Cognizant is a global technology services company that invests heavily in research-driven thought leadership, publishing studies on AI, cybersecurity, and the future of work that reach audiences from LinkedIn newsletters to Davos.

In a recent episode of BUILDERS, we sat down with Marlowe Newman, Director, Thought Leadership of Cognizant, to learn how B2B technology brands are shifting from the attention economy to the authority economy, and how research-driven content earns buyer trust at both ends of the funnel.

Topics Discussed:

• Why B2B tech is moving from the attention economy to the authority economy
• Why "all press is good press" no longer holds in B2B technology marketing
• How AI removed the friction that once made long-form content a competitive moat
• Why a clear, differentiated, human-produced point of view is now the core thought leadership asset
• How to identify and activate in-house subject matter experts, including those who avoid the stage
• What Marlowe's buyer journey research at Gartner revealed about how software shortlists actually form
• How Cognizant balances societal-level studies like AI and the future workforce with service-line research in cybersecurity, healthcare, and retail
• Why researchers, not CEOs, should front research-driven media pitches

GTM & Technology Adoption Lessons:

• Shift from attention to authority: Marlowe argues the race for attention at any cost is over in B2B. Audiences have grown savvy about opportunistic content, and bad press now costs more than obscurity. Trust and demonstrated expertise are the assets that compound.

• Volume is no longer a moat: The old playbook was to flood the zone and game the Google algorithm with content volume. Marlowe notes the barrier to entry was effort, since nobody wanted to grind out a fifteen hundred-word article, and AI made that barrier vanish. What remains defensible is a differentiated, human-produced point of view backed by proprietary research.

• Thought leadership works both ends of the funnel: At Gartner, Marlowe studied how software buyers form shortlists. Most could not pinpoint where they first heard of a vendor, but they arrived with three to five companies in mind. At the bottom of the funnel, buyers loop back to the same research to justify the purchase to whoever signs the purchase order.

• Time research to land ahead of the market: Quick pulse polls fielded over a couple of weeks produce rich, unique data sets. The planning question is not what buyers face today but what they will face in two months when the report ships. If the topic is current now, it is already too late.

• Match the expert to the format: Willing spokespeople come first. Experts who are not stage-ready can still write bylined articles, and podcasts let people who avoid cameras talk all day in one on one conversations. There is a format for every kind of expert.

• Platform the researchers: Pitching a big study with a CEO quote gives reporters pause because CEOs do not have time to run giant studies. Media want to go a few layers deeper with the people who dug through the data. Letting researchers speak is how a brand transmits authenticity in a market saturated with manufactured versions of it.

• Place bets across a fractured media landscape: A New York Times placement no longer reaches everyone who matters. Societal-level studies earn mainstream coverage, while problem-solution research belongs in trades, LinkedIn, podcasts, and niche media. Both audiences consume different media diets, so both bets are necessary.

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Pennylane spent its first two years operating an accounting firm to experience the workflows it intended to fix. It then sold the profitable business, removed the channel conflict, and went all-in on software. After three years of deliberate customer development, growth accelerated to more than one million SMEs on the platform. In this episode of BUILDERS, Tobias Janiesch, Managing Director - Germany at Pennylane, breaks down the accountant-led distribution model, the trust-building behind its growth, and why entering Germany required both a product rebuild and a startup-style local team.

Topics Discussed:

• Why Pennylane operated—and then sold—its own accounting firm
• How accountants became the channel behind roughly 95% of leads
• The customer sequence behind Pennylane's growth inflection point
• Using founder-led roadshows and peer referrals in a trust-driven market
• Why Germany offered a four-year window but required a 40% product rebuild
• Giving a local team startup autonomy inside a scaled company
• Building embedded AI on a unified financial data layer

GTM Lessons for B2B Founders:

• Make the channel successful before asking it to distribute: Pennylane saves accountants 30–40% of their time and gives them a workspace their clients use. The accountants then invite the SMEs; approximately 95% of leads originate through them. The channel works because the product improves the partner's own economics.

• Earn the right to move upmarket: Pennylane first made 20 digital-first firms successful, expanded to the next 50, and used each cohort to uncover edge cases. Only then did it pursue larger firms. The first flagship customer helped turn three years of steady growth into rapid acceleration.

• Enter conservative markets through the progressive edge: Pennylane started with accountants already running digital firms. Their recommendations in WhatsApp, Facebook, and professional communities transferred trust to more cautious peers. Identify the insiders whose credibility can bridge the adoption gap.

• Localize the product and the operating model: Germany could reuse roughly 60% of the French product; 40% required rebuilding around local rules. Pennylane added German accounting expertise early and let the local entity operate like a startup, using lightweight tools before institutionalizing systems such as Salesforce.

• Turn trust into operating metrics: The founders avoided promising features they could not ship and reviewed commitments against delivery each year. In Germany, the team measures real activation through monthly VAT submissions and expects no early churn. Track recurring workflow adoption—not logins or account creation.

