The Next Frontiers of AI
with Scott Hebner
About the podcast
AI is still in its infancy, but innovation cycles and the pursuit of high-value ROI are advancing at warp speed. The ability to keep up will determine who leads, who lags, and who fails.
Join theCUBE Research principal analyst Scott Hebner and industry pioneers and experts to explore the latest advancements shaping the future of AI and how to prepare today.
episodes
Ontology Maturity – Why Databricks’ Next Jump Is the Hardest One
The enterprise AI race may come down to the best frontier model. But it’s likely we’ll need more than a smart LLM and a popular copilot.
The bigger race is about who can build the most comprehensive real-time model of how an enterprise actually works – its data, entities, relationships, metrics, policies, workflows, decision rights and live operating state.
That is what we mean by a system of intelligence (SoI).
Why AI is Making Acquisitions the New Innovation Strategy
Enterprise AI is entering the era of digital labor, where AI agents evolve from simple assistants into trusted digital coworkers capable of reasoning, making decisions, and collaborating with people. Based on new primary research from 625 AI leaders, this brief examines why organizations are embracing digital labor, the barriers preventing scalable adoption, and the trust architectures required to turn AI ambition into measurable business value.
The Corporate Graveyard of AI Invisibility
Your company may exist on the internet. But does it exist in the answer? As AI compresses markets into just a handful of recommendations, millions of businesses risk becoming part of a new Corporate Graveyard of AI Invisibility. Understanding why AI chooses some brands—and ignores others—may become one of the most important competitive advantages of the decade. This research explores how leaders can survive the Great Marketplace Compression.
Escaping the AI Coding Chaos Trap
This research note examines the “AI Coding Chaos Trap”—an operational challenge where organizations become highly AI-active without becoming genuinely AI-productive.
It outlines why software engineering infrastructure must shift from tracking surface-level activity to mastering organizational coordination, institutional memory, and measurable business ROI. It highlights CodeVine and CEO Wells Burke’s strategic three-pillar model—Capture, Correlate, and Compound—as a critical architectural imperative.
Next Gen of AI Agents That Know, Contextualize, and Remember
The chatbot era is ending. Discover the four-act architectural progression—from simple linguistic fluency to domain-specific enterprise cognition —required to build next-gen AI agents that move beyond coherent conversation toward accountable, compounding digital labor. Meet the architecture that will unleash the “golden age” of digital labor.
Why Engineering Velocity is the New Determinant for AI ROI
Why is 85% of enterprise AI currently stalling in “Pilot Purgatory”? While 57% of organizations are experimenting with agentic workflows, only 15% have achieved productive ROI. This research brief identifies the root cause: the AI Velocity Trap. Moving beyond the “Browser Wars” of model selection, Scott Hebner and Nitesh Bansal reveal why Engineering Velocity is the new determinant for success. Learn how the 5-Layer Enterprise Cake framework collapsed a 16-month roadmap into just 9 weeks.
AEO Diagnostics: Create an AI Discovery Advantage
AEO is becoming a critical new discipline in B2B growth as AI-mediated buyer journeys reshape how buyers discover, evaluate, and shortlist vendors. In this episode, Scott Hebner talks with Stas Levitan, CEO of LightSite AI, about why measuring AI visibility is not enough, and why brands must diagnose the technical, narrative, and trust factors that determine whether they are surfaced, cited, and chosen in AI-driven discovery.
The conversation focuses on three underexamined dimensions of AEO success: how AI crawlers actually behave on and off your digital properties, whether your brand narrative is semantically clear enough for AI engines to understand your value and relevance, and how effectively your claims can be validated through credible, citable signals across the broader digital ecosystem. Together, these factors are increasingly shaping which brands AI engines know, trust, and recommend.
Beyond the Black Box: Building Transparent, Trustworthy Multi-Agent AI
Explore how to build trustworthy multi-agent AI systems. AI’s next frontier will not be defined by bigger models, but by trust. As enterprises push agentic AI into higher-stakes workflows, the question is no longer what AI can generate—it is whether its decisions can be justified and defended. With only 49% of enterprises reporting high trust in AI outcomes and just 29% having formal trust frameworks in place, the gap is clear. In this episode, Scott Hebner and Openstream.ai’s Magnus Revang explore why transparent, auditable multiagent systems—not black-box models—are the foundation for enterprise-grade AI.
