traps, not just build better models.
🔗 Full Video: https://youtu.be/oJuWcOITEIg
#AI #FailureRates #EnterpriseAI #dougortiz #Risk #TechStrategy #EnterpriseTechnology
Two kinds of AI most executives confuse:
DISCRIMINATIVE = Labels and predicts
• "Is this spam?"
• "Which segment?"
• Multiple choice
GENERATIVE = Creates new content
• "Draft a reply"
• "Summarize this"
• Essay question
Match the AI type to the problem.
Fragmented AI systems cost 40% more in development time.
LangChain's unified ecosystem integrates 50+ LLM providers and 100+ tools, cutting AI app development by 60% and reducing maintenance costs by 45%.
Provider flexibility means 30% cost optimization.
Production-ready RAG implementation drops from months to weeks.
#LangChain #AgenticAI #EnterpriseAI #dougortiz
▶ Video: https://youtu.be/a13L7RaDIhA
Generative AI vs. Predictive AI: The ROI Reality Check.
The tech world is buzzing about GenAI, but the stats reveal a gap between experimentation and production.
📉 Generative AI Reality:
65% of pilots fail to scale.
High compute costs and compliance hurdles.
📈 Predictive AI Advantage:
Proven 3x to 5x ROI.
Lower TCO and ready for enterprise deployment.
Sector Wins for Predictive AI:
Is your enterprise AI missing the connections that matter?
Traditional RAG finds documents but can't trace relationships. Knowledge graphs bridge this gap, cutting compliance risk by 60% and review cycles by 40%.
This isn't optional—it's competitive necessity.