The Ravit Show

What happens when AI is applied to real mission problems, not just demos? At Data Driven 2026, I sat down with Lisa Wolff from ForeSite360 to talk about how they are using AI, together with Reltio, to solve complex challenges in highly regulated environments like the federal government.One example stood out immediately. A deployment of their platform, Foresight 360, built on top of Reltio, has already helped a government agency save more than $100M every year. That kind of impact only happens when the data foundation is right.Lisa made an important point during our conversation. AI only works when the context around the data is well understood and properly managed. Without that, even the most advanced models struggle to deliver meaningful outcomes.We also discussed how large organizations are moving away from slow, traditional data modernization approaches. The pace of change is accelerating quickly, and Lisa expects some major shifts in the next six months as enterprises adopt more agent-driven systems.What I also found interesting was how these ideas translate beyond government. Foresight is applying similar approaches to improve experiences for seniors interacting with public programs and even the guest journey in hospitality. The real power of AI shows up when it solves personal, real-world problems.It was a fascinating conversation about how AI, data context, and agent systems are starting to deliver real impact.hashtag#data hashtag#ai hashtag#datadriven hashtag#reltio hashtag#theravitshow

Everyone talks about AI agents. Very few talk about what they actually change inside enterprises. At the DataDriven Conference, Ravit Jain sat down with Rajeev Krishnan from PwC to unpack what the agentic shift really means for data, governance, and Master Data Management.PwC and Reltio have been working together for years, but the conversation is now moving beyond implementations to real business outcomes. Rajeev shared how their Agent OS ecosystem is being integrated with Reltio to deploy agents that handle tasks data teams have struggled with for years. Things like resolving match queues, auto-classifying records, and improving data quality without constant manual effort.What makes this important is simple. Enterprises already know they need trusted master data. The challenge has always been the operational burden required to maintain it. Agentic AI is starting to change that equation by reducing operational cost while strengthening the data foundation needed for AI-driven decisions.We also discussed what leaders are wrestling with in 2026. Two themes stood out.First, governance is no longer just about data. It is about governing data in the age of AI.Second, organizations are facing a real tension between using data to power AI and using AI to fix their data. The right path depends on the use case, not a one size fits all strategy.It was a grounded conversation about how enterprises are moving from AI experiments to operational impact.#data #ai #datadriven #reltio #theravitshow

AI agents are only as good as the data and context behind them. At DataDriven 2026, I caught up with Sushant Rai from Reltio to talk about their latest announcements and where they see enterprise AI heading next. The big theme was clear. Context is everything. Without trusted enterprise data grounding AI systems, outcomes fall short. That is exactly where Reltio is placing its bets with its Context Intelligence Platform and the evolution of Agent Flow.We talked about how Agent Flow is moving beyond experimentation into real execution. From out-of-the-box agents for governance and operations, to a new Agent Builder that lets teams create agents with simple prompting, the focus is on making agentic AI practical for enterprises. Trust was another major point. Susant emphasized the need for observability, transparency, and explainability so organizations understand what agents are doing and why. Without that, adoption stalls. Looking ahead, Reltio is investing heavily in unstructured data processing, agent-driven data quality, expanded zero-copy integrations, and stronger identity resolution to unify enterprise data at scale.The direction is clear. Enterprises are shifting from dashboards to intelligent systems powered by context-rich data.#data #ai #datadriven #reltio #theravitshow

AI will fail without strong data foundations. At the DataDriven Conference 2026 by Reltio, I sat down with Bronwen Schumacher from ZS to talk about what it really takes to make enterprise data ready for AI.Bronwen leads the Reltio partnership at ZS, a global consulting firm deeply rooted in life sciences and healthcare. ZS has been one of Reltio’s earliest partners, working together for 13 years to build modern Master Data Management solutions for global pharma companies.This year, they won Innovation Partner of the Year for their work integrating ZS’s platform, ZAIDYN, with Reltio. The goal is clear. Deliver an out-of-the-box data and analytics solution that helps organizations, including smaller pharmaceutical companies, master their data faster.We also spoke about what 2026 really demands from enterprises. The focus is shifting toward Agentic MDM, where strong data quality, governance, and change enablement become the backbone for AI. Without organizational buy-in and clean, trusted data, large-scale AI programs simply do not scale.Beyond pharma, ZS is also expanding into travel and hospitality, bringing similar data discipline to customer loyalty and experience use cases.This was a grounded conversation about how real enterprises are preparing their data before chasing AI.Sharing the full interview here.#data #ai #datadriven #reltio #theravitshow