2026 Enterprise AI Predictions
It’s time for theCUBE Research’s 2026 Enterprise AI predictions. Join Scott Hebner and Christophe Bertrand as they give their 2026 Enterprise AI predictions and pressure-test what changed in 2025. The enterprise AI market is now operating on innovation cycles measured in quarters, not years, and the competitive gap is compounding: organizations that learn, instrument, and govern faster will pull away, while laggards may never fully catch up. The conversation opens with a scorecard on our six 2025 enterprise AI predictions from last year. Then we shift to four 2026 predictions focused on what will matter most for enterprise leaders: The throughline is pragmatic: in 2026, trust becomes the gating factor for scale, and visibility becomes a competitive moat. These are predictions you can count on, grounded in real survey data and industry insights. Watch the podcast to hear the conversation. ⏱ Chapters 05:43 – Assessment of 2025 predictions – LLMs run out of gas in the
How To Build Decision-grade AI Agents You Can Trust and Audit
Enterprises are pushing agentic AI beyond copilots into diagnosis, problem-solving, and decision-making—but trust is now the ROI limiter. In this episode of Next Frontiers of AI, Scott Hebner and George Gilbert explain why LLM-only architectures are reliability traps and outline a practical, three-layer blueprint—LLM+CoT, semantic layers (knowledge graphs), and causal reasoning—to deliver decisions you can verify, defend, and audit.
Will 2026 Be The Year AI Decision Intelligence Goes Mainstream?
In this episode of Next Frontiers of AI, Scott Hebner and Joel Sherlock, CEO of Causify, argue that 2026 will be the year AI Decision Intelligence goes mainstream. Following GenAI and the rise of AI agents and agentic workflows, enterprises are facing a reality check, as a recent Carnegie Mellon study found — AI agents can act, but they often cannot justify, explain, or audit the decisions that matter most. Scott and Joel unpack why causal AI and knowledge graphs are emerging as the enabling layer for decision-grade AI.
How Agentic AI Rewires a SaaS Business: Lessons from a Unicorn
Digital labor is no longer emerging — it is becoming the defining operating model of modern service businesses. According to the Digital Labor Transformation Index, over 61% of enterprises believe the rise of digital labor is now inevitable, and the organizations seeing the highest ROI are those that shift from basic automation to knowledge-centered, agentic work. Few companies embody this shift as clearly as Vantaca, the newly minted $1.25B unicorn redefining community management through an AI-first architecture.
In this episode of The Next Frontiers of AI, Scott Hebner is joined by CEO Ben Currin to unpack how Vantaca rewired itself around a “UI, API, and AI-first” model, and how its platform now operationalizes millions of agentic workflows that free humans from low-value tasks and elevate their capacity for real community-building work.
The Agentic AI Masquerade: How to Tell What’s Real vs. Marketing
The industry is racing to claim “agentic AI,” but the reality looks very different. Scott Hebner and David Linthicum reveal why only 17% of enterprises are actually building real AI agents, what distinguishes assistants from agents, and why reasoning—not prompting—defines the next frontier of autonomous intelligence.
Why AI Chooses Your Brand: Demystifying How AI Discovery and Digital Buyer Journeys Work
AI discovery and AEO are reshaping how B2B buyers find and trust brands — here’s how to ensure yours shows up in AI search. As generative AI assistants like ChatGPT, Claude, Gemini, Grok, and Perplexity replace traditional search, brand visibility now depends on how large language models (LLMs) learn, rank, and recommend. Together, they unpack a 19-attribute framework across four categories that explain how LLMs discover, learn, and select brands to include in AI-generated answers.
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The Widening AI Value Gap: How to Close the Gap Before It’s Too Late
In this episode of The Next Frontiers of AI, host Scott Hebner, Principal Analyst for AI at theCUBE Research, sits down with Vladimir Lukic, Global Leader of the Tech & Digital Advantage Practice at Boston Consulting Group (BCG) to explore one of the most urgent questions in enterprise AI today: Why are only 5% of companies realizing real value from AI, while the rest are falling further behind? And more importantly, what can companies do to remedy this problem before it’s too late.
