BUILDERS

Front Lines Media
  • 5.0 (6)
  • Entrepreneurship
  • Updated Biweekly

Welcome to BUILDERS — the show about how founders get new technology adopted. Each episode features a founder on the front lines of bringing new tech to market, sharing how they broke into their industry, earned early believers, built credibility, and unlocked real technology adoption. BUILDERS is part of a network of 20 industry-specific shows with a library of 1,200+ founder interviews conducted over the past three years. For the full network, visit FrontLines.io. Brought to you by:  www.FrontLines.io/FounderLedGrowth — Founder-led Growth as a Service. Launch your own podcast that drives thought leadership, demand, and most importantly, revenue.

  1. 2d ago

    Finding the buyer who was already on the hook | Ria Shah

    Handl Health is building an AI platform that aggregates and analyzes publicly available healthcare pricing data, helping brokers and benefits consultants design, evaluate, and personalize health plans for self-insured employers. In a recent episode of BUILDERS, we sat down with Ria Shah, Co-founder & Chief Product Officer of Handl Health, to learn how the company turned newly mandated price transparency data into a plan design platform that brokers and benefits consultants rely on. Topics Discussed: How price transparency legislation created a now-or-never moment to build on terabytes of newly published contracted ratesWhy neither co-founder was technical, and how Ria learned Python and PySpark to ingest 300 billion row machine readable filesHow an NIH grant and a free consumer cost estimator revealed the wrong initial customerWhy Handl Health moved past direct-to-employer sales to the broker and benefits consultant channelWhere brokers see value first: prospecting new business with carrier comparisons and personalizing renewals with claim-level cost projectionsThe three-year education arc from explaining what an MRF is to a market where everyone needs a price transparency partnerHow Handl Health escaped the checkbox compliance perception by layering actuarial modeling and steerage on top of public dataWhy white glove service remains core even as the company productizes a services-heavy workflow GTM & Technology Adoption Lessons: Follow the burden until you find the buyer who owns it: Handl Health started consumer-facing with a free cost estimator, then realized that reaching the masses meant going through self-insured employers, who hold majority market share in how most Americans access healthcare. But employers are overburdened and understaffed, so the company went to the brokers and benefits consultants those employers already trust.Sell to the channel that is already on the hook: Brokers must give sound recommendations to employer clients about which network to rent and which point solutions to buy, while working with disparate data and no ROI visibility on vendors. When they started using the platform, Ria said their reaction was "wait, we can do this in minutes." Adoption is fastest where accountability and pain already sit together.Market education runs in stages, then flips: Ria described years one to three as skepticism that the regulations would even hold and that the data was useful. The company went from explaining what an MRF was, to convincing the market that MRFs contain useful data, to a market where everyone needs a price transparency partner and the only question is which one. Early adopter champions carried the company through the skeptical years.Regulation creates data, not a category: Early on, products like Handl Health's were perceived as checkbox compliance costs. The escape was the layer above the public data: actuarial modeling, cost projections, and steerage assumptions that help employers bring down costs and help members shop for higher value, lower cost care.Align the commercial model with channel growth: Ria said the commercial model came down to aligning incentives. As long as the platform helps brokers grow their book of business and differentiate in the market, they keep coming back and find new ways to partner.Productize the workflow, keep the concierge: Handl Health is productizing a highly services business. AI tooling automates much of the analytics, but when brokers run reports or stratify networks, the team wraps their arms around those partners to interpret results together. Ria does not expect that to go away, because the white glove layer is what makes the channel stick. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