Most companies think they are building data platforms. What they are actually building is the foundation for AI agents to make decisions!!!! At DataDriven 2026, I sat down with Manish Sood, Founder and CEO of Reltio, and our conversation made one thing clear: the role of data platforms is changing fast.Reltio just crossed $185M in ARR with strong growth, but the bigger story is how they are redefining master data management for the AI era. Instead of focusing only on data storage, they are pushing toward Context Intelligence, where AI systems operate on real-time, curated, and governed data.We discussed their new AgentFlow approach, where prebuilt AI agents automate stewardship work like match resolution, profiling, and data exploration. This moves data teams from manual cleanup to intelligent automation.We also talked about speed and access. Their Lightspeed data delivery network aims to make enterprise data globally available in milliseconds so customer-facing and agentic AI systems can actually function in real time.What stood out from customers at the event is simple:- The conversation is no longer about adopting AI- It is about whether their data foundation can support itSharing the full interview here where Manish breaks down the announcements, the strategy behind AgentFlow, and what enterprises should be preparing for next.#data #ai #datadriven #reltio #theravitshow

Most AI systems look impressive in controlled environments.But the real test begins when they meet production data.In my latest conversation, I sat down with Antonio Bustamante, Co-Founder and CEO of bem on The Ravit Show, to unpack one of the hardest problems in enterprise AI today: making unstructured data reliable enough to power real decisions.We talked about why extraction alone is not the problem anymore. The harder challenge is what comes after. Validation. Business rules. Schema enforcement. Exception handling. And making sure the system does not quietly fail when confidence drops.Antonio shared how bem approaches this differently by treating unstructured data pipelines more like critical infrastructure than experimental AI workflows. Instead of relying on prompts and probabilistic outputs, their focus is on deterministic systems that enforce constraints, match against existing data, and flag uncertainty rather than guessing.We also explored why unstructured pipelines tend to fail silently, how teams should rethink data quality in a probabilistic world, and where the real intellectual property lies when building AI-powered products today.What I found most interesting is how this shifts the conversation from model capability to operational trust. Enterprises are not just asking whether AI works. They are asking whether they can depend on it when money, compliance, or customers are involved.If you are building AI products, data platforms, or automation workflows, this discussion goes deeper than the usual AI hype cycle.Watch the full interview below and share your biggest takeaway.#data #ai #bem #theravitshow

They built one of the fastest growing newsletter platforms for creators.I just published my conversation with Tyler Denk, Co-Founder & CEO of beehiiv on The Ravit Show and this one is fully practical.Instead of talking about newsletters in theory, we went inside his own newsletter, Big Desk Energy, and broke down how he actually runs it.On screen.Step by step.No fluff.We covered:* How Big Desk Energy crossed 118,000 subscribers* What is automated vs what still needs direct input* Website builder from landing page to archive* What happens the second someone signs up* How signup data powers smarter automations* Welcome journeys and re-engagement campaigns explained simply* Mistakes new creators make with automations* The post editor and what actually improves open rates* Growth tools like Boosts, Marketplace, referrals, and recommendations* Monetization through digital products, paid subscriptions, and ads* Why beehiiv charges 0% platform fees on paid subscriptionsPersonally, this conversation meant a lot to me.I use beehiiv myself to run our newsletter with 137,000 subscribers. It powers everything behind the scenes for us. Publishing, segmentation, automations, monetization.This episode felt like opening the backend of a real newsletter business and understanding how to think about it as a system, not just emails.If you are serious about building a newsletter in 2026, this is not inspiration content. It is execution content.We also have a special offer for The Ravit Show community:30% off for your first three monthsCode: RAVIT30This link auto-applies the discount:https://beehiiv.link/7twzg8I built 137K subscribers on beehiiv.Now you can see exactly how the CEO himself runs it.#data #ai #newsletter #beehiiv #creators #community #automations #theravitshow