Agentic AI ROI: From Automation to Decisions
n this episode of Next Frontiers of AI, host Scott Hebner is joined by Paul Chada, CEO of Doozer AI, to explore one of the most urgent questions in enterprise AI: What is the real state of agentic AI ROI, and where is it headed? As companies shift from foundational Generative AI to the ”golden age of AI Agents” and the super cycle of innovation it promises, the stakes are rising. Digital coworkers are no longer just creating content or automating repetitive tasks, but are actively involved in workflows, knowledge work, and decision-making processes. In this discussion, we share real-world lessons from AI agent deployments and present new findings from the Agentic AI Futures Index survey to illustrate how adoption is progressing, where plans are accelerating, and what the journey toward decision intelligence entails.
The State of Digital Labor Transformation:
In this episode of Next Frontiers of AI, Scott Hebner and Christophe Bertrand, both Principal Analysts at theCUBE Research, unpack fresh primary research data on the state of digital labor transformation. The new Digital Labor Transformation Index reveals a striking workforce evolution underway: business leaders are no longer viewing agentic AI as simply a software automation or analytics paradigm shift, but as a genuine labor market phenomenon that promises to fundamentally change how work gets done.
The data shows more than 70% of AI and business professionals believe this generation of leaders will be the last to manage human-only workforces, underscoring a conviction that digital labor is inevitable. With an aggregate maturity score of 3.1 across 13 dimensions on a 0–5 scale, enterprises are moving steadily from experimentation into structured adoption—but the journey remains uneven and trust in autonomous roles is fragile. The research highlights the pivotal role that Chief HR Officers (CHROs) will play as co-architects of this transformation, and how the emerging role of Chief AI Officers (CAIOs) is destined to expand into a powerful intersection of business strategy, technology leadership, and digital workforce design.
The conclusion: success in digital labor transformation will require cross-functional ownership, new models of trust, and bold leadership from both CHROs and emerging Chief AI Officers. #DigitalLabor #AgenticAI #FutureOfWork
Digital Labor @ Work: How AI Agents Are Transforming Community Management
Explore how agentic AI and digital workers are transforming the operations of community association management companies. What began as a vision to eliminate inefficiencies in community management has grown into a platform that manages more than a million homes, delivering measurable ROI for management companies while achieving higher satisfaction for homeowners and board members.
The conversation examines how HOAi’s agentic AI platform addresses persistent challenges, including growing homeowner demands, hiring and retaining talent, rising operational costs, low margins, and effective communication with homeowners and board members.
By introducing digital workers tailored for domain-specific complexity, HOAi streamlines core functions like accounts payable, accounts receivable, customer service, management tasks, and more. This leads to more efficient operations, the ability to expand without hiring more staff, working smarter and faster with improved quality, freeing up time for the team, and gaining a competitive edge.
Navigating the AI Talent Crisis: Act Now Before It’s Too Late!
In this episode of Next Frontiers of AI, host Scott Hebner is joined by Justice Erolin, Chief Technology Officer at BairesDev, to confront one of the defining challenges of 2025: the AI talent crisis. The demand for AI-skilled professionals is already outpacing supply by a factor of 2.3 times, with job openings growing 10 times faster than the number of new entrants into the field. Seventy percent of enterprises report struggling to find qualified AI talent, while 40% of existing AI-skilled employees are considering leaving their jobs. The result is a spiraling competition for scarce talent, with companies paying salary premiums of 47% to 200% in an unsustainable arms race.
This episode examines what lies beneath that crisis—and why the solution isn’t just about pursuing human capital. A key shift is happening as software developers become data scientists and AI engineers, broadening their skills while using agentic AI systems that allow them to design and deploy models without requiring deep expertise. Simultaneously, AI talent augmentation is becoming inevitable, as enterprises blend flexible outsourcing with AI agents serving as virtual specialists.
Decoding NVIDIA’s AI Factory Product Maze
NVIDIA’s Q2 FY26 earnings call underscored once again that the company is not just a GPU vendor, rather it is an AI infrastructure company supporting the buildout of AI Factories. With revenue hitting $46.7B for the quarter and data center sales accelerating, the product portfolio is expanding so quickly that even seasoned observers struggle to keep the names straight. To help make sense of the landscape, we’ve compiled a cheat sheet mapping NVIDIA’s sprawling platforms, where they sit in the roadmap, and how much revenue they’re driving.
A Strategic Analysis of the Future of AI and Robotics: From Industrial Efficiency to Embodied Intelligence
We believe the convergence of artificial intelligence, advanced computing, and robotics is not merely an incremental technological step; it is a “systems revolution,” as described by industry leaders, creating a new, dynamic market landscape with profound economic and societal implications.
