From Pharma to AI with Ome Ogbru

In this episode, Ome Ogbru, founder and CEO of AINGENS, shares his journey from biotech professional to AI startup founder. 

He joins the Predictable Revenue Podcast to discuss the origins of AINGENS, its focus on narrative generation for life sciences, and the strategic steps taken to achieve product-market fit and grow the business.

The Common Failure Pattern

There’s a common pattern behind most early-stage failures, and it’s surprisingly consistent.

Founders build first, then try to validate afterward. By the time they start asking whether the problem actually matters, they’ve already invested months into a solution.

At the same time, they begin pouring effort into go-to-market. Hiring, outbound, paid channels, trying to “push” something that hasn’t yet proven it naturally pulls demand.

Underlying all of this is a quiet assumption: that demand exists.

So when growth doesn’t happen, the conclusion is predictable: we need better marketing.

But that’s almost never the real issue. If growth isn’t working, it’s not a marketing problem. It’s a product-market fit problem.

Start With Pain, Not Product

Strong startups don’t start with a product idea. They start with a problem that’s painful, specific, and already costing people time or money.

The mistake is starting with something like “AI for X.” It sounds compelling, but it’s too broad to anchor in anything real. There’s no clear user, no clear workflow, and no clear reason someone would switch.

What actually works is the opposite approach, zooming in.

• Not “AI for healthcare,” but this exact workflow is slow, manual, and breaking under pressure.
• Not “AI for biotech,” but teams are struggling to generate clear, evidence-based narratives from complex data.

That’s where AINGENS started.

Instead of building a generic AI layer for life sciences, they focused on a specific bottleneck: narrative and communication. Translating complex scientific data into structured, evidence-backed content was a repeated, high-friction problem, and one that existing tools didn’t solve well.

That level of specificity is what gives you something to validate.

Because when you start with real pain, not a broad idea, you’re not guessing whether demand exists. You’re stepping into it.

Go Deeper Than Surface Problems

Most founders stop at the surface.

They describe problems in broad terms (inefficiency, lack of automation, too much manual work). It sounds right, but it doesn’t go deep enough to be useful.

Real insight comes from understanding what’s actually happening underneath.

• What does the workflow look like step by step?
• Where does it break?
• What constraints are people operating under?
• What’s at stake if nothing improves?

That’s where the truth is.

Because a vague problem doesn’t create urgency. It doesn’t force change. It doesn’t justify buying anything new.

Specific pain does. When you can point to a broken workflow, real constraints, and meaningful consequences, the problem becomes tangible, and that’s what converts.

Do the Unscalable Work

Understanding your customer isn’t something you can delegate early on. It has to be earned firsthand.

That means doing the unscalable work. Founders need to be in the conversations, running discovery, closing the first customers, and manually validating whether the problem is real and whether the solution actually holds up.

It’s slower, and it doesn’t scale, but that’s exactly why it matters. 

This is where you learn how people actually think, how they describe their problems, what they’ve already tried, and what finally pushes them to act.

If you skip this, you’re not saving time. You’re building on assumptions. And those assumptions show up later as weak messaging, broken sales processes, and poor hiring decisions.

You can outsource execution. But you can’t outsource understanding your customer.

What PMF Actually Looks Like

Product-market fit isn’t a milestone you hit. It’s something you start to feel.

At first, everything is a push. You’re convincing people to take calls, explaining the problem for them, and working hard to justify why your product matters.

Then something shifts.

Customers start pulling the product instead of being pushed into it. The conversations get easier because the problem is already clear to them. You’re no longer selling the “why”, you’re discussing the “how.”

At the same time, the product begins to settle into real workflows. It’s not a nice-to-have or an experiment. It becomes part of how the work actually gets done.

That’s what early product-market fit looks like, not explosive growth, but reduced friction. Shorter sales cycles. Clearer demand. Less resistance.

And even then, it’s not a binary state you unlock once.

Product-market fit exists on a spectrum. You move closer to it as the pull gets stronger, the use cases get clearer, and the product becomes harder to replace.

Growth Follows Trust (Not Channels)

In complex industries, growth doesn’t come from channels. It comes from trust.

You can’t rely on aggressive outbound or quick-hit tactics when the stakes are high and the problems are nuanced. Buyers don’t make fast decisions, and they don’t take risks on unknown vendors.

Instead, credibility has to come first.

PR plays a role here. It signals legitimacy and positions you within the industry. Networking opens doors that cold outreach can’t, creating access to the right conversations. And over time, relationships become the foundation for actual deals.

This is how early growth happens, not through scale, but through trust compounding over time. Because in markets like biotech, pharma, and healthcare, trust is the growth engine.

Most mistakes in early-stage growth follow a pattern.

Founders try to scale before product-market fit, expecting go-to-market to compensate. But GTM doesn’t fix weak demand. It amplifies it. If the pull isn’t there, all you’re doing is scaling inefficiency.

• They hire salespeople too early, hoping someone else can figure out how to sell the product. But without firsthand experience, there’s no foundation to build on. Early sales isn’t a role you delegate, it’s how you learn.
• They keep their customer definition broad to avoid limiting the market. In reality, that lack of precision makes everything harder: messaging, positioning, and conversion all suffer when you’re not clear on who it’s for.
• They lean on tools and systems too soon, mistaking structure for progress. But without understanding the underlying process, tools don’t create clarity. They just mask the gaps.
• And they chase trends instead of problems, building around what’s hot instead of what’s actually broken.

All of this leads to the same place: motion without traction.

Conclusion

This all builds to a simple reality.

Product-market fit isn’t something you declare. It’s something you earn through depth of understanding, of problem definition, and of execution.

AINGENS didn’t get there by starting broad or scaling early. They got there by focusing on a real bottleneck, doing the work to understand it, and building around a problem that already had demand.

That’s the difference. Not better tactics. Not better tools. Better alignment with what the market actually needs.

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