Let's go 2026!!!! This Enterprise series is huge. Loved recording this one with real leaders who are using GenAI and leveraging right Data. Everyone is talking about GenAI in customer service. Very few are talking about what actually works in production. Next week, we are going live with a real, honest conversation on how enterprises are using GenAI with customer data to transform customer service.This is not about theory.This is not about shiny demos.We will talk about:- What GenAI chatbots and virtual agents are actually doing in production- Why most pilots fail when they hit real enterprise data- The kinds of customer questions that create the most value- How teams think about security, privacy, real-time access, and scaleThe business impact leaders really care about like resolution time, agent efficiency, and customer satisfactionJoining me are Ronen Schwartz and Miguel Navarro, who are working hands-on with these challenges inside large financial institutions.If you are building GenAI for customer-facing use cases, or planning to, this session will help you avoid costly mistakes and focus on what actually matters.Customer service is being redefined.But only for teams that get data right.#data #ai #genai #agents #governance #dataquality #k2view #theravitshow

Once teams start trusting AI to explain systems and guide decisions, expectations change. The conversation shifts from understanding to action. In Part 2 of the podcast, we go deeper into what happens next in the AI journey on the mainframe.We talk about trust and why it is the real blocker to scaling AI.How organizations move from alerts and recommendations to agentic workflows.And what safe autonomy actually looks like in real enterprise environments.Liat Sokolov from BMC Software shares how trust in AI develops over time and why it cannot be rushed.Anthony DiStauro from BMC Software breaks down how AI agents and orchestration change day-to-day mainframe operations without removing human accountability.This episode is about delegation, scale, and using AI in a way that strengthens reliability rather than putting it at risk.#data #ai #mainframe #agents #bmi #mainframe #skills #bmc #theravitshow

🚨Breaking: Big announcements by MongoDB. I just spoke to Pete Johnson, Field CTO for AI at MongoDB on The Ravit Show. This conversation cuts through the noise around AI and focuses on what actually works in production!!!!We get into:- What the Field CTO for AI role really looks like in the field- How MongoDB thinks about the data and AI intersection- Which recent MongoDB announcements actually matter- What enterprises should prioritize as they head into 2026- Clear advice for developers, data, and DevOps teams building with AINo hype. No buzzwords. Just practical insight from someone working directly with customers every day.If you are building, scaling, or planning AI beyond pilots, this episode is for you.Thank you MongoDB for sponsoring this post!#data #ai #mongodb #databases #mongodbpartner #agents #agenticai #theravitshow

AI agents did not suddenly appear this year. What changed is that enterprises are finally ready to use them. At AWS re:Invent, I spoke with Ronen Schwartz, CEO of K2view, to talk about what has really shifted in the agent space from last year to this year and why this moment feels different!!!!Here is what we covered • What changed in the agent landscapeLast year was about ideas and experiments. This year is about execution. Ronen shared why agents are moving from demos into real enterprise workflows • K2View on the AWS MarketplaceWe talked about what it means for K2View to be available on the marketplace and how customers can make the most of it, from faster onboarding to simpler adoption • The AWS and K2View partnershipWe discussed how the partnership with AWS helps customers deploy agent driven use cases faster while keeping control over their data • Agentic AI and the re:Invent keynotesWe reflected on the keynote announcements and why agentic AI has become a central theme for AWS and its ecosystemIf you are trying to separate agent hype from what is actually working in production, this conversation brings a grounded perspective!#data #ai #awsreinvent #agents #agenticai #aws #enterprise #k2view #theravitshow

Cloudera and AWS Partnership is extraordinary!!!! At AWS re: Invent, I stopped by the Cloudera booth to sit down with Michelle H., who leads Global Alliances and Channels worldwide for Cloudera. She sits right at the intersection of Cloudera, AWS, and the customers who are trying to move faster with data and AI.A few highlights from our conversation • Cloudera x AWS as a strategic betThis is not a surface-level partnership. There is a Strategic Collaboration Agreement in place with AWS that goes deep into joint roadmaps and hands-on POC workshops, all focused on delivering more value for customers. • AI, but with control and flexibilityCustomers want AI, but they also want to de-risk it. Cloudera is helping with offerings like AI Studios, while still giving customers an open base and control over their data in their own AWS environment. • Hybrid as a real differentiatorCloudera is becoming a true “bridge to the cloud” for many teams, helping them move workloads between cloud, on-prem, and even the edge instead of locking them into a single pattern. • Real impact, not just slidesWe talked about work with Mercy Corps, where data and AI are helping save lives in crisis zones like Sudan and Gaza, and about a major pharma company running 100-plus GenAI use cases on Cloudera AI to bring drugs to market faster. • Innovation and sovereigntyCloudera is also leaning into Sovereign Cloud, including being a launch partner for the EU Sovereign Cloud in AMIA and working in regions like the Kingdom of Saudi Arabia.Michelle’s advice to enterprise leaders was simple and practical: lean on your partners as trusted advisors, and do not wait for the perfect plan. Get started today with one use case and learn from it.#data #ai #awsreinvent #aws #agents #awspartners #agenticai #theravitshow

