We Built It Because We Had To - Tech Founder Backstories

Jonathan W. Buckley of The Artesian Network

We Built It Because We Had To is a founder-interview podcast from The Artesian Network, hosted by Jonathan Buckley. Each episode digs into the real founder journey behind B2B SaaS and tech startups — the backstories, the drama, the lessons, go-to-market, product-market fit, fundraising, enterprise sales, scaling, and how agentic AI is reshaping the bet.

  1. 2d ago

    He Didn't Found the Company. He Ran It for a Decade and Handed It Back. (Edgard Capdevielle)

    Almost every founder story on this show is told from the middle of the climb. This one is told from the other end. Edgard Capdevielle spent about a decade as President and CEO of Nozomi Networks, one of the defining companies in OT and IoT security — a company he did not found. It was started by Andrea Carcano and Moreno Carullo; Edgard was brought in to run it. Under him Nozomi passed $100 million in annual revenue, reached sustained cash-flow break-even, and was acquired by Mitsubishi Electric. In July 2026 he handed the CEO seat back to co-founder Carcano and moved into an executive advisor role. Host Jonathan W. Buckley of The Artesian Network and Edgard get into: What makes an operator take someone else's company and give it ten yearsWhat is actually at stake when industrial systems are exposed, for anyone who has never set foot on a plant floorSelling to plant operators and industrial engineers instead of IT — and what his security peers got wrong about that buyerWhat the company looked like the week he took over, and the first thing he decided had to changeWhat a small startup has to prove before a large industrial operator will trust it with systems that cannot go downCulture, burn, repeatable sales and boards — which one actually kept him up at nightGetting the non-founder CEO relationship right alongside two technical co-founders, and where it got testedThe unglamorous, repetitive work behind $100M ARR that never makes a press releaseThe bet on the next phase of OT security he thinks the market has not priced inWhat he would tell an operator about to take the CEO seat at a company someone else foundedConnect with EdgardLinkedIn: linkedin.com/in/edgardcapdevielleNozomi Networks: nozominetworks.com Follow the showYouTube: youtube.com/@theartesiannetworkSpotify: open.spotify.comApple Podcasts: podcasts.apple.com Every episode, on every platform: WeBuiltItBecauseWeHadTo.com More from The Artesian Network: artesiannetwork.com

    He Didn't Found the Company. He Ran It for a Decade and Handed It Back. (Edgard Capdevielle)
  2. Oct 22

    Everyone Asks Who Can Access the AI. He Asks What It Just Sent. (Gidi Cohen)

    Enterprises rolled out AI agents and generative tools faster than they built any way to see what those systems were doing with sensitive data. Gidi Cohen built Bonfy to ask the question the existing security stack skips. Most security teams reach for DLP or CASB and ask who has access to the agent. Bonfy's framing — what the company calls Contextual Data Enforcement — asks something harder: what sensitive data is actually moving through AI agents, email, SaaS applications, collaboration tools and generative AI systems like ChatGPT, Claude and Microsoft Copilot. Bonfy's described customer base spans financial services, healthcare, insurance and technology, the sectors where unstructured content is hardest to govern. Gidi and host Jonathan W. Buckley talk about the intrinsic risks agentic AI brings into an organization and what it takes to get ahead of them, why AI doesn't carry the context a human brings to a judgment call, and the gap between a security problem that has a budget line and one that is merely a priority — the hardest part of selling a category buyers haven't funded yet. Every episode on Apple, Spotify, YouTube, Amazon and more: https://www.WeBuiltItBecauseWeHadTo.com Bonfy: https://bonfy.ai Enjoying the show? Follow We Built It Because We Had To wherever you listen and leave a rating. It helps other founders find these stories. For more on how The Artesian Network helps early-stage tech companies get to market and scale, visit The Artesian Network.