    Finding the buyer who was already on the hook | Ria Shah

  2. 2d ago

    AI visibility is not SEO 2.0 | Imri Marcus

    Brandlight is building an AI visibility platform that helps enterprise brands, most of them Fortune 500 companies, monitor and influence how they show up in AI engines across AI search, AI ads, and agentic commerce. In a recent episode of BUILDERS, we sat down with Imri Marcus, CEO & Co-Founder of Brandlight, to learn how the company won Fortune 500 customers from day zero and turned AI visibility into a CMO priority instead of an SEO project. Topics Discussed: Why calling AI visibility "SEO 2.0" is the industry's most prevalent misconceptionWho owns AI visibility inside enterprise marketing departments, and why Brandlight always starts from the CMOHow Brandlight answers skeptics who claim AI engine results cannot be influencedThe advisory board of Fortune 50 CMOs and agency CEOs that opened enterprise doors from day zeroWhy enterprise AI visibility programs require orchestrating close to a hundred stakeholdersHow the education burden in first CMO conversations disappeared between late 2024 and todayWhat happens to SEO, brand, legacy search, and Google as search shifts into AI enginesReddit's real role in an AI visibility strategy GTM & Technology Adoption Lessons: Refuse the frame that shrinks your category: Imri said the most prevalent misconception is that AI visibility is SEO 2.0. Brandlight positioned it as a completely new marketing channel where traffic just happened to be the first KPI that got hit. The framing decides who owns the problem and how big the budget conversation can be.Start the sale where the orchestration lives: The SEO team is involved in every account Brandlight works with, but Imri called a single-department home the wrong place for a big enterprise. Brandlight always tried to start from the CMO and preach a holistic orchestrated approach, because PR, content, partnerships, and even legal teams need to get involved.Build the door-opening system before the market exists: Brandlight went after the Fortune 500 from day zero and built an advisory board of over a dozen advisors, people who are or were Fortune 50 CMOs and CEOs of some of the biggest agencies. The advisors made the initial connections, and the first iterations of the platform were seen by Fortune 50 CMOs.Treat early education as pipeline, not lost deals: At the end of 2024, the first 15 minutes of every CMO conversation was education. Not all of those CMOs purchased in 2024 or 2025, but it made sense to all of them, and Imri said the vast majority became customers later on.Answer skepticism with proof at the largest possible scale: Against the claim that AI answers cannot be influenced, Brandlight presented on the ANA's big stage with its customer Kimberly-Clark: over 12 months, the program took 12 out of 12 brands to lead their categories.Anchor urgency in behavior data, not predictions: Imri said that when Brandlight started, less than 1% of search happened in AI engines, and now it is over 50%. Brandlight analyzes billions of data points daily and can show traditionally successful marketing organizations losing share of voice while smaller companies overtake them.Position the new channel as additive, not substitutive: Imri argued SEO foundations still matter and brand still matters. AI visibility is an addition, not a substitution, which lowers the perceived risk of adopting it. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

    AI visibility is not SEO 2.0 | Imri Marcus

  3. 2d ago

    Selling into 95% market concentration | John Taylor Garner

    Odynn is an AI-powered, fully modular platform that helps fintechs, banks, card issuers, and travel companies launch embedded travel, loyalty, and rewards programs. The company's flagship product, Awayz, gives financial institutions a white-label travel portal where cardholders can search, plan, and book hotels and flights with side-by-side points, miles, and cash pricing. In a recent episode of BUILDERS, we sat down with John Taylor Garner, Founder & CEO of Odynn, to learn how the company is taking on a market where Booking, Expedia, and Hopper collectively hold 95% market share by offering financial institutions a personalized, modular alternative to their monolithic competitors. Topics Discussed: How John's background as a points and miles enthusiast led him to identify the gap in embedded travelWhy John shut down his first startup, Card Curator, and how that experience led to founding OdynnHow Built Rewards became Odynn's first customer and what they saw that other banks had not yet recognizedHow the market shifted from requiring heavy customer education to prospects who arrive already understanding the problemWhy US customers immediately understand the cardholder retention problem while European markets require more educationWhere the term "embedded travel" came from and how Odynn uses it to define the categoryThe critical marketing decisions John made to reach six different types of buyersHow Odynn structures its approach across personal banking, business banking, BaaS, credit card affiliates, card issuers, and corporate travel managementWhat selling to tier-one banks actually looks like in terms of sales cycle lengthWhat John learned transitioning from direct-to-consumer to enterprise financial institution salesTactics that have helped shorten long enterprise sales cyclesAdvice for founders selling technology to banks GTM & Technology Adoption Lessons: Solve a problem before customers know they have it: Odynn launched in January 2022 with the hypothesis that airlines and hotels moving toward dynamic pricing would cause points to become less valuable, which would hurt cardholder retention. As John put it, "fixing a problem that nobody really knew that they had was a hard thing to do." The company had to wait for market timing to catch up with its thesis before the sales motion became straightforward.Let customers tell you what product to build: Odynn originally focused on the loyalty layer of the problem. Customers like Built Rewards pushed them toward building a full travel portal. "It wasn't just the loyalty space that was broken," John said. "It is the entire experience of redeeming points or just booking travel with cash, either way, on the embedded side was really bad." The product pivot came from listening to customers, not from an internal strategic decision.Land a lighthouse customer who already sees what is coming: Built Rewards was Odynn's first customer and remains one today. John credited Built with being "one of the few customers that were savvy enough to know that this was going to be a big problem and ultimately in their favor, because they got ahead of it." Built had team members from airline and bank loyalty backgrounds who could read the trajectory of dynamic pricing before most banks could.