At AWS re: Invent this month, I spoke to one and only Ed Huang, Co-Founder and CTO of TiDB, powered by PingCAP, to talk about something many teams are quietly struggling with.The last few years in data were all about unbundling.- One database for transactions.- One for analytics.- One for vectors.That worked when workloads were separate.But AI changed the rules.As Ed put it, today the same application, or even a single AI agent, jumps across transactions, analytics, and vector search in milliseconds. No developer wants to manage five databases. Agents cannot do that at all.That is why PingCAP is betting on unification with TiDB X.One system that can:- Scale like an analytical warehouse- Behave like a transactional database- Support vectors and search natively- Run on object storage with elastic computeKeep a single SQL interface with strong guaranteesThis does not mean specialized databases disappear. Many of them will continue to win in narrow use cases.But the center of gravity is clearly shifting.As AI agents become first-class users of data systems, platforms that remove boundaries matter more than platforms that optimize for one workload in isolation.This was a sharp, honest conversation on where databases are heading in the AI era.#data #ai #awsreinvent #qlik #agenticai #sovereigncloud #aws #theravitshow

Big companies do not switch databases unless something is broken. At AWS re: Invent I spoke to Max Liu, Co-Founder and CEO of TiDB, powered by PingCAP, and Bo Liu, Head of Online Infrastructure at Pinterest, to talk about why teams like Pinterest are moving core systems back to SQL with TiDB.This was a deep, honest conversation about scale, reliability, and where databases are headed next.We covered:- Why Pinterest finally hit a wall with NoSQL after years on HBase- What really breaks first at massive scale: consistency, operations, or developer velocity- How Pinterest migrated critical graph systems to TiDB with no downtime and five nines consistency- The tension CIOs face between rock-solid stability and fast-moving AI teams- Whether embeddings and AI workloads should live inside the same database as transactions- How agentic workloads are changing what enterprises expect from a databaseThis was not about hype. It was about real systems, real migrations, and real trade-offs.#data #ai #awsreinvent #agents #agenticai #aws #database#enterprise AWS Partners #pingcap #theravitshow

Most cloud conversations ignore one simple truth. AI only moves as fast as your connectivity. At AWS re:Invent, I spoke to Ed Baichtal, Principal Engineer at Equinix, to talk about what actually sits underneath modern cloud and AI architectures!!!!A few takeaways from the conversation- Equinix operates more than 270 data centers worldwide and acts as the physical home for servers, networks, and cloud on ramps- Equinix is the largest AWS on-ramp provider, with native AWS connectivity built directly into its data centers- The Equinix Fabric Cloud Router is now available on the AWS Marketplace, making multi-cloud connectivity much simpler- Customers can virtually connect up to 25 Gbps to AWS across different regions without deploying physical hardware- AI workloads are pushing serious demand for higher throughput and more reliable connectivity between cloudsOver 3,000 customers are already connected through the Equinix Fabric, which means new connections can happen virtuallyOne customer moved massive volumes of data to AWS in under 30 days using the Fabric Cloud RouterLooking ahead, Equinix plans to introduce Fabric Intelligence in Q1 2026 to make multi-cloud and NeoCloud connectivity even smarterIf you are building AI or multi-cloud systems, this layer matters more than most people realize.#data #ai #awsreinvent #aws #agents #awspartners #agenticai #theravitshow

Developers are not just writing code anymore. They are starting to run a virtual team. At AWS re:Invent, I had a conversation with Jemiah Sius, VP, Market Strategy and Developer Relations, from New Relic about how AI is changing the day-to-day life of developers. This was one of those chats that makes you pause and rethink how software will be built very soon.Here is what stood out-- Agentic AI is becoming real for developers Teams are excited about agents that behave like a digital team or a virtual SRE, taking care of reliability and performance while developers focus on building features-- Developers are becoming orchestrators Over the next 6 to 8 months, the role of the developer is shifting. Less time writing every line of code, more time directing agents and tools. This shift is already driving a big jump in productivity-- Observability matters more than ever As agents start working across multiple LLM servers and interacting with other agents, visibility becomes critical. Without observability across the full agent layer, things can quickly create more work instead of less-- New Relic and AWS coming together We talked about the New Relic integration with AWS Q, which brings observability data directly into AWS DevOps workflows, and the new security agent that surfaces real production data on vulnerabilitiesIt was great catching up with Jemiah again and hearing how New Relic is thinking about the future of developers and reliability.#Data #AI #AWSRecipes #NewRelic #AgenticAI #Security #MCP #reinvent #NewRelic #TheRavitShow

