Épisodes

  • Companies Record What They Decided. Almost None Record Why. (Ashutosh Garg)
    Oct 29 2026

    Most companies record what they decided. Almost none record why, or what they considered and ruled out.

    Ashutosh Garg, co-founder and CEO of Twin Cafe (formerly Viven), is building Digital Twins: AI assistants trained on how a specific person reasons, decides and communicates, with that person kept in the loop. It is his third company, after Bloomreach and Eightfold, and it started with a blood test, a two-day wait to see his doctor, and three hours with ChatGPT.

    Host Jonathan W. Buckley of The Artesian Network and Ashutosh get into:

    • Why generic AI chases average knowledge, when people really want the experience of someone they trust
    • Keeping the human in the loop: review, edits and escalation to the real person
    • A two-month pilot that ended with roughly 140,000 employees on the platform
    • Augmentation vs. replacement, and why the quality of work is the real gain
    • Whether "digital twin" is the right name for the category
    • What enterprise knowledge management looks like in five years
    • His advice to founders: trust and security are non-negotiable, and don't build around today's technology constraints

    Every episode, on every platform: WeBuiltItBecauseWeHadTo.com

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    44 min
  • Everyone Asks Who Can Access the AI. He Asks What It Just Sent. (Gidi Cohen)
    Oct 22 2026

    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.

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    35 min
  • Software Ships Weekly. Pentests Still Run Once a Year. (Rejah Rehim)
    Oct 15 2026

    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/rejahrehim
    Beagle 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.

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    26 min
  • Seventy-Five Demos, Zero Sales. Then He Bet on Precision Over Volume. (Ashok Rajan)
    Oct 8 2026

    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/rajanashok
    Pristine 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.

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    54 min
  • The Wall Every AI Data Center Is Quietly Hitting (Vivek Raghunathan)
    Oct 1 2026

    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

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    57 min
  • Daniel Rosenrauch of Viirtue
    Sep 24 2026

    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-rosenrauch
    Viirtue: 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

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    41 min
  • Everyone Ignored In-House Legal. He Built Its Operating System. (Evan Wong)
    Sep 17 2026

    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/theevanwong
    Checkbox: 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

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    45 min
  • Nobody Wanted His Sales Playbooks. They Wanted the Recorder. (Gerald Zankl)
    Sep 10 2026

    Gerald Zankl and his co-founders spent three years selling sales playbooks. The playbooks were good. Almost nobody bought them. So they built a recorder to prove to sales reps that they needed the playbooks, and the customers told them to keep the recorder and throw the playbooks away.

    In this episode of We Built It Because We Had To, host Jonathan W. Buckley is joined by Gerald Zankl, founder of Kickscale, the conversation and revenue intelligence platform built for European B2B sales teams. Gerald opens with the two numbers the company exists to attack: sales teams lose roughly 66 percent of their time to non-selling work, and about 90 percent of what gets said in customer conversations is never captured anywhere. Kickscale records the calls, writes the data back into the CRM, and turns the transcripts into coaching, forecasting and product signal.

    The pivot is the story. The company is about six years old, but the product is three. The first three years were content, video tutorials and playbooks that were, in Gerald's words, hard to sell. The recorder started as a diagnostic to show reps what they were doing wrong. By September and October of 2023 the feedback was unmistakable: nobody asked about the playbooks anymore, everybody asked about the transcripts and the CRM sync. They rebuilt the whole company around the thing they had made as a means to an end.

    Gerald is direct about competing with a category leader. Kickscale is a Gong-like solution for Europe, and he names Gong as a great company doing 500 million in ARR rather than pretending otherwise. His wedge is where Gong is heavy: languages, data privacy, and the cultural differences in how European teams sell. The ICP is mid-market, teams with somewhere between ten and a hundred reps, a segment he had personally tried and failed to buy Gong for at a previous company.

    The rest is the unglamorous mechanics of getting to roughly 230 customers with about twenty people. Customer number one was an existing relationship, a social media management company, sold on a prototype so manual that users had to record in Teams, download the file, and upload it by hand. Bootstrapped as long as possible with one engineer and two people on go-to-market, then a 2.4 million pre-seed once traction was real. Three account executives now, with Gerald still selling. He is candid that the first sales hires are the real breaking point, because a founder sells the vision and a rep cannot.

    His backstory runs from his parents' petrol station in Austria, where his mother worked the register, through a technical high school where he built content management systems and personal finance tools that nobody ever used. That was the lesson that set the career: the best product in the world does not matter if you cannot sell it. He went from there to being the first sales and marketing hire at a startup that grew from seven people to 250.

    His advice to an operator six months into building B2B SaaS is the line he repeats to himself: the limiting factor in a software company is always sales. Ignore the rest and build yourself a system that sells. Motivation gets you started, but the system is what keeps you going.

    Every episode on Apple, Spotify, YouTube, Amazon and more: https://www.WeBuiltItBecauseWeHadTo.com

    Connect with Gerald Zankl: https://at.linkedin.com/in/geraldzankl/de
    Kickscale: https://kickscale.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=ep35&utm_content=shownotes

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    31 min