AI Orchestration for Smart Cities and the Enterprise with Robin Braun and Luke Norris - #755
Episode
54 min
Read time
2 min
Topics
Productivity, Remote Work, Leadership
AI-Generated Summary
Key Takeaways
- ✓Back-office automation priority: Fortune 500 companies and municipalities achieve fastest ROI by automating finance, HR, and procurement workflows first rather than customer-facing chatbots, enabling overnight efficiency gains before pursuing advanced use cases that demonstrate tangible value to stakeholders and boards.
- ✓Five zero eight compliance automation: Kamiwaza's agents process millions of tokens to remediate website accessibility violations by analyzing PDFs, images, and HTML code, achieving 90% technical compliance on first pass using visual language models and computer use agents running on private NVIDIA RTX 6000 infrastructure.
- ✓Data readiness paradigm shift: Visual language models now achieve 99% accuracy extracting data from unstructured sources like microfiche and handwritten documents, eliminating the need for data cleansing before AI implementation. Organizations can start processing legacy data immediately rather than spending months on preparation.
- ✓Distributed inferencing economics: Running AI workflows on private infrastructure becomes cost-effective within three to four months for heavy processing workloads, enabling unlimited token usage for recursive agent operations that require thousands of data pull requests per workflow without cloud API constraints or escalating costs.
What It Covers
Robin Braun from HPE and Luke Norris from Kamiwaza discuss deploying AI orchestration for smart city operations in Vail, Colorado, focusing on back-office automation, website accessibility compliance, and deed restriction management using private infrastructure.
Key Questions Answered
- •Back-office automation priority: Fortune 500 companies and municipalities achieve fastest ROI by automating finance, HR, and procurement workflows first rather than customer-facing chatbots, enabling overnight efficiency gains before pursuing advanced use cases that demonstrate tangible value to stakeholders and boards.
- •Five zero eight compliance automation: Kamiwaza's agents process millions of tokens to remediate website accessibility violations by analyzing PDFs, images, and HTML code, achieving 90% technical compliance on first pass using visual language models and computer use agents running on private NVIDIA RTX 6000 infrastructure.
- •Data readiness paradigm shift: Visual language models now achieve 99% accuracy extracting data from unstructured sources like microfiche and handwritten documents, eliminating the need for data cleansing before AI implementation. Organizations can start processing legacy data immediately rather than spending months on preparation.
- •Distributed inferencing economics: Running AI workflows on private infrastructure becomes cost-effective within three to four months for heavy processing workloads, enabling unlimited token usage for recursive agent operations that require thousands of data pull requests per workflow without cloud API constraints or escalating costs.
Notable Moment
Luke Norris argues chatbots represent the worst application of AI capabilities, forcing PhD-level intelligence that processes thousands of tokens per second to communicate at human typing speed of 20 tokens per second instead of automating complex backend workflows.
Episode Transcript
It is just my pet peeve, but I think the chatbot was almost the worst thing to happen to AI, like, period. What we're actually finding at mass adoption, whether it's the town of Vale or it's Fortune five hundred's is back office automation. The normal enterprise looks so similar at the finance area, looks so similar at the HR area, looks so similar at procurement. And generative AI can just knock all of that down literally almost overnight. You get those ROIs, and then you go on to the sexy of new use cases. Alright, everyone. Welcome to another episode of the TwiML AI podcast. I am your host, Sam Charrington. Today, I'm joined by Robin Braun, VP of AI business development for hybrid cloud at HPE, and Luke Norris, cofounder and CEO at Kamiwaza. Robin's been leading HPE efforts to build out its unleashed AI ecosystem with the goal of enabling partners to take advantage of the company's infrastructure to deliver enterprise AI solutions. Luke's company is one of those partners. Kamiwaza offers an AI orchestration platform that connects enterprise data and systems with LLMs and agents. Before we get going, be sure to take a moment to hit that subscribe button wherever you're listening to today's show. Robin and Luke, welcome to the podcast. Thanks for having us. I'm really looking forward to digging into our conversation. You've both been working on some really interesting projects together, including a new AgenTic smart city deployment in Vail, Colorado that we'll be discussing a little bit later on. Before we dive into the details though, it feels like we're at a little bit of a moment where every company is trying to figure out how to connect AI more deeply into their operations. And the two of you have been right in the middle of this. Curious how you're both thinking about this wave of enterprise AI adoption right now. What's the mood and the conversations you're having? Luke, we'll let you jump in first. Well, thanks. And once again, excited to be here. So, I think the beginning of the year, it was an AI mandate, AI washer, AI do anything. I think it was coming down from boards, it was coming down from external, pressures. And now I think it's turned very sharply to AI ROI. You have to have this sort of return on investment. The investment dollars are there, and everyone's excited to put them in, but you have to be able to show some actual tangible reason for it. You have to take that baby step, and then you could take larger and larger and larger steps faster and faster. And I think we're right at that inflection where people are getting that first baby step then. They're starting to actually see maybe that first ROI, and they're willing to take the next large step. And, Robin, how does that resonate with what you're seeing? I completely agree. I think that there there were …
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