From PoC to Product: Scaling Agentic AI in Financial Services
In this episode of Next Frontiers of AI, host Scott Hebner is joined by Peyman Parsi, Senior Principal for Financial Services at MongoDB, to examine a critical industry challenge: why roughly two‑thirds of AI projects in financial services stall before reaching production, and why those that do often fail to scale with the business. With the advent of agentic AI and its higher‑stakes use cases, this challenge is only becoming more pressing.
The conversation examines the organizational, technical, and trust barriers that prevent promising proofs-of-concept from scaling, ranging from legacy infrastructure and governance gaps to rising costs, bias, and unclear ROI. Scott and Peyman discuss how financial institutions can overcome these obstacles by adopting trusted, agentic architectures built on strong data foundations.
Why Brand Matters in the Age of AI Discovery
In this episode of Next Frontiers of AI, host Scott Hebner is joined by Mick Hollison, founder and CEO of Redline Advisors, former CMO of CrowdStrike and Cloudera, and one of the industry’s leading voices on strategic messaging and brand elevation. Together, they unpack a pressing question: in an AI-first world where algorithms increasingly shape buyer discovery and decision-making, does brand still matter? The answer is a resounding YES, but not in the way it used to. The days of traditional “search and click” are numbered, being replaced by AI-guided discovery and engagement.
AI Meets Psychology: How to Build Agents that Understand People
In this episode of Next Frontiers of AI, we talk with Jonathan Kreindler, President and Co-Founder of Receptiviti, about the emerging science of psychologically aware AI. Jonathan explains how psychological signals—often hidden in filler words that LLMs overlook—are vital for turning AI agents from simple responders into emotionally intelligent and human-aware coworkers. His team is developing new technologies that provide AI with a validated, research-backed layer of human insight, enabling agents to detect stress, mindset, and decision-making style from natural language in real time.
Governance and Compliance in the Age of AI
In this episode of Next Frontiers of AI, Scott Hebner is joined by Christophe Bertrand, the Principal Analyst for Cyber Resiliency and Data Protection at theCUBE Research, to unpack a growing reality across the enterprise landscape: AI progress is hitting a wall—not because of technology limitations, but because of trust, transparency, and compliance shortfalls. While the promise of data-driven, AI-guided decision-making transforms strategy in every industry, many organizations are now pausing deployments due to inadequate data governance frameworks and a rapidly evolving regulatory environment. Together, they preview the upcoming Governance and Compliance in the Age of Data & AI Summit, hosted by theCUBE on September 27, 2025—a high-impact digital event designed to help enterprises confront today’s most urgent compliance challenges while enabling future-ready AI strategies. They’ll introduce the summit’s four foundational pillars: From explainability gaps and “what-if” reasoning frameworks, to federated governance, causal AI, and policy-as-code architectures, this episode offers a strategic preview into
Are the Agile & SaaS Models Dead with the Rise of Agentic AI? (#15)
In this episode of The Next Frontiers of AI, we’re joined by Arun Varadarajan, CRO of Ascendion, to explore a provocative question reshaping the future of software engineering and the software marketplace: Is Agile development dead? And as a result, will the SaaS model become a relic of the past? As AI agents begin to play an active role, not just assisting but actually engineering software, will Agentic AI-driven software engineering become the norm? And when? Arun discusses why traditional methodologies like Agile, which were built for human-centric development cycles, are giving way to a new model that is faster, leaner, and increasingly autonomous.
Agentic AI – What is Hype, Myth, and Truth (#14)
In one of our most clarifying episodes yet, we sit down with Satya Nitta—renowned AI innovator and CEO of Emergence AI—to separate fact from fiction in today’s rapidly evolving Agentic AI landscape. The enterprise world is awash in buzzwords, bold claims, and conflicting narratives, from predictive, generative, and agentic AI, onward to an AGI future. It’s never been harder to know what matters—and what doesn’t. Satya helps us decode the signal from the noise. He shares what agentic AI really is (and isn’t), how enterprises should think beyond AI assistants to intelligent systems that can reason, act, and collaborate, and where the real frontiers lie.
EY: Charting the Agentic AI Adoption Curve
In episode #13 of The Next Frontiers of AI, host Scott Hebner sits down with Ken Englund, Americas’ Technology Sector Growth Leader at EY, to unpack the results of the latest EY Technology Pulse Poll—a revealing snapshot of how tech leaders are embracing agentic AI.
