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Why Custom AI Wins the Healthcare Brand Intelligence Gap

  • Writer: Philipp Striebe
    Philipp Striebe
  • Jan 22
  • 6 min read

The case for building custom AI in Healthcare when the market offers nothing that fits


There's a moment in every strategic decision where you realize the off-the-shelf option will never work.


Not because it's poorly built. Not because the vendor is incompetent. But because what you're trying to solve doesn't exist in their roadmap and probably never will.


That's the moment I found myself in when building nunNEO, our proprietary brand intelligence engine for healthcare. And the research confirms what instinct already knew: when your problem is truly specific, generic tools become expensive compromises.



The Hidden Buyers Problem No One Is Solving


Let's start with what the data tells us about B2B buying, because this is where most brand measurement tools fail catastrophically.


Research from LinkedIn's B2B Institute and Bain & Company reveals something that should terrify anyone relying on traditional analytics: 50% of buying influence comes from "hidden buyers" who never appear in your CRM, don't download your whitepapers and couldn't care less about your product features.


These are the process experts (procurement, legal, finance) who hold veto power over deals worth trillions annually. The study of 515 B2B buyers across brands like Tesla, Pfizer and Kaiser Permanente found that only 4% of deals closed when just the recommending function knew the brand. But when the entire buying group was aware? 81% of deals went through.


Think about that. The difference between a 4% and 81% close rate isn't better product features. It's brand awareness across people you've probably never targeted.


Healthcare makes this worse. Buying committees in healthcare technology average 8.4 decision-makers. Medical device purchases involve regulatory affairs, clinical operations, IT security, finance and compliance, all before procurement even weighs in. The "hidden buyers" aren't hiding. We just never thought to look for them.


And here's where existing tools fall short: they measure clicks, track form fills and score leads. They optimize for the people already raising their hands while ignoring the silent majority who will ultimately decide your fate.



Why Off-the-Shelf AI Fails at Healthcare Brand Intelligence


McKinsey research confirms what practitioners already know: fewer than 10% of AI use cases deployed ever make it past the pilot stage. The horizontal tools, your generic copilots and plug-and-play platforms work fine for tasks that look the same across industries. But vertical use cases, the ones embedded in specific business functions, stall out.


Why? Because as McKinsey notes, these use cases "require custom development... teams are frequently forced to build from scratch, using emerging, fast-evolving technologies they have limited experience with."


The IBM 2024 ROI of AI study found that companies using open-source and custom AI tools were more likely to achieve positive ROI than those relying solely on off-the-shelf solutions (51% vs. 41%). The pattern is consistent: specificity pays.


Forrester research goes further, finding that organizations with custom AI architectures designed for their specific scaling patterns could accommodate 3.4x growth in data volume before requiring significant changes, compared to just 1.7x for organizations using configurable off-the-shelf platforms.


In healthcare, this matters enormously. The regulatory environment, the patient privacy requirements, the clinical language, the trust dynamics; these aren't edge cases you can configure around. They're the entire context.


Healthcare Brand Intelligence, Custom AI, nunNEO

The Market Gap That Made nunNEO Necessary


Here's what I couldn't find anywhere:


A brand intelligence tool that understands healthcare buying committees aren't just "larger than average". No, they're structurally different. Where clinical champions, IT stakeholders and C-suite executives operate on different timelines, speak different languages and fear different failures.


A system that recognizes brand familiarity is the most important factor in B2B purchasing decisions, according to LinkedIn and Bain's research, yet measures meaning rather than just mentions.


A platform that accounts for the 6sense finding that 84% of buyers pick a favored vendor before talking to sales, which means by the time you're pitching, the brand decision has already been made.


Existing tools measure campaigns. They don't decode why certain brands create collective confidence across buying groups while others (with objectively better products) get vetoed by someone in finance who "just doesn't feel good about them."


That feeling? That's the brand equity hidden in cultural markers, linguistic patterns and identity signals. That's what nunNEO is designed to surface.



The Commercial Case for Healthcare AI


The market timing isn't incidental.


