The generative AI increase minted a startup a minute. However because the mud begins to settle, two once-hot enterprise fashions are wanting extra like cautionary tales: LLM wrappers and AI aggregators.
Darren Mowry, who leads Google’s international startup group throughout Cloud, DeepMind, and Alphabet, says startups with these hooks have their “test engine gentle” on.
LLM wrappers are basically startups that wrap present giant language fashions, like Claude, GPT, or Gemini, with a product or UX layer to resolve a selected downside. An instance could be a startup that uses AI to helps students study.
“If you happen to’re actually simply relying on the again finish mannequin to do all of the work and also you’re nearly white-labeling that mannequin, the business doesn’t have loads of endurance for that anymore,” Mowry stated on this week’s episode of Fairness.
Wrapping “very skinny mental property wrapped round Gemini or GPT-5” alerts you’re not differentiating your self, Mowry says.
“You’ve bought to have deep, large moats which can be both horizontally differentiated or one thing actually particular to a vertical market” for a startup to “progress and develop,” he stated. Examples of the deep moat LLM wrapper sort embrace Cursor, a GPT-powered coding assistant, or Harvey AI, a authorized AI assistant.
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In different phrases, startups can now not count on to slap a UI on high of a GPT and get traction on their product, like they might, maybe, in mid-2024 when OpenAI launched its ChatGPT retailer. The problem now could be to construct sustainable product worth.
AI aggregators are a subset of wrappers — they’re startups that mixture a number of LLMs into one interface or API layer to route queries throughout fashions and provides customers entry to a number of fashions. These corporations sometimes present an orchestration layer that features monitoring, governance, or eval tooling. Suppose: AI search startup Perplexity or developer platform OpenRouter, which offers entry to a number of AI fashions by way of a single API.
Whereas many of those platforms have gained floor, Mowry’s phrases are clear to incoming startups: “Keep out of the aggregator enterprise.”
Usually talking, aggregators aren’t seeing a lot development or development lately as a result of, he says, customers need “some mental property in-built” to make sure they’re routed to the correct mannequin on the proper time based mostly on their wants — not due to behind-the-scenes compute or entry constraints.
Mowry has been within the cloud sport for many years, reducing his enamel at AWS and Microsoft earlier than establishing store at Google Cloud, and he’s seen how this performs out. He stated the state of affairs right now mirrors the early days of cloud computing within the late 2000s/early 2010s as Amazon’s cloud enterprise began taking off.
At the moment, a crop of startups sprang as much as resell AWS infrastructure, advertising and marketing themselves as simpler entry factors that offered tooling, billing consolidation, and assist. However when Amazon constructed its personal enterprise instruments and prospects realized to handle cloud companies immediately, most of these startups have been squeezed out. The one survivors have been those who added actual companies, like safety, migration, or DevOps consulting.
AI aggregators right now face comparable margin stress as mannequin suppliers develop into enterprise options themselves, doubtlessly sidelining middlemen.
For his half, Mowry is bullish on vibe coding and developer platforms, which had a record-breaking yr in 2025 with startups like Replit, Lovable, and Cursor (all Google Cloud prospects, per Mowry) attracting main funding and buyer traction.
Mowry additionally expects robust development in direct-to-consumer tech, in corporations that put a few of these highly effective AI instruments into the palms of shoppers. He pointed to the chance for movie and TV college students to make use of Google’s AI video generator Veo to carry tales to life.
Past AI, Mowry additionally thinks biotech and local weather tech are having a second — each when it comes to enterprise funding going into the 2 industries and the “unbelievable quantities of knowledge” startups can entry to create actual worth “in methods we might by no means have been in a position to earlier than.”
