The 272-Day B2B Sales Cycle (Nick Turner)

The 272-Day B2B Sales Cycle (Nick Turner)

The B2B sales cycle just hit 272 days. That is not friction. That is a buying committee with a new veto holder back at the table.In this episode of We Built It Because We Had To, I sit down with Nick Turner, CEO of Dreamdata, the Copenhagen-founded B2B revenue attribution platform that closed a $55M Series B in October. Nick spent twenty years in MarTech sales before joining Dreamdata as CRO to open the US market, and recently stepped into the CEO seat. We get into the counter-intuitive move that preceded the round — narrowing the ICP and the user persona instead of broadening it — and what Dreamdata's latest LinkedIn benchmark data is telling us about how B2B buying actually works in 2026.You will learn why the average B2B sales cycle stretched from roughly 205 days a year ago to 272 days today, why finance teams are reasserting veto power inside the buyer, why roughly eight different people are active in every account every week, and why Nick cut the Dreamdata product roadmap to six months in an Anthropic-funded world where assumptions expire fast. Nick explains why his North Star metric is the tenure of the CMO who uses the platform, and why you should never ask a marketer to manufacture demand for a deal that has to close this quarter. He closes with three lessons that shaped his path: you are a product of your failures more than your successes, all you need is one yes (he pitched 74 investors to close the round), and know yourself — he once joined a pre-revenue company and fell flat because scaling, not zero-to-one, was his game.If you run revenue, sit in the CMO chair, or own a number that depends on a buying committee saying yes, this one is for you.GuestNick Turner — Chief Executive Officer, DreamdataLinkedIn: https://www.linkedin.com/in/cnickturner/Company: https://dreamdata.ioAbout the showWe Built It Because We Had To is a podcast about early-stage tech founders, the spark behind what they built, and the journey to make it exist. Hosted by Jonathan Buckley of The Artesian Network, where we have helped founders scale companies and have seen more than half of our clients reach an IPO or acquisition.Subscribe wherever you listen, follow the show on YouTube for the full video, and learn more at https://artesiannetwork.com.— Jonathan Buckley, The Artesian Network

The AI Pushing Back on Insurance Denials (Michael Riley of Gabeo.ai)

On his fourth B2B SaaS company, Michael Riley walked into the most crowded corner of healthcare tech — claim denials — and walked right back out. He pivoted Gabeo.ai into a niche almost no one was working: claim write-offs, the revenue hospitals and provider groups have already given up on. In the first 90 days at a large Midwest hospital group, his agentic AI layer pulled back $1.2 million.In this episode of We Built It Because We Had To, Michael and host Jonathan W. Buckley get into the mechanics of finding a niche inside a saturated market, the two-product strategy at Gabeo (Zoey for fee-for-service, Aria for value-based care), and why value-based care flips the economic incentives of US healthcare. Michael walks through how their AI agents cut through hundreds of pages of contract language that "you'd need a team of lawyers and months to decode."Then they rewind to his arc — learning to program at seven, co-founding Simple Post, surviving a year of failure-after-failure at Funnl before landing on an analytics product that got acquired. Michael gets candid about a 45x-ROI pilot he renegotiated DOWN to a fairer 5-10x, why his entire GTM at Gabeo is warm intros (no paid ads, no sales team), and the single biggest tell that you've actually hit product-market fit: the body language in the room.What you'll hear:- Why Gabeo abandoned denials and chased write-offs instead- How agentic AI cuts through 100s of pages of contract language in minutes- The pricing lesson behind the 45x ROI pilot they renegotiated- 12 product pivots, one acquisition — and what Michael learned about MVPs- Why "selling is asking questions" beats pitching, every time- What he wishes he'd known 15 years agoConnect with Michael Riley: https://www.linkedin.com/in/themichaelriley/Learn more about Gabeo.ai: https://gabeo.aiSubscribe to We Built It Because We Had To for new episodes every Tuesday and Thursday. More from Jonathan W. Buckley and The Artesian Network: https://artesiannetwork.comIf this episode hit, share it with a founder who's still trying to brute-force product-market fit with a bigger sales team.#FounderStory #HealthcareAI #B2BSaaS #ProductMarketFit #AgenticAI

AGE: The 4th Axis the AGI Conversation Is Missing | Rana Gujral

🎙 Season 1, Episode 13Rana Gujral thinks the AGI conversation is missing a fourth axis: Artificial General Experience (AGE). On this episode of We Built It Because We Had To, the founder of Behavioral Signals and author of the upcoming book The AI Instinct: The Future of AI and Human Decision Making explains why intelligence without experience, memory, valence, or a persistent self-model is hollow — and why superintelligence won't arrive as an external god-like machine. It will emerge from hybrid cognition: the tight loop between a human's priors and a machine's scale.We also get into the through line from founding TIZE (acquired), leading Smart Home at Logitech, and helping rebuild Cricut during a near-bankruptcy stretch that turned into a successful IPO. Rana explains why Behavioral Signals doesn't use third-party LLMs and how its paralinguistic models read tone, pitch, prosody, and micro-pauses to extract the signal under the words. He breaks down the company's two business lines (CCaaS and national security, where they're backed by In-Q-Tel), and how their new behavioral mapping approach to deepfake audio detection works at half-second granularity and 98–99% accuracy when classical artifact analysis has stopped working.🎙 In this episode:→ AGE: Artificial General Experience as the missing AGI axis→ Why Behavioral Signals refuses to use third-party LLMs→ Paralinguistic models that read tone, prosody, and micro-pauses→ Deepfake audio detection by behavioral mapping (98–99% accuracy)→ In-Q-Tel backing and the national security business line→ From Logitech Smart Home to Cricut's IPO turnaround→ "Measure what the system does to the person, not just for them"📌 Connect with Rana Gujral:LinkedIn: https://www.linkedin.com/in/ranagujral/🎧 About "We Built It Because We Had To"The Artesian Network's podcast — hosted by CEO Jonathan Buckley. Real founder stories about the spark, the struggle, and the strategy behind building a tech company. More than half of our clients reach IPO or acquisition.→ Subscribe for new episodes every Tuesday and Thursday at 11 AM ET→ More from Jonathan: https://artesiannetwork.com→ Connect with Jonathan: https://www.linkedin.com/in/jonathanwbuckley/⏱ Chapters:00:00 Intro01:08 From Cricut's near bankruptcy to a successful IPO02:30 Behavioral Signals as research roots, not chatbot05:19 Two equal legs: call centers and national security06:56 Why old deepfake detection broke07:43 The cybersecurity manipulation problem10:12 Series A in 2019, before Transformers12:33 Inventing the category nobody had a bucket for16:09 Artificial general experience explained18:50 The chess engine that lives through nothing20:02 Hybrid cognition and the new unit24:23 Measure what the system does to the person#FounderStories #AI #AGI #VoiceAI #DeepfakeDetection