    Selling into 95% market concentration | John Taylor Garner

  4. Aug 20

    The market nobody wanted | Alex Jekowsky

    Cents builds software, payments, and hardware for the laundry industry, serving laundromat operators and other commercial laundry businesses. The company is the only venture-backed company operating at scale in a market that most technology companies had overlooked, and has reached approximately one in six U.S. laundromats. In a recent episode of BUILDERS, we sat down with Alexander Jekowsky, CEO & Co-Founder of Cents, to learn how the company grew to serve roughly one in six U.S. laundromats by building technology for operators that most software companies had written off. Topics Discussed: How Alex discovered the laundromat industry while looking to buy a small business after selling his previous company, a payment system for college campusesWhy laundromats generate durable cash flows -- 30% margins, 20-plus year equipment lifespans, and leases that can outlive their operatorsHow Cents became the only venture-backed company in the laundry software space and what Alex means by "first executor advantage"Why 70% of Cents's early sales were inbound -- and what that revealed about how badly the market was underservedHow trade shows became Cents's "Super Bowl" and why they staffed booths 25 to 50% heavier than plannedThe tension between brand building and product credibility in SMB tech, and the question operators ask when they see a high-profile marketing spendWhy the laundromat business is "a highly services-based business" despite appearing commoditized on the surfaceHow AI and robotics fit into laundry -- and why improving efficiency without improving service quality is "net worse"Why Cents describes its role as digitizing, not transforming, the laundromat industry GTM & Technology Adoption Lessons: Build in markets where buyers are already searching. Alex said 70% of Cents's early sales were inbound. The market was ready -- operators were actively looking for product. Know who you're actually selling to. Laundromat operators are not the unsophisticated buyers that investors and technology companies assume. Alex said they are often "more cash generative than any of the portfolio companies of a seed or series A investor." The insult embedded in that assumption had left a massive gap -- and Cents walked into it with 70% inbound demand.First executor advantage is more durable than first mover advantage. Cents was not first to try selling software to laundromats. But Alex described the company's edge as "first executor advantage" -- being the only company willing to raise the capital and build the balance sheet to actually execute at a level operators were searching for.Use events as trust infrastructure, not just brand exposure. Trade shows were Cents's "Super Bowl." The company staffed booths 25 to 50% heavier than planned because Alex believed the people behind the brand were what converted attention into trust. Earn the right to innovate before leading with transformation. Alex described Cents's job as "to not transform or change" the laundromat business -- it's to "digitize, create optionality, and earn the opportunity to drive innovation over time." Understand why the business looks commoditized but isn't. Two laundromats can use the same equipment, detergent, and labor pool and still deliver entirely different customer experiences. The laundromat business is actually "a highly services-based business." Adoption required understanding that operators cared deeply about how customers felt in the store, not just about technology features. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

