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Missed calls cost more than you think, especially when leads come in after hours or demand spikes without warning. From the Enterprise Connect show floor, we sit down with https://www.girikon.com and their product and innovation leaders to unpack how AI-first customer engagement is changing the way contact centers and sales teams respond in real time.

We talk through Girikon’s path from a decade of CRM onboarding and consulting into Girikon AI, including Girik Connect, a unified customer engagement platform that brings telephony, two-way messaging, and chat under one roof. The big promise is practical: stay CRM-agnostic so teams can keep Salesforce, HubSpot, Dynamics, or ServiceNow as the system of record while still connecting every conversation across channels. We explore what it looks like to deploy AI voice agents, AI message agents, and AI chat agents as the first touchpoint, so inbound callers get help fast and sales gets qualified opportunities instead of a messy backlog.

Then we get specific about enterprise realities: legacy integrations, multiple platforms, and the need to map conversation history back into the CRM with actionable insights. Think call takeaways, meeting notes, next steps, lead scoring signals, and case trends that reveal the true root cause behind hundreds of support tickets. We also dig into rollout timelines, native integrations, and open APIs, plus the hard parts of making LLMs work on real calls with noise, accents, multilingual speakers, and the risk of hallucinations.

If you care about AI customer experience, contact center automation, CRM integration, and faster speed-to-lead, this one is for you. Subscribe, share with your team, and leave a review with the AI use case you want to automate next.
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Meetings create the most valuable raw material in a company: the ideas people say out loud. The problem is that those ideas usually evaporate into scattered notes, half-remembered decisions, and action items no one can trace. From the floor of Enterprise Connect, we sit down with Zoom Chief Product Officer Jeff Smith to unpack how Zoom is trying to close that gap by turning conversation into completed work.

Jeff explains why transcription is only the starting point and how “My Notes” is designed to capture interactions across platforms, building a durable repository that feels like perfect recall. We get into the less-hyped but crucial AI work that makes outputs reliable, like noise reduction, voice understanding, and meeting-room identity so tasks go to people instead of “Conference Room One.” Then we zoom out to the big product bet: AI canvases. With Zoom Docs as a text surface and new AI Slides and AI Sheets, AI Companion can translate what you discussed into a project plan, a deck, or a spreadsheet without the blank-page grind.

We also explore how customer obsession shapes the AI roadmap, how a unified data layer connects customer experience, revenue, and support insights, and why healthcare could be a breakout use case for AI workflow automation, better clinician preparation, and more focused patient conversations. If you care about AI productivity, meeting intelligence, knowledge management, and practical enterprise AI, this is a clear look at where collaboration software is going next.

Subscribe for more conversations like this, share this with a teammate who lives in meetings, and leave a review with your take: what should AI automate first in your daily workflow?
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Your contact center already tells you what’s happening. The harder question is why and what you should do next. From the Enterprise Connect floor, we sit down with Ray Bohoac CEO of Spearfish.ai to unpack a practical approach to contextual intelligence that connects customer conversations to the back-office data that actually explains outcomes.

We get specific about how Spearfish moves teams beyond classic contact center KPIs like service level, QA, and CSAT, using a “signals” architecture that learns from calls and correlates them with systems like ERP, sales, and operational data. Ray shares a standout customer story: an apparel brand hears repeated complaints about a shoe wearing out, then traces those calls to the exact product and lot number, tracks the issue into the supply chain, and gets proactive with customers before the problem snowballs. That’s root cause analysis built for speed, not a report you read a month later.

We also talk about reality: multi-vendor environments, legacy tech, and a market crowded with agentic AI companies. The big takeaway is the feedback loop. When AI and humans do more work automatically, you still need a way to measure what changed, what worked, and what needs adjusting in real time across support, operations, training, and marketing. Ray also highlights expansion into non-traditional “contact center” settings like 211 organizations, proving the same foundation can drive mission-critical outcomes.

Subscribe for more conversations on contact center innovation, customer experience analytics, and applied AI, then share this episode and leave a review. What back-office data would you connect to customer calls first?
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A single customer call can reveal why people churn, what drives complaints, and where sales get stuck, but only if you can actually see the patterns. On the Enterprise Connect show floor, we sit down with John from MiaRec to unpack how AI-powered conversation analytics turns everyday contact center recordings into clear actions you can take the same day.

We get specific about the biggest wins: automated QA that replaces slow manual scoring, customer experience intelligence that infers CSAT and NPS without relying on biased surveys, and churn-risk detection that can alert a retention team the moment a caller is truly unhappy. John explains how this “visibility first” approach helps teams protect revenue by catching problems early, while also improving coaching and consistency across agents.

Then we move into revenue intelligence for sales conversations: spotting buying intent, understanding how reps handle objections, and finding missed opportunities that quietly drain conversions. We also talk deployment realities in complex environments, including cloud integrations with popular CCaaS and UCaaS platforms like RingCentral and Twilio, plus what onboarding and configuration can look like.

The most exciting part is what’s new: Ask AI, a chat-style way to query large datasets and uncover trends across negative calls in seconds, and Zapier-powered workflows that can summarize a call, draft a personalized follow-up email, and automate next steps to improve CX and revenue outcomes. If you care about contact center AI, speech analytics, and practical automation, this one is built for you. Subscribe, share this with a teammate, and leave a review with your biggest takeaway.
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Cloud native doesn’t mean what it used to. What started as a self-service way to buy compute fast has turned into a full application platform transformation where Kubernetes, desired state, and automation decide how software scales, heals, and lands on compute, storage, and networking.

From Mobile World Congress in Barcelona, we sit down with Dilpreet from Broadcom’s VMware Cloud Foundation (VCF) organization to talk about what’s actually changing on the ground. We get into why Kubernetes has moved from a niche tool to a mainstream standard, and why that success brings a new set of problems: operational complexity, painful upgrades, lifecycle management, and the skills required to keep clusters stable over time. If your cloud native journey feels slower than the slide decks promised, this is the part you’ve been running into.

We also unpack VCF’s product strategy for simplifying the cloud consumption experience by bringing key capabilities together, including automation and multi-tenant cloud operations. Dilpreet explains how combining ARIA Automation with vCloud Director can create a more unified interface for enterprises and cloud service providers, then tying that experience more deeply to the underlying Kubernetes and infrastructure fabric. The aim is a Kubernetes-like workflow where you declare what you want and the platform does the heavy lifting.

Finally, we talk about a big shift we’re hearing from customers: they want that cloud experience on-prem. We connect that to telco modernization as networks move from VNFs to CNFs and the push toward modern telco cloud platforms announced at MWC. If you care about cloud native, Kubernetes operations, VMware Cloud Foundation, platform engineering, and what AI-era apps will demand next, this one is for you.

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