The global AI in healthcare market was valued at $29 billion in 2024. By 2032, projections show it reaching $504 billion, a 44% compound annual growth rate. The U.S. market alone is expected to grow from $13.26 billion to nearly $195 billion over the same period.


But most of that investment flows toward clinical applications: diagnostics, drug discovery, surgical robotics. The marketing and brand intelligence space remains underserved, dominated by tools that treat healthcare like any other B2B vertical.


That's a mistake. According to 6sense's 2025 Buyer Experience Report, B2B buying cycles shortened from 11.3 months to 10.1 months, with buyers contacting sellers roughly 6-7 weeks sooner than in previous years. In healthcare, where regulatory approval, clinical validation and institutional procurement add months to any decision, brands that aren't on the Day One shortlist simply don't get chosen.


The research is unambiguous: in 95% of cases, buyers purchase from a vendor already on their initial shortlist. And that shortlist forms before any active research begins, built from memory, reputation and peer recommendation.


If your brand intelligence system can't tell you whether you're making that list and why or why not, you're flying blind.



Why Custom Beats Generic (When Your Problem Is Specific)


The cost argument against custom AI has always been straightforward: higher upfront investment, longer development timelines, uncertain ROI.


But the data tells a different story for organizations with specific, high-value problems to solve.


Three-year projections frequently favor custom AI despite higher initial costs. Custom systems eliminate recurring license fees that typically increase 20-30% at renewal. Enterprise deployments of generic tools often cost 3-5x more than advertised subscription prices after adding integration and customization.


More importantly, custom AI solutions become proprietary competitive assets. As Deloitte's State of Generative AI report notes, organizations have learned that "GenAI scaling and value creation is hard work", the majority acknowledge needing at least a year to resolve ROI and adoption challenges.


That investment period favors those building moats rather than renting capabilities.


H&M provides an instructive example: they began with generic AI chatbots, then eventually invested in their own enterprise AI platform, "Fountainhead," to gain flexibility and control. The pattern repeats across industries. Off-the-shelf tools serve as starting points; custom solutions become destinations.



What nunNEO Actually Does Differently


The inspiration for the name comes from a mythical being in the Cherokee folklore tradition, called the  “nuneihi”, spirit beings who reveal what's hidden. It felt right for a tool designed to surface the brand signals that existing analytics miss.


Where traditional tools count impressions, nunNEO decodes meaning. Where most platforms optimize for the buyer you've already identified, nunNEO maps the hidden stakeholders you haven't.


The core framework builds on the buyability research: when buyers are 20x more likely to purchase when the whole buying group knows the brand, brand investment becomes deal risk insurance. When 71% of buyers choose their first shortlist option, being on that list matters more than any subsequent pitch.


nunNEO doesn't replace the tools you already have. It provides the intelligence layer they're missing, the why behind the what, the meaning behind the metrics.



The Foundation Before the Facade


I didn't build nunNEO because I wanted to sell software. I built it because the problem I was trying to solve, helping healthcare brands understand how they're actually perceived across complex buying committees, had no existing solution.


The research validated the gap. The market timing made it urgent. The limitations of generic tools available made the insane adventure of a custom development necessary.


That's the real lesson here. When your problem is specific enough, building becomes the only responsible path forward.


The $500 billion healthcare AI market will be won by those who understand this. Not the companies with the most features, but the ones who solve problems no one else is addressing.


Sometimes the signal is clear. You just have to build the system that can hear it.




References & Further Reading


The State of B2B Buying & The "Hidden Buyer"

AI Strategy: Custom vs. Off-the-Shelf

Healthcare AI Market Projections


About the Author

With 10+ years of leadership experience across the healthcare landscape, from

medtech product management to global marketing strategy, Philipp Striebe has spent a decade navigating the complexities of the clinical and procurement labyrinths. As the founder of Sweep & Co, they built nunNEO to solve the specific intelligence gaps that generalist tools ignore, helping healthcare and healthtech brands transform market complexity into actionable clarity.


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