    The market nobody wanted | Alex Jekowsky

  5. Aug 20

    The friends-of-friends GTM model in cybersecurity | Elad Ben Meir

    Onit Security builds AI agents for exposure management, helping security teams cut through the noise of tens of millions of vulnerability scanner findings to identify and prioritize the ones that can actually be exploited. The company is built from the ground up on agentic infrastructure, positioning itself as the fifth generation of exposure management tooling in a category that has evolved from basic vulnerability scanners to AI-native platforms over three decades. In a recent episode of BUILDERS, we sat down with Elad Ben Meir, CEO & Co-Founder of Onit Security, to learn how a cybersecurity founder with a marketing background is building go-to-market motion in one of the most competitive markets in tech. Topics Discussed: How Onit Security's AI agents filter tens of millions of scanner findings to identify the ones that can actually be exploitedWhy exposure management is still an unsolved problem after three decades and how the category has evolved through five generationsWhy early GTM in cybersecurity is built entirely on relationships and CISO trustHow Elad used channel partnerships at his previous company SCADAfence to scale from early stage to growth, and why he's running the same playbook at Onit SecurityThe "mailbox money" channel model where partner sellers identify opportunities and hand off to Onit Security's sales teamWhy spreading marketing risk across field marketing, brand, digital, social, and employee evangelism is the right approach at the early stageHow a branding agency investment Elad almost didn't make became one of the best decisions in the company's historyThe VC defensibility question: how Onit Security is building its moat as frontier AI models expand into adjacent marketsWhy technical founders find storytelling the hardest GTM skill to develop GTM & Technology Adoption Lessons: Trust before pipeline: Elad said early GTM in cybersecurity is "all about relationships." The first customers came from existing CISO relationships built over years. The story wasn't about product features alone -- it was about the founding team's personal track record and direct understanding of the problem. One co-founder had their previous company breached by a nation-state actor, and the forensic investigation traced the cause to an unmanaged vulnerability. Friends of friends compounds without effort: The second phase after direct relationships is peer referrals within the CISO community. Elad said the community is "very well knitted and close to one another," and successful deployments generate organic pipeline through peer trust. Channels are how you move from zero to scale: At SCADAfence, the GTM inflection came from strategic channel partnerships. Partners would identify the opportunity, open the door, and SCADAfence's sellers would close. Elad called it "mailbox money."Spread marketing risk early: At the early stage, a data-driven marketing machine is aspirational, not operational. Elad's approach is deliberate diversification: field marketing, brand building, digital, social, personal brand, and employees as evangelists. Branding is a bet, not a line item: Elad almost didn't sign the branding agency contract. The cost didn't justify itself analytically. His co-founders persuaded him: "We're building something big here. Let's bet on something big." He called it one of the best decisions the company has made. Marketing background as both asset and filter: Elad's time as VP of Marketing at a previous company gives him patience with early-stage marketing economics -- no direct correlation between money and results when you're starting -- and zero tolerance for agency narratives that don't hold up. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

    The friends-of-friends GTM model in cybersecurity | Elad Ben Meir

  6. Aug 20

    The growth engine hiding in a 28-week order set | Andrea Ippolito

    SimpliFed is a maternal care at home platform focused on virtual breastfeeding and baby feeding support, delivering insurance-covered care from pregnancy through the first year postpartum. In a recent episode of BUILDERS, we sat down with Andrea Ippolito, CEO and Founder of SimpliFed, to learn how the company built a referral engine that is on track to receive referrals representing about five percent of all births in the US this year. Topics Discussed: How Andrea validated that parents would pay out of pocket for feeding support before pursuing insurance contractsWhy SimpliFed enters health plans bottoms up through the provider credentialing page rather than selling as a vendorWhy the company moved away from a large commercial team and built a credentialing team insteadHow integration into the 28-week prenatal order set inside OB electronic medical records became the growth engineThe three-legged stool behind SimpliFed's growth: patient demand, health plan coverage, and referral partnersWhy SimpliFed spent three years on a clinical study with UMassCurrent coverage: roughly 50% of commercial health plans, Medicaid in 12 states, all 50 states commercially, and two national TRICARE contractsWhat it would take to grow from referrals representing five percent of US births to fifty percent GTM & Technology Adoption Lessons: Validate willingness to pay before chasing contracts: Andrea knew insurance contracts would take years, so the first test was whether parents would pay out of pocket. She recruited local lactation consultants as 1099 providers, ran the service on commercial off-the-shelf software, and let real payment behavior justify the harder infrastructure investments that followed.Know whether you are a vendor or a provider: SimpliFed originally built a large commercial team, then learned it did not need one. As Andrea said, "We are an in-network provider with a health plan. We're not a vendor." Providers enter health plans bottoms up through the provider credentialing page, so the company replaced its commercial engine with a strong credentialing team.Distribution beats proprietary software: Andrea said that with AI, "having proprietary software and all that is not as exciting as it used to be. It's about distribution." SimpliFed's growth runs on EMR and API integrations, not product novelty.Make the referral structured, not handcrafted: Posters and handcrafted outreach were fine for customer discovery, but growth came from integration into the 28-week prenatal order set template inside the OB's electronic medical record. The provider refers without changing their workflow, and the consented, structured referral data makes the motion scalable, predictable, and high growth.Augment the clinician instead of competing with them: With one in three counties lacking access to OB-GYNs and fewer OBs entering practice, SimpliFed positions itself as taking work off providers' plates. OB adoption depends on showing the company complements their care rather than threatening it.Buy evidence early because it cannot be rushed: SimpliFed's clinical study with UMass took three years and a full IRB process. The results, including 16 weeks longer breastfeeding duration and lower PHQ-9 scores at six months, are what make the ROI case to health plans, whose number one postpartum cost driver is maternal mental health. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

