Gal Jacobi

The through-line

Jacobi's consistent argument is that generative AI in the visual domain is a "moonshot experiment to understand the entire visual domain in order to be able down to the pixel level understand it and then to disassemble and assemble it back again" [1], and that the discipline of building a company around such a vision lies in refusing to wait for the technology to mature. He is explicit that he and his co-founder are "truly committed to random sitting in the garage for two years," and that the alternative is to "slice and dice and to find the bits and pieces that are ready for productization and for commercialization and to generate impact true value to our customers and to do so now" [1]. Everything else follows from that tension: an enormous, long-horizon technical ambition paired with an insistence on measurable commercial impact in the present.

The second recurring note is that immature deep tech is de-risked through people rather than through more engineering. Partners, design partners, investors and co-founders are, in his account, the mechanism by which a speculative hypothesis becomes a validated one [1].

On building a company on unproven technology

Jacobi's diagnosis is candid: "generative ai is still perceived as an unmature technology" [1]. His remedy is twofold. First, find the right partners, "both in the investment community in the vc world obviously but also finding the right design partners to solve real problems," because a company's assumptions about the market are only ever "our current best assumptions" until they are validated, and "the only way to do so eventually is by generating impact to end clients" [1]. Second, accept that novel technology comes with an educational burden. In his framing there is "a need in our world to educate the market about the opportunities and also about the how to mitigate concerns when it comes to ethical eye generative ai and the opportunities that they both unfold" [1]. Ethics, for him, is not a separate compliance track; it is part of the same market-education work that creates demand.

On finding product-market fit for a horizontally broad platform

He treats breadth as a problem rather than a boast. Because Bria addresses "the entire visual domain" and "there are visuals everywhere," the platform "can generate impact to so many verticals in so many use cases for so many prime prospects," and Jacobi names this as "truly one of the biggest challenges that we face here at bria" [1]. His resolution is to pick a single point of leverage: what he calls the creative cycle, "the creation cycles of visuals and videos," and to reach it by integrating into existing processes and platforms rather than asking anyone to change how they work [1]. He describes Bria as an API-first or SDK platform and as "the world's first enterprise grade generative ai platform," plugging into digital content platforms "wherever there are templates that need to be enriched with visuals," including website building, presentation building, email personalization and video creation, alongside work with the world's largest image banks and creative agencies, plus e-commerce and performance marketing [1].

On replacing the camera, and what that actually means

The line about replacing the camera is one Jacobi both uses and immediately qualifies. Pressed on it, he says "it's not a mission it's just a demonstrator of potential capabilities" [1]. His distinction is between the two jobs a photograph does: capturing a memory, which he has no intention of touching, and conveying a message, where "we can be a force multiplier" [1]. He puts it plainly: "my wife is a photographer she's an artist we're not replacing the canon" [1]. What the technology does instead is democratize creation, so that "conveying a visual message is no longer only to professional photographers or to digital creators or to professional graphic designers," by removing "all of the barriers the complexity the cost the creative skills that some of us potentially lack" [1]. The company name carries the same idea; he explains that Bria comes from the Hebrew for creation, and that enabling creation from scratch "is what it is eventually all about for us" [1].

On founding at the intersection of your own experience

Jacobi is careful not to generalize, saying he does "not feel that i should necessarily be the one giving advices," but he is clear about what mattered to him: "it was indeed important to solve problems that i personally faced and to make an impact in domains that i think that i understand in" [1]. He describes Bria as sitting at the intersection of three strands of his own career, having led cutting-edge computer vision projects, come from a marketing background that exposed him to "the pains and opportunities in the creative and the marketing in the product world," and worked at AI-leading companies, which "completes the triangle" [1]. Pairing that with a co-founder he calls "a computer vision rockstar" made the target obvious to both of them: impact in organizations via the visual domain [1].

On partnerships as the founder's real lever

Two pieces of advice recur. The first is motivational honesty: "you should enjoy the journey it is an incredible journey but a bumpy one with ups and downs eventually the driver should be intrinsic it can't be just about the money or the potential money statistically the odds are against us" [1]. The second is that founders "should optimize for partnerships," choosing partners carefully for what they add rather than for their name, specifically people "that can generate added value they can push back that can challenge us" [1]. He calls this "one of the potential secret sauces for potential success" [1]. What he values in an investor is less capital than mentality and reach: "the scale the reputation the resources but mainly the the state of mind the founders mentality that understand funders that have the experience and the benchmark" [1]. He describes the practical payoff in concrete terms, that when the team wanted "to validate hypothesis to speak with a potential client," a warm introduction could arrive "within two phone calls and less than sometimes less than 24 hours" through the network [1]. He also cites Reid Hoffman and the Masters of Scale podcast as a source of inspiration, valuing it as "user-friendly digestible short" and eye-opening [1].

Takeaways

• Treat an immature technology as a sequencing problem: identify the pieces ready for productization now rather than waiting years for the full vision to mature [1].
• Design partners are the validation mechanism for deep tech, because assumptions only become knowledge through impact delivered to end clients [1].
• Market education for generative AI has to cover ethical concerns and commercial opportunity together, not separately [1].
• A horizontally broad platform needs one concrete point of leverage; Bria's is integration into the creative cycle via an API-first, SDK-based enterprise platform embedded in existing content, e-commerce and marketing workflows [1].
• The camera-replacement framing is a demonstrator, not a goal: memories stay with photographers, message-conveying visuals are where automation acts as a force multiplier [1].
• Choose investors and co-founders for state of mind, challenge and network access rather than reputation alone; this is described as a secret sauce for potential success [1].
• The motivation to found must be intrinsic, because "statistically the odds are against us" [1].