More than two years into the GenAI era, technology companies are setting the pace of rapid Agentic AI adoption, with 48% already deploying agentic AI in some capacity and over half expecting the majority of their AI deployments to be autonomous within two years. Furthermore, 81% are optimistic about the potential of Agentic AI. But what’s driving this momentum? And are these early movers securing a real competitive edge, or simply moving faster into uncharted territory?
Ken and Scott explore what motivates tech executives to pursue agentic AI, how organizations manage their investments and risks, what this shift means for the future of tech jobs, and whether this innovation curve will soon extend beyond the tech sector into other industries.
The Future of Marketing: Causal AI Agents That Think Strategically
In this episode, we sit down with Michelle Killebrew, founder of Pegasus Strategy Co, to explore the future of causal marketing agents—a game-changing opportunity for marketers. Michelle, a seasoned marketing executive renowned for her AI-driven approach to growth and innovation, shares insights gained from over two decades of experience leading marketing transformations at companies like IBM and NTT and now advises organizations on leveraging AI to drive go-to-market success.
We delve into the transformative potential of causal AI in marketing. Unlike traditional predictive and generative AI, causal AI uncovers the “why” behind customer behaviors, even as conditions change. Michelle shares how causal AI empowers marketers to think more strategically.
Join us in this enlightening conversation about how the advent of causal AI is reshaping the marketing profession, enabling businesses to move beyond surface-level insights and make data-informed decisions that drive meaningful results.
Agentic AI – Why Architecture Matters
In this episode of the Next Frontiers of AI, we delve into the array of new technologies fueling Agentic AI and why architecture matters more than ever. I am joined by George Gilbert, the principal analyst at theCUBE Research, who covers data platforms, intelligent apps, and agentic frameworks, to dissect the approaches that industry pioneers are taking. As enterprises seek to harness AI’s full potential, the focus shifts from GenAI and LLMs to sophisticated AI agents capable of autonomous decision-making and continuous learning. We’ll share our insights about the importance of building a multi-layered architecture of AI agents.
Join us as we explore the future of AI agents and their role in enhancing workflows and driving innovation in enterprise technology. We will discuss how agentic AI fundamentally changes the nature of what software can do and how it is built. It is a must-watch conversation for anyone just getting started with agentic AI.
A Blueprint for Scaling a New Agentic AI Business
What does it take to build — and rapidly scale — a successful company in the era of Agentic AI? In this episode, we explore that question with Haoyu Zha, the Y-Combinator founder of HOAi, a fast-growing startup harnessing AI agents as digital workers to transform how homeowner associations (HOAs) operate, create value, and engage their communities. Founded in 2023, it turned real-world frustrations into an AI solution now adopted by major HOAs such as EJF Real Estate Services, Tyco Property Management, and CAMCO.
With the Agentic AI market projected to grow by nearly 45% CAGR through 2030, HOAi offers a rare case study on how to capitalize early on a breakout category. Their platform enables AI agents and human supervisors to partner, speeding up workflows and improving decision-making, making their solution fundamentally different from traditional business automation solutions.
Whether you’re a founder, investor, or tech strategist, this is your front-row seat to the blueprint for scaling a business in one of AI’s fastest-growing frontiers.
The Role of AppDev SDLC Platforms in the Era of Agentic AI
As enterprises rapidly embrace AI agents and agentic systems to revolutionize decision-making and automation, the question arises: Are Software Development Lifecycle (SDLC) solutions critical to the future of Agentic AI?
As Agentic AI increasingly becomes central to business innovation, understanding how Software Development Lifecycle (SDLC) platforms intersect with AI development is becoming mission-critical for business and technology leaders. This market brief, informed by discussions with industry expert Paul Nashawaty on theCUBE Research’s “Next Frontiers of AI” podcast, explores the significance of SDLC methodologies within AI workflows, highlights potential challenges, and examines how software developer roles adapt to widespread AI adoption. We also explore the evolving role of software developers in the era of AI.
History’s Guide To The Future Of AI
“In episode #8 of the Next Frontiers of AI Podcast, I’m joined by Irving Wladawsky-Berger—MIT research affiliate, legendary IBM executive, and influential technology innovator. We explore how 50 years of transformative tech provides valuable insights for AI’s future. Drawing from Irving’s experiences shaping mainframes, PCs, client-server systems, e-business, cloud, IoT, and AI, we ask: are we watching the same movie again with new characters? Tune in!”