Fantastic catching up with Camden Swita, Head of AI at New Relic at AWS re:Invent last week to discuss the biggest changes in the world of Agentic AI over the last year! We talked about how New Relic is connecting the dots at AWS re:Invent with major announcements including:- The Security RX agent, an AI agent that automates the process of finding and remediating security vulnerabilities in runtime, saving engineers a huge amount of time- Integrating the Model Context Protocol (MCP) server with AWS DevOps agents to ensure agents can access live context and make informed decisions from production- Camden also shared advice for leaders entering the agent tech space: don't treat observability as a secondary concern, as end-to-end tracing will be "fundamentally essential" for compliance and performanceWatch the video to learn more!#Data #AI #AWSRecipes #NewRelic #AgenticAI #Security #MCP #reinvent #NewRelic #TheRavitShow

Most companies want AI agents talking to their customers. Very few have the data to back it up. I had a blast chatting with Ali Behnam, Founder of Tealium on The Ravit Show at AWS re:Invent. If you work with customer data or AI, this one is worth watching.Tealium helps organizations bring customer data together in one place and use it in real time across marketing, product, and AI use cases. I keep hearing their name when people talk about getting data ready for AI, so I sat down with Ali to go deeper.We spoke about- Who uses Tealium and the main problem they solve for enterprises that are serious about customer data- Why agentic AI is such a big theme this year and what is actually changing inside large companies- Why so many AI agent projects get stuck in pilots and what is missing to make them work in the real world- How Tealium works with AWS, and what being built on AWS unlocks for customers- What Ali wants customers to be able to do by next re:Invent that they cannot easily do todayIf you are trying to make AI agents useful for real customers, not just in demos, I think you will find this helpful.#data #ai #aws #reinvent2025 AWS Partners #databases #agents #agenticai #tealium #theravitshow

Most mainframe challenges today are not caused by broken systems.They are caused by disappearing knowledge.Senior experts are retiring.Documentation is incomplete or outdated.And newer team members are expected to operate some of the most critical systems in the enterprise with very little context.In Part 1 of this podcast, we focus on where the AI journey really begins.- Why mainframe teams are under pressure right now.- What types of institutional knowledge are most at risk.- And how AI changes the way that knowledge is captured, shared, and used.Liat Sokolov walks through why AI is showing up at this moment and why traditional approaches have not been enough.Anthony DiStauro explains how AI helps close the skills gap by shortening learning curves and guiding teams through complex systems with more confidence.This episode is not about autonomy yet.It is about preserving what matters and helping people work better with the systems they already depend on.Part 1 is live now.#data #ai #mainframe #agents #bmi #mainframe #skills #bmc #theravitshow

I had a blast chatting with Anthony Anter, DevOps Evangelist at BMC Software on The Ravit Show and this one goes deep into a topic many enterprises are struggling with quietly. Mainframe modernization. Not tools. Not hype. Real ground reality.We started with a simple but uncomfortable truth Tony writes aboutBefore you even think about converting code, explain what you already have.That single line sets the tone for the entire conversation.- We talked about why so many COBOL to Java projects fail even before they begin.- Why teams rush into conversion without understanding decades of business logic buried in code.- And why mainframe systems often look like a long game of telephone, where intent is lost but code survives.A big part of the discussion focused on generative AI.Not as a magic converter, but as a way to explain, map, and document existing systems before touching a single line of Java.When teams finally see dependencies and flows clearly, the surprises are often eye opening.We also broke down a critical distinction that is often ignoredCode explanation is not the same as code translation.Missing this is where most modernization programs go wrong.Tony also shared why refactoring before rewriting matters, what practical cleanup really looks like, and how GenAI can help create Java code that is actually maintainable, not just converted.One part I personally found valuable was the balance between automation and human expertise.Where AI helps, where humans are still irreplaceable, and what governance is needed so AI output can be trusted.We wrapped with Tony’s checklist for smarter modernization and one clear takeaway for anyone working on or around mainframes today.If you are a CIO, architect, or mainframe professional thinking about modernization, this conversation will save you from expensive mistakes.#data #ai #mainframes #bmc #theravitshow