The Union

An executive asked if Krista would favor his competitor. That question tells you everything about where the market actually is. Scott and John unpack the massive gap between AI vendor assumptions and enterprise buyer reality, with real customer stories that reveal how dangerous that gap can be.

What you'll learn:

• Why the median enterprise buyer scores 10 to 20 out of 100 on AI literacy
• The customer story that shows what "AI will learn from your people" actually means in practice
• Why tenant isolation matters and how to explain it in plain language
• The single best question to ask any AI vendor before signing a contract
• Why the AI industry is the biggest source of buyer confusion

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Meeting note takers flood your inbox and bury knowledge in silos. An enterprise brain does the opposite. It connects meetings, email, chat, tickets, and systems of record into one shared memory that remembers, reasons, and acts.

In this episode of the Union Podcast, Scott King, John Michelsen, and Chris Kraus break down why understanding is the prerequisite for any agentic AI strategy, why summaries are spam, and how one customer made Krista the brain of their entire business. They cover layered access, real-time system connection, privacy discipline, and an 80-page investment thesis built from thousands of internal meetings.

Learn where to start, how long it takes, and why action, not another inbox, is the real ROI.

Build the understanding your business can act on: https://krista.ai

1. Why the enterprise brain matters
2. Tribal knowledge and the visibility gap
3. Why meeting summaries are spam
4. Siloed note takers and recording risk
5. Beyond meetings: emails, chat, systems of record
6. The 80-page investment thesis
7. Privacy and access policies
8. Where to start and how long it takes
9. The real ROI is action

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Are you treating your AI strategy like a popularity contest? In this episode, we break down our latest research on 28 LLMs and explain why "celebrity" models are often a liability for the Cognitive Enterprise.

Key Learnings:

• The ROI Trap: Why using a trillion-parameter model for menial data extraction is killing your budget.
• The API Burden: How to avoid the massive development cycles triggered by model deprecation.
• Dynamic Orchestration: Using Krista to select models based on speed, accuracy, cost, and risk in real-time.

Continuous Learning: Why GenAI alone can't learn your business, and why you need a platform that does.

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In this episode, Scott, John, and Chris explain what it takes to build a cognitive enterprise—a business with memory, reasoning, and action. We reject the idea of adding AI for AI’s sake. Instead, we show you how to create an organizational brain that weaves systems, humans, and models into a unified, intelligent whole.

 🔍 What you'll learn:

• Why AI initiatives often fail and how to avoid fragmentation
• The three core functions your organization must master: memory, reasoning, and action
• A step-by-step approach to build cognitive capability, starting small and scaling smart
• How to platform AI agents so they share memory and
  context
• Real-world business implications, from operations to approvals
• Why “technology should be invoking us, not the other way around” 

🎯 Who this is for:

• VPs of IT, CIOs, digital transformation leaders, AI architects, growth executives — anyone tasked with making AI meaningful rather than simply busy.

👉 If you’re tired of isolated AI pilots and ready to think with AI instead of chasing hype, this episode is for you.

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A recent MIT report found that only 5 percent of generative AI projects deliver measurable ROI. The rest collapse under complexity, lack of memory, and poor alignment with business outcomes. 

In this podcast, we break down why companies often struggle with AI adoption and what leaders can do to succeed. You’ll learn: 

- Why personal productivity with GenAI tools doesn’t translate to enterprise success 
- The risks of shadow IT and siloed deployments 
- Why building your own AI platform rarely works 
- How companies can leverage their agility to find early wins 
- The role of agentic platforms in scaling AI across the enterprise 
- A real-world case study from Doc Prep 911 showing measurable ROI 

If you are an executive looking to cross the GenAI divide and unlock real value, this video provides a practical playbook. 