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Don't Miss: New Podcast Series — How I Hire

Senior GTM leaders share the tactical hiring frameworks they use to build winning revenue teams. Hosted by Andy Mowat, who scaled 4 unicorns from $10M to $100M+ ARR and launched Whispered to help executives find their next role.

Subscribe here:
https://open.spotify.com/show/53yCHlPfLSMFimtv0riPyM

SafetyWing is building a social safety net for people who live, work, and travel across borders — covering health insurance, income protection, disability, and life insurance that follows you around the world. The company was founded in 2017 and has insured over 400,000 people through its consumer products. Its Trustpilot rating sits at 4.3 stars. Its NPS score is 10x the insurance industry average.

In a recent episode of BUILDERS, we sat down with Joey Flores, Head of Marketing at SafetyWing, to learn how a nine-year-old company built category leadership in global health insurance by rejecting fear-based marketing and betting on an aspirational brand identity.

Topics Discussed:

• How SafetyWing builds trust across a product category where customers hope they never need the product
• Why SafetyWing uses cartoon birds instead of the fear-based visual language that defines traditional insurance
• How "create, don't copy" shapes every marketing and brand decision at SafetyWing
• Why the company launched a US-specific team health plan after years of global-first products
• How SafetyWing is using AI to compress the time between claim submission and resolution
• The ambassador program featuring extreme adventurers and what it reveals about SafetyWing's brand strategy
• How the brand's distinctiveness shortens the customer recognition path in a crowded market

GTM and Technology Adoption Lessons:

• Brand distinctiveness as adoption infrastructure: Joey said the cartoon birds create a shortcut. "the birds are just so damn memorable, like, you don't expect it from an insurance company."

• Aspirational branding in a fear-driven category: Traditional insurance marketing creates urgency through fear of loss. SafetyWing chose the opposite. Joey explained: "We don't think of ourselves as an insurance company. We're building a social safety net that follows people all around the world, literally with the mission of empowering them to go wherever they want, safely, securely, and feel like if something does happen, they are covered."

• Trust has to be rebuilt with each new product: SafetyWing's 4.3 Trustpilot score and 10x industry NPS are earned on existing products. But when the company launched income protection, Joey noted: "when we, when we roll out new products, for example, there's a bit of like doing that again, right? Like, okay, I trust you with my health. But like, you know, our newest product has income protection.

• Create, don't copy as a design constraint: When redesigning the homepage, the team came in with a standard three-plan pricing layout. A founder pushed back. Joey said: "every landing page I've ever been on has three plans next to each other. And the goal is always that you pick. The consumer will pick the middle plan... I was like, this is just like, I'm so tired of seeing this.

• Ambassador programs as brand proof: Sponsoring Ria G., who is running 20,000 km from China to Portugal, completing her 66th consecutive ultra marathon at the time of recording, is not a traditional brand awareness play. It is a live demonstration of what SafetyWing makes possible.

• AI for claims process improvement: SafetyWing deployed AI to flag missing claim documents at the point of submission rather than days later after human review. Joey described the practical impact: "it doesn't just shorten it by the two days it took a human to review it, it may shorten it by the two weeks that they would have waited to sit down again and do it."

• US expansion as a distinct product bet: The global team health plan has been running for years. The US plan launched at the start of 2026 because US healthcare operates in a different regulatory and pricing environment.

// 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

Labrynth is an outcome-based AI regulatory intelligence platform that helps regulated entities accelerate permitting, compliance, and licensing workflows. Stuart Lacey, CEO and Founder, built the Red Tape Index as a free, unpaywalled public resource measuring regulatory burden across U.S. jurisdictions and expanding globally. He used it to create inbound pipeline, earn mainstream media coverage, and demonstrate the company's core thesis: give the market something useful before asking it to give you anything back.

In a recent episode of BUILDERS, we sat down with Stuart Lacey, CEO and Founder of Labrynth, to learn how his team generated tens of millions of impressions, a direct call from the mayor of Washington D.C., and coverage from Bloomberg to Fox News with no paywall and no sales outreach, and why deterministic AI is the only model that works in regulated compliance environments.

Topics Discussed:

• Why Stuart built the Red Tape Index as a free, public data resource with no paywall
• How the index generated tens of millions of impressions and mainstream media coverage
• The story of Mayor Bowser calling Labrynth directly after D.C. ranked 508th
• What it costs to build and launch your own industry index (approximately $50K, approximately 8 weeks)
• How Labrynth reduced LA County permitting from 188 days to 20 using AI
• Why probabilistic AI fails in regulated environments and how hermeneutical agents fix it
• How Labrynth structures outcome-based pricing and when clients push back to per-transaction
• The three differentiators behind Labrynth: outcome alignment, self-improving backend, high trust

GTM and Technology Adoption Lessons:

• Give value publicly before asking for anything in return: Stuart built the Red Tape Index with no paywall and free data access for anyone. The Data Center Readiness Index launch generated 10 million impressions in under a week, 18,000 full print media replays, and a 14.75% click-through rate.

