Vibe coding platform Base44 launches own model as AI startups seek defensibility
Wix-owned vibe coding platform Base44 has started rolling out its own AI model — with hopes that it will eventually outperform frontier models.
Base44 , the vibe coding platform that Wix acquired for $80 million just one year ago — when the company was barely six moths old and had a team of eight — has started rolling out its own AI model to support its users in creating apps with natural language.
The move comes as the discussion in AI circles has intensified over whether frontier models are best suited for all use cases. A related question is whether businesses built on top of someone else’s models are truly defensible long-term. The latest move of Base44, based in the Bay Area, speaks to both.
While its custom LLM is only just rolling out, Base44 hopes that it will eventually outperform frontier models. According to its founder, Maor Shlomo, “training and owning the model as part of [our] entire stack allows us a lot more optimizations on latency, cost, and efficiency.”
At first glance, this could be a way to stay ahead of competitors such as Swedish startup Lovable , which reached unicorn status in its Series A round last summer and that relies on external LLMs . However, Shlomo expects that others will train their own models — “at least the players that have gotten enough scale and velocity to have enough data.”
According to Jonathan Userovici, a general partner at VC firm Headline — whose portfolio includes AI companies like Mistral AI, but not Base44 — data is one of three key ingredients of defensibility for AI startups, alongside distribution and tech stack.
The upshot is that players with strong brands are now leaning into their data and infrastructure to increase their defensibility, and Base44 fits that pattern. The company says the first iteration of its LLM, Base1, was developed and trained on a dataset generated from “tens of millions of real user interactions on the platform.”
This dataset will keep on growing with the company; but so will its rivals’. The bigger competition may not be vibe-coding startups at all but instead come from frontier AI labs that are getting closer to Base44’s home turf — Cursor and Grok’s parent company xAI now both belong to SpaceX , and Claude Code has become a vibe coding player in its own right.
This gives Anthropic and other foundational AI providers access to data and feedback loops they can use to improve models for app creation, but Shlomo thinks specialization gives Base44 a leg up. “Models are progressing, but they’ll stay very general in what they can do,” he predicted.
Userovici, for his part, cautioned against underestimating frontier models, citing the example of the legal tech startup Harvey, which abandoned plans to train its own model. He doesn’t expect applied AI companies to become frontier labs en masse but frames Base44’s move in a broader context — one in which inference costs have become a meaningful part of the equation.
That cost pressure, Userovici says, has driven change that enterprise customers are now demanding. “They don’t necessarily see a [return on investment] when using the latest models for all use cases, so an entire infrastructure is being set up to do orchestration and optimization to select the right models for them so that costs don’t skyrocket while maintaining the same or similar performance across the majority of use cases.”
Enterprise companies still are a minority among the audience of the vibe coding platforms, but they represent a growing share of platform revenue, and users of all sizes are starting to express concerns over the cost of using AI. Base44’s decision to develop its own LLM stemmed from multiple factors, but cost reduction is likely among the benefits.
“We want to get a model that is going to be more aligned to what we think is the right thing, is going to be more optimized to what we see users like in terms of the results we’re getting, and is going to be faster and cheaper for customers eventually than using the frontier models like Opus,” Shlomo said.
As for Base44 itself, cost reduction isn’t as clear cut. In a press release, the company explained that “ownership of the model gives Base44 direct control over compute and inference spend, expected to result in a structurally stronger margin profile over time.”
Even with a delayed payoff, improved margins would be good news for Base44’s parent company, which recently announced it would lay off 20% of its workforce . In contrast, Base44 has been growing in headcount since the acquisition — and announced it had passed $100 million in annual recurring revenue a few months ago.
That’s still less than Lovable, which said it hit $500 million in ARR earlier this month . But Shlomo is betting that the “huge engineering effort” to develop Base1 will cement Base44’s positioning as the “only vertically integrated vibe-coding application — meaning, in Userovici’s terms, a player that owns its distribution, data, and infrastructure all at once.
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Key takeaways
- Base44 aims to enhance its defensibility by developing its own AI model, reflecting a growing trend among startups.
- Specialization in AI models can provide a significant competitive advantage in a saturated market.
- Effective use of data collected from real user interactions is crucial for the evolution and continuous improvement of AI models.
Editorial analysis
Base44's initiative to develop its own AI model reflects growing concerns about startups' reliance on third-party models, especially in a landscape where defensibility is crucial. For the Brazilian tech sector, this move can serve as a wake-up call for local companies still utilizing AI models from major providers. The ability to train and optimize an in-house model not only provides a competitive edge but also allows for greater control over costs and efficiency, essential factors in an increasingly competitive market.
Moreover, Base44 is strategically positioning itself in a niche that may be less vulnerable to competition from large AI labs, such as Anthropic and xAI, which have access to vast datasets and resources. This specialization could be an important differentiator, especially in an environment where personalization and adaptation to user needs are increasingly valued. For Brazilian startups, this may mean the need to invest in their own infrastructure and data collection strategies to ensure their relevance in the future.
Finally, the evolution of Base44's Base1 model, which feeds on real user interactions, highlights the importance of continuous feedback in improving AI models. This suggests that companies that not only collect data but also use it effectively will be in a stronger position. What we observe is a movement towards an ecosystem where ownership and control of data become increasingly essential for the survival and growth of tech startups, both in Brazil and globally.
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