    The growth engine hiding in a 28-week order set | Andrea Ippolito

  7. Aug 20

    The head of AI who had never heard of an ontology | Rob Buller

    Cyberhill Partners builds and deploys enterprise AI solutions, including Cerebro, an enterprise AI platform Rob describes as AI in a box, and Wolverine, a digital twin product, drawing on eight years of AI work inside the intelligence community. In a recent episode of BUILDERS, we sat down with Rob Buller, Chief Executive Officer of Cyberhill Partners, to learn how the company is bringing intelligence-community-grade AI to enterprise buyers who are still missing the semantic layer that makes AI work. Topics Discussed: Why the core principles of technology adoption have not changed, but complexity has, splitting the buyer across CIOs, CTOs, and CISOsThe AI factory model: a runtime AI fabric that plugs into Snowflake, Databricks, Grok, or Gemini instead of shipping compiled, embedded logicHow Cyberhill positions Cerebro against Palantir on cost, vendor lock-in, and implementation speedWhy Rob has been shocked that heads of AI at multi-billion dollar companies do not know what an ontology isHow large incumbents like Workday and Salesforce try to freeze the market when new technology emergesWhy Cyberhill picks verticals by following demand into government, automotive, and healthcareMarketing at the local level in secondary markets like Dallas and Denver with billboards, airports, and quarterly steak dinnersPartnerships with ServiceNow and Databricks, and government AI work including a global biosurveillance platform GTM & Technology Adoption Lessons: The market cannot buy what it does not understand: Rob has been on roughly a hundred client calls where heads of AI at multi-billion dollar companies could not define an ontology. Without the semantic layer, he argues, you cannot apply context to AI or get traceability. Until buyers understand that, adoption stalls, so education is now part of the sales motion whether Cyberhill wants it or not.Sell the problem solved, not the underlying technology: "People don't care about ontologies and knowledge graphs, they care about can you solve my problem." Cyberhill leads with the business problem and only opens up the technical underpinnings when a buyer wants to know why the product is different.Expect incumbents to freeze the market: Rob says large companies respond to new AI entrants by telling customers they already have AI covered. He admits it does not really work, but it works a little bit. Plan the GTM knowing buyers are hearing "you don't need AI" from vendors they already pay.Let demand pick your verticals: "I've found that business is a lot like water. It finds the lowest level." Rather than forcing a vertical strategy, Cyberhill follows where demand shows up: government, automotive, healthcare. When healthcare demand grew, the company hired a doctor, because subject matter experts are how it enters an industry credibly.Position against the expensive incumbent on speed to value: Rob calls Palantir a great company and a great platform, but points to cost and vendor lock-in. Cyberhill's counter is malleability and implementation speed: "we can implement it in days, not months."Compete where the playing field is level: Instead of fighting Salesforce for attention in New York, LA, and San Francisco, Cyberhill markets at the local level in secondary markets like Dallas and Denver, with billboards, airport advertising, and quarterly steak dinners. Own the category conversation before the window closes: Rob predicts everybody will be talking about the semantic layer in enterprise AI within three years, if not sooner. He also acknowledges the loudest technology does oftentimes win, which makes owning that conversation early a strategic requirement, not a vanity project. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