• Use data to create gravity: The Red Tape Index works because it turns anecdotal regulatory pain into measurable, comparable data. That data becomes a conversation starter, a competitive lever for cities, and a trust signal for enterprise buyers. Mayors call. Media covers it.

• Index economics anyone can replicate: Building an index costs approximately $50K and takes about 8 weeks, including data scraping, actuarial science methodology, build, go-to-market, publishing, support, and follow-on. Stuart's point: "I think if you're a mid sized to large size company, you're probably blowing that money on party and marketing right now with no direct return on it.

• Deterministic AI is the only viable AI for regulated environments: Most companies deploy probabilistic AI in compliance and regulatory contexts, which by definition only "probably" gets the right answer. Labrynth uses hermeneutical agents, which Stuart describes as "role context specific deterministic agents that can actually define whether or not something is actually correct and then measure the difference between right and wrong and then help you get it right."

• Outcome-based pricing creates trust but sometimes clients ask to exit it: Labrynth prices against client outcomes, not seat licenses. Stuart noted that in about half of cases, after seeing what the platform delivers, the client's finance team comes back and asks to revert to regular pricing.

• Output-based AI pricing is a trap: Stuart specifically pushed back on the output-based pricing model gaining traction in AI services. "I would put a cautionary note there to anyone that's kind of thinking that through Brett, output based might mean that volume matters.

// 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

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 rates
• Why neither co-founder was technical, and how Ria learned Python and PySpark to ingest 300 billion row machine readable files
• How an NIH grant and a free consumer cost estimator revealed the wrong initial customer
• Why Handl Health moved past direct-to-employer sales to the broker and benefits consultant channel
• Where brokers see value first: prospecting new business with carrier comparisons and personalizing renewals with claim-level cost projections
• The three-year education arc from explaining what an MRF is to a market where everyone needs a price transparency partner
• How Handl Health escaped the checkbox compliance perception by layering actuarial modeling and steerage on top of public data
• Why 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.
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• 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

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 misconception
• Who owns AI visibility inside enterprise marketing departments, and why Brandlight always starts from the CMO
• How Brandlight answers skeptics who claim AI engine results cannot be influenced
• The advisory board of Fortune 50 CMOs and agency CEOs that opened enterprise doors from day zero
• Why enterprise AI visibility programs require orchestrating close to a hundred stakeholders
• How the education burden in first CMO conversations disappeared between late 2024 and today
• What happens to SEO, brand, legacy search, and Google as search shifts into AI engines
• Reddit'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.

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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 travel
• Why John shut down his first startup, Card Curator, and how that experience led to founding Odynn
• How Built Rewards became Odynn's first customer and what they saw that other banks had not yet recognized
• How the market shifted from requiring heavy customer education to prospects who arrive already understanding the problem
• Why US customers immediately understand the cardholder retention problem while European markets require more education
• Where the term "embedded travel" came from and how Odynn uses it to define the category
• The critical marketing decisions John made to reach six different types of buyers
• How Odynn structures its approach across personal banking, business banking, BaaS, credit card affiliates, card issuers, and corporate travel management
• What selling to tier-one banks actually looks like in terms of sales cycle length
• What John learned transitioning from direct-to-consumer to enterprise financial institution sales
• Tactics that have helped shorten long enterprise sales cycles
• Advice 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.

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 campuses
• Why laundromats generate durable cash flows -- 30% margins, 20-plus year equipment lifespans, and leases that can outlive their operators
• How 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 underserved
• How trade shows became Cents's "Super Bowl" and why they staffed booths 25 to 50% heavier than planned
• The tension between brand building and product credibility in SMB tech, and the question operators ask when they see a high-profile marketing spend
• Why the laundromat business is "a highly services-based business" despite appearing commoditized on the surface
• How 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

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 exploited
• Why exposure management is still an unsolved problem after three decades and how the category has evolved through five generations
• Why early GTM in cybersecurity is built entirely on relationships and CISO trust
• How 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 Security
• The "mailbox money" channel model where partner sellers identify opportunities and hand off to Onit Security's sales team
• Why spreading marketing risk across field marketing, brand, digital, social, and employee evangelism is the right approach at the early stage
• How a branding agency investment Elad almost didn't make became one of the best decisions in the company's history
• The VC defensibility question: how Onit Security is building its moat as frontier AI models expand into adjacent markets
• Why 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

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 contracts
• Why SimpliFed enters health plans bottoms up through the provider credentialing page rather than selling as a vendor
• Why the company moved away from a large commercial team and built a credentialing team instead
• How integration into the 28-week prenatal order set inside OB electronic medical records became the growth engine
• The three-legged stool behind SimpliFed's growth: patient demand, health plan coverage, and referral partners
• Why SimpliFed spent three years on a clinical study with UMass
• Current coverage: roughly 50% of commercial health plans, Medicaid in 12 states, all 50 states commercially, and two national TRICARE contracts
• What 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