50 Customers, One US Patent, and a Tool That Plays Nice (Stephen Franklin)

Most cybersecurity vendors win by telling the buyer their existing tools are broken. Stephen Franklin filed a U.S. patent on doing the opposite.In this episode, Stephen — Founder and CEO of Netwatch.ai — walks through how he went from a teenage job at Pitney Bowes Software to building the patented AI integration layer that now sits on top of AWS, Azure, Carbon Black, Meraki, Cisco Cybervision, SolarWinds, and Nutanix. The thesis is simple: stop forcing rip-and-replace. Plug in. Reduce the customer's tool sprawl. Use AI to collapse mean time to contain from hours to seconds.What you'll hear:How a decade of technical sales at Argent taught Stephen exactly which integrations every cyber buyer wishes they had.Why bootstrapping Netwatch from his own Argent commissions kept the product roadmap honest.How utility co-ops — a vertical almost nobody else is actively selling cyber to — became one of Netwatch's sharpest early segments.The two AI "personas" Netwatch ships: a sysadmin and a CISO, with guardrails for what each one is allowed to do.How a Florida statewide cybersecurity contract opened the door to North Carolina, South Carolina, and Georgia.Why Stephen has turned down VC offers at 50 customers and a 100% renewal rate.50 customers in. 100% renewal. A real US patent. No rip-and-replace pitch in sight.Guest: Stephen Franklin, Founder and CEO, Netwatch.aiConnect with Stephen on LinkedIn: https://www.linkedin.com/in/stephen-franklin-ii/Netwatch: https://netwatch.aiHosted by Jonathan Buckley, CEO of Artesian Network. Subscribe to "We Built It Because We Had To, stories about founders and their journeys" wherever you get your podcasts. More at https://artesiannetwork.com.

Laid Off by the DoE — Then He Built an AI Startup | David Blumenthal

When the U.S. Department of Education was dismantled, David Blumenthal lost his 13-year career as an education researcher in a single March 2025 Zoom call. Three weeks later, his daughter was born. Somewhere between 2 AM and 3 AM bottle feeds, he started plotting his next chapter. The result is Eddy — a RAG-based AI tool for teachers built on 400,000+ peer-reviewed journal articles that cuts through academic jargon and cites every recommendation back to its source.In this episode of We Built It Because We Had To, David walks through the twin trust problem educators face (distrust of academic research and fear of AI hallucinations), why contextual matching and social proof matter more than raw accuracy, how they're validating their MVP by paying arms-length teacher-testers $50 for honest feedback, and why the path from bootstrap to pre-seed raise looks completely different now thanks to Claude Code, Lovable, and Replit. He also previews the Eddy Pro launch.🎙 In this episode:→ Losing a 13-year research career to a single Zoom call→ Building Eddy on 400K+ peer-reviewed studies→ The teacher trust problem (research distrust + AI hallucinations)→ Contextual matching beats raw accuracy→ Paying arms-length testers $50 for honest MVP feedback→ How Claude Code, Lovable, and Replit changed the bootstrap-to-seed path📌 Connect with David Blumenthal:LinkedIn: https://www.linkedin.com/in/blumenthaldavid/📌 Connect with Jonathan W Buckley:LinkedIn: https://www.linkedin.com/in/jonathanwbuckley/🎧 About "We Built It Because We Had To"The Artesian Network's podcast — hosted by CEO Jonathan Buckley. Real founder stories about the spark, the struggle, and the strategy behind building a tech company. More than half of our clients reach IPO or acquisition.→ Subscribe for new episodes every Tuesday and Thursday at 11 AM ET→ More from Jonathan: https://artesiannetwork.com→ Connect with Jonathan: https://www.linkedin.com/in/jonathanwbuckley/⏱ Chapters:00:00 Intro01:00 A tech CEO with no tech or business degree02:00 13 years at AIR and the March 2025 layoff04:21 The 2 AM idea that became Eddy06:45 400,000 journal articles inside a RAG09:45 Launching into an anti-evidence climate11:55 Context matching and the trust problem14:52 Paying teachers $50 for arms-length feedback17:56 Bootstrapping toward the pre-seed20:46 Saving Sunday night for teachers22:22 The billion-dollar two-person company#FounderStories #EdTech #RAG #FirstTimeFounder #AIForTeachers