The Anatomy of a Decision-Making Agent
In this episode of the Next Frontiers of AI Podcast, I go solo to address an array of questions I have received about how to build decision intelligence capabilities in AI Agents and agentic systems. As the market quickly realizes, generative AI and LLMs are insufficient to fuel these AI Agents, and businesses must build an extended ecosystem of specialized AI models. You’ll learn my point-of-view, which has been informed by dozens of AI experts and pioneering companies. I am eager to hear your views!
Create Resilient Supply Chains with Causal AI
In the latest episode of the Next Frontiers of AI Podcast, hear from Ishansh Gupta, the lead data scientist for quality management at BMW Group. We discuss how advancements in AI are being used to create more resilient and trustworthy supply chains and manufacturing processes.
You’ll also learn more about the power of Causal AI, why Ishansh became an early Ph.D. in the rapidly expanding field, how he earned his management’s trust, and how he is now nurturing the next generation of AI and data science talent.
AI That Knows Why
In this episode of the Next Frontiers of AI Podcast, I am joined by Stuart Frost, the CEO and founder of Geminos. We discuss the future of AI-powered business decision-making, which understands why outcomes occur. You’ll learn how this industry pioneer has delivered next-generation AI platforms that incorporate new innovations in Causal Knowledge Graphs. By integrating causal relationships, Causal Knowledge Graphs transform knowledge graphs from passive repositories into dynamic, self-reinforcing systems that provide a foundation for more intelligent decision-making AI agents.
Next-Generation AI in Financial Services
n this episode of the Next Frontiers of AI Podcast, I am joined by Jayeeta Putatunda, the director of the AI Center of Excellence at the Fitch Ratings, to discuss the unique needs of financial services organizations and how institutions are addressing the limitations of today’s AI. You’ll learn about the power of advanced RAG frameworks, agent-based architectures, and knowledge graphs and how Causal AI combined with RAG represents the next frontier for actionable, interpretable, and reliable AI decision-making.
Making AI Decisions Explainable
In this episode of the Next Frontiers of AI Podcast, I am joined by Marc Le Maitre, the CTO of Scanbuy, to discuss how his organization achieved a 10x ROI in digital advertising campaigns by creating fully explainable and transparent AI models through the emerging innovation of causal AI. Listen in and discover why Scanbuy is “flying their flag on Causal AI” to transform the world of programmatic advertising. You’ll also learn why causal AI will become a critical component in future Agentic AI systems and is rapidly being democratized for the masses to achieve similar business outcomes.
The Ladder to Agentic AI
The AI landscape is evolving fast, and 2025 is shaping up to be the year of Agentic AI—where AI moves beyond task automation and prediction to goal-driven decision-making. But here’s the challenge: 90% of enterprises want to embark on this journey, yet only one in three know where to start.
On the latest Next Frontiers of AI podcast, we broke down the roadmap to Agentic AI adoption with a simple framework—the Ladder to Agentic AI
#1 – Predictions for AI in 2025
In this first episode of The Next Frontiers of AI Podcast, I am joined by my industry colleague Tim Sanders, VP of Research Insights at G2, to debate theCUBE Research’s predictions for AI in 2025. We begin 2025 grounded in the consensus that will see the rise of agentic AI. In our predictions, we won’t restate that widely held belief; instead, we will focus on what will shape Agentic AI. We foresee a year of advancements that will tackle various real-world barriers to AI adoption and elevate the playing field for enterprises to achieve higher ROI use cases. Join us for this informative conversation, and chime in to let us know what YOU think!
The On-Premises AI Challenge for Startups
Today’s AI startups are overly reliant on public clouds and risk missing the opportunity to bring AI to data that resides on-premises. Organizations increasingly want to bring intelligence to their proprietary data that resides on-prem, to do training and inference under their own control. Startups’ primary route to market is either through hyperscaler marketplaces, which typically de-emphasize on-prem deployments, or via direct sources. When going direct, startups lack the credibility and go to market breadth to scale efficiently. As such we believe an opportunity exists for startups to partner with infrastructure leaders that have a strong on-premises installed base and both the talent and go to market expertise to penetrate traditional enterprises.