    Everyone Asks Who Can Access the AI. He Asks What It Just Sent. (Gidi Cohen)
  3. Oct 15

    Software Ships Weekly. Pentests Still Run Once a Year. (Rejah Rehim)

    Software ships every week. Most penetration tests still run once a year. Rejah Rehim built Beagle Security to close that gap. Rejah started his career as a penetration tester, writing scripts to speed up his own audits. He saw small and mid-sized companies skipping pentests entirely because the cost was high and nobody was available to do them, so he turned those scripts into an automated product. Beagle Security launched with a lifetime deal that brought in roughly 1,600 to 1,700 early users, and that early usage trained the system. Today it has around 150 recurring subscription customers, and most still find it inbound through SEO and the blog. Rejah and host Jonathan W. Buckley talk about fitting security testing into the development cycle, why business-logic testing was the hardest part to automate, how the team handles misses and false positives in a trust-heavy sale, and what AI-written code means for the attack surface. His advice for security founders: get customer feedback as early as you can. Every episode on Apple, Spotify, YouTube, Amazon and more: https://www.WeBuiltItBecauseWeHadTo.com Connect with Rejah Rehim: https://www.linkedin.com/in/rejahrehimBeagle Security: https://beaglesecurity.com Enjoying the show? Follow We Built It Because We Had To wherever you listen and leave a rating. It helps other founders find these stories. For more on how The Artesian Network helps early-stage tech companies get to market and scale, visit The Artesian Network.

    Software Ships Weekly. Pentests Still Run Once a Year. (Rejah Rehim)
  4. Oct 8

    Seventy-Five Demos, Zero Sales. Then He Bet on Precision Over Volume. (Ashok Rajan)

    Ashok Rajan ran 75 demos in two months and closed nothing. Then he took every recording, fed it to AI, and rebuilt his company around what customers actually said. In this episode of We Built It Because We Had To, host Jonathan Buckley is joined by Ashok Rajan, founder of Pristine Data AI, an AI sales intelligence and outbound platform that handles prospect search, enrichment, research, playbooks, personalized email and deliverability in one place. Ashok spent years at Responsys and 6sense watching revenue teams drown in disconnected tools, and he started Pristine Data on a contrarian bet: in a market that rewards volume, precision wins. You will hear why a tight ICP matters more than a bigger list, how the message has to change by buying role and seniority, and why Ashok adds a third pillar to right person and right message: right time. Jonathan and Ashok compare notes on a surround-sound, multi-touch approach, and on the tension between precision and the volume it still takes to get noticed. Ashok also tells the founder story straight: two months of demos with no sales, a product rebuilt on what the recordings revealed, a first outbound campaign in July, and a first paying customer who found him through an AI-personalized email. Revenue has been growing since August 2025, and he has chosen not to chase a seed round yet. His closing advice for founders is to be ruthless with your time, because time, not money, is the real currency. Every episode on Apple, Spotify, YouTube, Amazon and more: https://www.WeBuiltItBecauseWeHadTo.com Connect with Ashok Rajan: https://www.linkedin.com/in/rajanashokPristine Data AI: https://www.pristinedata.ai Enjoying the show? Follow We Built It Because We Had To wherever you listen and leave a rating. It helps other founders find these stories. For more on how The Artesian Network helps early-stage tech companies get to market and scale, visit The Artesian Network.

    Seventy-Five Demos, Zero Sales. Then He Bet on Precision Over Volume. (Ashok Rajan)
  5. Oct 1

    The Wall Every AI Data Center Is Quietly Hitting (Vivek Raghunathan)

    Every major AI training operation is quietly running into the same wall: the speed at which silicon can move data between chips. Every new GPU cluster a hyperscaler adds makes the problem more expensive. In this episode of We Built It Because We Had To, host Jonathan W. Buckley is joined by Vivek Raghunathan of Xscape Photonics — the deep-tech company spun out of Columbia University research to attack the bandwidth bottleneck at GPU-to-GPU and GPU-to-memory interfaces inside AI data centers. Xscape's core platform is a scalable multi-color laser system: custom silicon photonics built for hyperscale data centers and AI infrastructure operators. This is not a software company with a slick demo. It's a materials and systems company making a long, capital-heavy bet — and the conversation digs into what that takes: the moment Columbia research stopped being research and started feeling like a company that had to exist, what the skeptics got wrong about the market, what broke first in the university spin-out chaos and how it got fixed, and how a hardware team holds together when timelines slip. Vivek is candid about the growth challenge in front of him now: finding product-market fit and expanding into new segments. Every episode on Apple, Spotify, YouTube, Amazon and more: https://www.WeBuiltItBecauseWeHadTo.com Xscape Photonics: https://www.xscapephotonics.com Enjoying the show? Follow We Built It Because We Had To wherever you listen and leave a rating. It helps other founders find these stories. For more on how The Artesian Network helps early-stage tech companies get to market and scale, visit https://www.artesiannetwork.com/?utm_source=podcast&utm_medium=referral&utm_campaign=ep38&utm_content=shownotes