    The head of AI who had never heard of an ontology | Rob Buller

  8. Aug 18

    Breaking into the twenty-year startup graveyard of mortgage lending | Naren Krishna

    Balerion AI is an agentic AI platform for mortgage loan manufacturing, automating origination work like document analysis, income review, and underwriting for lenders. The company came out of stealth this spring and is backed by a $6M seed round led by Kleiner Perkins, with its platform in production at FM Home Loans, a lender originating two billion dollars in annual loan volume. In a recent episode of BUILDERS, we sat down with Naren Krishna, CEO and Co-Founder of Balerion AI, to learn how the company is breaking into an industry he describes as a twenty-year startup graveyard. Topics Discussed: Why lending has been a startup graveyard for twenty years, and the three failure buckets Naren sees in past mortgage tech companiesWhy the cost to originate a loan went from about $4,500 in 2007 to around $13,000 in 2026 even as technology improvedWhy Naren argues the worst thing that happened to the mortgage industry was its vendors, with lenders using an average of 32 point solutionsHow 100 pages of guidelines became an 800-page PDF that changes every couple of months, and why people spend, not technology spend, absorbed the complexityThe stare and compare problem: multiple roles reviewing the same 800 pagesHow Balerion recruited by marrying AI talent, infrastructure talent, and lending expertiseWhat made FM Home Loans the right pilot partner, and how the case study opens the rest of the marketThe launch video that led to hiring a VP of sales off a LinkedIn likeHis color-coded framework for executive updatesHow the vision expanded from automated underwriting toward loan quality for capital and secondary markets GTM & Technology Adoption Lessons: Study the graveyard before entering it: Naren puts past mortgage tech failures into buckets: companies beholden to macroeconomic shocks because they served only one loan category, companies that forced their own UI or database onto lenders instead of living where underwriters and processors already work, and companies that never understood the distinct needs of independent mortgage banks, depository institutions, and the secondary market.Sell a generalizable system, not a point solution: Lenders use an average of 32 vendors for one manufacturing process, which means underwriters must learn the process, what each vendor does, and how to fill the gaps between them. Pick a pilot partner who already believes: FM Home Loans wanted a world where a mortgage application works like a credit card application, knew it lacked the in-house AI expertise to build it, and originates two billion dollars in annual volume across a broad mix of loan types. Buy credibility in relationship-based industries: Balerion's VP of sales has been in mortgage for decades and opens doors the technology alone cannot. In an industry where everyone claims AI, relationships get the meeting and the technology has to back up the claims.Marketing bets pay off in unpredictable ways: The launch video cost about ten grand and could not be tied to a tangible outcome, until someone liked the LinkedIn post about it and Balerion recruited them. Simplify communication to match attention spans: Naren color-codes executive updates green, amber, and red. Green means do not even look at it; red means you will get a call from me in four hours.Hire against the bet, not the present: Naren spends a quarter to a third of his time on hiring and posts JDs six months ahead of anticipated need, because finding the right person takes three to four months. // Sponsors: Front Lines -- Silicon Valley's leading Podcast Production Studio. We help B2B tech companies launch, manage, and grow podcasts that drive demand, awareness, and thought leadership. Mention you are a listener and get a 10% discount. www.FrontLines.io/Podcast-as-a-Service

    Breaking into the twenty-year startup graveyard of mortgage lending | Naren Krishna
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Ratings & Reviews

5
out of 5
6 Ratings

About

Welcome to BUILDERS — the show about how founders get new technology adopted. Each episode features a founder on the front lines of bringing new tech to market, sharing how they broke into their industry, earned early believers, built credibility, and unlocked real technology adoption. BUILDERS is part of a network of 20 industry-specific shows with a library of 1,200+ founder interviews conducted over the past three years. For the full network, visit FrontLines.io. Brought to you by:  www.FrontLines.io/FounderLedGrowth — Founder-led Growth as a Service. Launch your own podcast that drives thought leadership, demand, and most importantly, revenue.

Information

  • Creator
    Front Lines Media
  • Years Active
    2022 - 2026
  • Episodes
    942
  • Rating
    Clean
  • Copyright
    © Front Lines Media
  • Show Website
    BUILDERS

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