👉 Read the full article here: https://krista.ai/crossing-the-genai-divide-and-unlocking-real-value
 👉 Learn more about how Krista helps enterprises adopt AI: https://krista.ai

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Scott King, John Michelsen, and Chris Kraus discuss key insights from the report Choosing the Right Agentic Platform. They break down what separates true agentic platforms from chatbot tools and task bots that create more fragmentation than value. Learn why orchestration, integration, machine learning, and built-in enterprise features are essential for sustainable AI adoption. See how Krista enables organizations to run complex, cross-functional workflows with AI, people, and systems working together at machine speed.

Download the full report here: https://krista.ai/choosing-the-right-agentic-platform/

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Most business leaders say they don’t want AI training on their data—but what they really mean is they don’t want to lose control. In this episode, we explain why the only way AI delivers real value is by learning your business: your documents, your processes, your language, and your priorities.

We break down the difference between exposing data and improving outcomes, and why generic AI won't scale. You’ll hear how AI that understands your workflows can anticipate needs, suggest actions, and drive results—without writing endless prompts or building from scratch.

If you’re still treating AI like a tool that needs babysitting, it’s time to rethink the strategy.

Topics covered:

• Why blocking AI from learning limits your ROI
• The risks of generic intelligence in enterprise settings
• How to train AI like you train your people
• Real-world examples of AI reinforcing strategy by learning context

Learn how to make AI work for your business—starting with your data.

Listen now and subscribe for more episodes on making AI work in the enterprise.

#AI #EnterpriseAI #Automation #BusinessIntelligence #AgenticPlatforms #AITraining #LLM #ProcessAutomation #DigitalTransformation

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Tired of meeting recordings that lead nowhere? We explore why summaries and tasks aren’t enough for operations executives seeking real enterprise knowledge. It’s more than recordings—it’s about weaving in emails, Teams chats, CRM data, and documents for a complete picture. Learn how orchestration transforms these insights into automated workflows, boosting efficiency and outcomes. From tackling customer churn with full context to unifying data with Krista, this episode shows how to turn meetings into a strategic asset.  

 Key Takeaways:  

• Recordings alone don’t cut it—context is king  
• Enterprise data (emails, chats, CRM) powers smarter decisions  
• Orchestration automates action from unified knowledge

Want to elevate your meetings? Check out Krista’s conversation agents, AI-led knowledge management, and orchestration at https://krista.ai/solutions/conversation-agent/.

Subscribe for more tips on turning data into results!  

#EnterpriseKnowledge #MeetingAutomation #Orchestration #AI #BusinessStrategy  

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In this episode, we break down the Model Context Protocol (MCP) — what it is, how it works, and why it’s generating so much hype in the AI world.

But beyond the headlines, we explore the real enterprise implications. Is MCP secure? Can it be trusted to connect large language models to your internal systems? And what risks are developers and businesses ignoring in the rush to experiment?

We draw parallels to past tech missteps (remember ActiveX?) and share firsthand insights from our own use of MCP tools.

If you're leading AI strategy, running IT, or just trying to understand where this is all headed — this is the conversation you don’t want to miss.

👉 Subscribe for more deep dives on AI, automation, and enterprise tech.

#MCP #AIintegration #EnterpriseAI #LLM

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Should AI agents really cost $20,000 per month? In this episode, we break down OpenAI’s reported pricing for specialized AI agents and why many companies will try (and fail) to build their own.

🔍 What’s Inside:

✅ The hidden costs of DIY AI—why it’s not just about training a model
✅ Why most AI agents fail without orchestration, security, and integration
✅ How businesses get trapped in an endless cycle of building, fixing, and rebuilding
✅ Why a platform approach is the key to deploying AI agents faster and at lower costs

💡 Instead of sinking millions into fragmented AI projects, companies need a smarter way to assemble, orchestrate, and scale AI agents. Krista is that platform.

📌 Subscribe for more insights on AI and automation!
📩 Want to learn more? Visit Krista.ai for smarter AI deployment.

#AI #Automation #ArtificialIntelligence #AIAgents #BusinessTech

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