    The Wall Every AI Data Center Is Quietly Hitting (Vivek Raghunathan)
  6. Sep 24

    Assume Everything Will Break. That's What Fast Scaling Feels Like. (Daniel Rosenrauch)

    In this episode of We Built It Because We Had To, host Jonathan W. Buckley is joined by Daniel Rosenrauch of Viirtue, a white-label VoIP and unified communications platform built for MSPs, ISPs, and resellers who want to sell voice services under their own brand without running the infrastructure themselves. Viirtue was founded by people who had been resellers themselves, and it positions itself as partner-first: fully managed cloud infrastructure, with billing, tax compliance, and usage rating handled for partners, plus AI call intelligence such as call transcription and sentiment analysis. Jonathan and Daniel talk about building a channel-dependent business through several market shifts — the move from on-premise to cloud, COVID, and now AI — and what it takes to keep a partner-first model together as the ground moves. Every episode on Apple, Spotify, YouTube, Amazon and more: https://www.WeBuiltItBecauseWeHadTo.com Connect with Daniel Rosenrauch: https://www.linkedin.com/in/viirtue-dan-rosenrauchViirtue: https://www.viirtue.com Enjoying the show? Follow We Built It Because We Had To wherever you listen and leave a rating. It helps other founders find these stories. For more on how The Artesian Network helps early-stage tech companies get to market and scale, visit https://www.artesiannetwork.com/?utm_source=podcast&utm_medium=referral&utm_campaign=ep37&utm_content=shownotes

    Assume Everything Will Break. That's What Fast Scaling Feels Like. (Daniel Rosenrauch)
  7. Sep 17

    Everyone Ignored In-House Legal. He Built Its Operating System. (Evan Wong)

    Enterprise legal teams are overwhelmed by inbound work they can't see or control — and it slows down the whole business. Most AI companies chase sales and customer support. Evan Wong went after the function they all ignore. In this episode of We Built It Because We Had To, host Jonathan W. Buckley is joined by Evan Wong, founder of Checkbox — the AI Legal Front Door and Operating System built for enterprise in-house legal teams. Checkbox intakes requests from every channel, automates routine work with AI, and assigns matters automatically based on type and expertise, while giving legal leaders the visibility and metrics to track workload, cycle times, and resources. For the business, that means instant answers, faster turnaround times, and full transparency into where requests stand. The wedge is the story. Legal ops is one of the least glamorous corners of enterprise software, and enterprise legal teams have historically been invisible inside their own companies — no real operating system to manage the flood of inbound work. Checkbox picked that beachhead deliberately, positioned itself as the front door to the legal function, and earned its way into serious procurement environments: named customers include Analog Devices, SAP, Coca-Cola, and Woolworths — with no IT required to deploy and minimal change management. Jonathan and Evan get into the origin of that bet — who first convinced Evan that in-house legal was the right beachhead — what early selling looks like when the buyers are lawyers rather than revenue leaders, how Checkbox thinks about applying generative AI to a function most AI companies have ignored, and the growth challenge Evan names candidly: adding revenue at a rapidly increasing rate quarter over quarter to hit growth goals. Every episode on Apple, Spotify, YouTube, Amazon and more: https://www.WeBuiltItBecauseWeHadTo.com Connect with Evan Wong: https://www.linkedin.com/in/theevanwongCheckbox: https://www.checkbox.ai Enjoying the show? Follow We Built It Because We Had To wherever you listen and leave a rating. It helps other founders find these stories. For more on how The Artesian Network helps early-stage tech companies get to market and scale, visit https://www.artesiannetwork.com/?utm_source=podcast&utm_medium=referral&utm_campaign=ep36&utm_content=shownotes

    Everyone Ignored In-House Legal. He Built Its Operating System. (Evan Wong)

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We Built It Because We Had To is a founder-interview podcast from The Artesian Network, hosted by Jonathan Buckley. Each episode digs into the real founder journey behind B2B SaaS and tech startups — the backstories, the drama, the lessons, go-to-market, product-market fit, fundraising, enterprise sales, scaling, and how agentic AI is reshaping the bet.