Building a software company on top of another business’s technology is a dangerous game. If you rely entirely on outside systems, you do not really own your product, and a competitor can copy your setup in an afternoon. To solve this exact problem, a vibe coding platform named Base44 just made a massive move. Only a year after Wix bought the startup for 80 million dollars, the young team is rolling out its very own custom artificial intelligence model to help users build applications using natural language.

This hardware and software shift comes at a time when software engineers and venture capitalists are fiercely debating whether massive foundation models are actually ideal for every single software task. A major question facing tech startups is how to protect their business over the long run when everyone uses the same underlying intelligence. Base44, which operates out of Tel Aviv, wants to answer that question by taking full control of its technology stack.

While the engineering team is still rolling out this custom large language model, the company hopes its internal software will eventually beat the performance of generalized foundation models. Meor Shlomo, the founder of Base44, explained that training and owning the model as part of their main product gives them the freedom to tweak the code. This setup allows them to make major improvements to processing speed, lag times, and operating costs.

At first glance, building a custom model looks like a smart strategy to stay ahead of fast moving rivals. For example, a Swedish software competitor named Lovable recently secured a high valuation by relying heavily on external language models. However, Shlomo expects other builders will eventually have to train custom models too, provided they grow fast enough to capture enough user data to feed the algorithms.

Jonathan Userovici, a general partner at investment firm Headline, pointed out that proprietary data serves as one of the three foundational pillars for protecting an artificial intelligence startup, alongside distribution networks and custom hardware setups. Because of this reality, brands with strong consumer recognition are moving fast to secure their information loops. Base44 trained the first version of its system, called Base1, on a custom dataset built from tens of millions of actual human interactions recorded directly on its software platform.

This internal data library will grow over time, but the startup faces massive pressure from giant competitors. The real threat is not coming from tiny coding apps. Instead, it comes from massive labs moving into the vibe coding space. For instance, Cursor and Grok’s parent firm, xAI, both have deep ties to SpaceX, while Anthropic’s Claude Code has quickly become a massive player in the automated programming market.

These massive foundation models have access to endless data streams, which they use to improve their programming apps continuously. However, Shlomo thinks specialized training gives Base44 a permanent edge. He predicted that while generalized foundation models will continue to improve, they will always remain too broad to handle niche programming tasks perfectly.

Userovici also warned startups not to underestimate the massive tech labs, pointing to legal tech platform Harvey, which recently scrapped its plans to train custom internal systems. While he does not expect every app developer to abandon mainstream foundation models, he notes that rising computer bills are forcing businesses to rethink their strategies. Enterprise clients are demanding better returns on their technology budgets, prompting firms to mix and match different models so costs do not skyrocket.

Building a proprietary model gives Base44 direct power over its computing bills, which should create a much healthier profit margin over time. This financial boost is excellent news for parent company Wix, which recently announced plans to cut its workforce by 20%. In contrast, Base44 has expanded its staff numbers and just crossed 150 million dollars in annual recurring revenue. The team remains completely focused on engineering custom software layers to stay ahead of the curve and maintain independent control in the fast-moving automated software market.