Two Google alumni raised $11.3 million to back early-stage AI startups. Founders Bontia Stewart and Jackson Georges Jr. started BAG Ventures to help companies that enterprises will actually pay for. Georges said, "Enterprises are dialing in heavily on the unit economics right now." They already backed 10 firms using this fund.
Two Google alumni have closed an $11.3 million fund to back early-stage AI startups, betting that the era of enterprise AI experimentation is ending and that customers will increasingly pay only for products that prove their worth.
BAG Ventures, founded by Bontia Stewart, a former Google vice president, and Jackson Georges Jr., a former CapitalG partner, closed the fund after about two years of investing from it as it came together. The firm has already backed 10 companies, including the software company SXD, the AI travel agent BizTrip, and the agentic reasoning platform Nomadic.
It invests in startups in areas like AI infrastructure, compute, physical and edge AI, security, governance, and vertical SaaS. Check sizes range from $100,000 to $500,000, and the team hopes to invest the rest of the fund over the next two years.
Stewart spent 17 years at Google, including nearly a decade as a vice president. During that time, she also served on the board of Gradient Ventures, Google's early-stage AI fund. She is a limited partner in the Female Founders Fund and the Operator Collective. With Georges, she also co-led the angel syndicate BAG Collective, which has more than 450 members.
Georges worked at GE Healthcare and at Google, where he met Stewart. He later became a partner at CapitalG, Alphabet's growth fund. He and Stewart were in the first cohort of the Black Venture Institute at Berkeley.
The pair say their edge is access. They launched BAG Ventures to "address the emerging AI divide between founders and operators," Georges said.
"Founders needed inside access to the organizations they wanted to sell into, and we knew so many high-level operators who wanted to support early founders but didn't know how," he said. As a result, "we don't just give founders capital; we give them direct warm introductions to potential customers and hands-on [go-to-market] advice," he continued, adding that the firm, whose limited partners include Google, as well as operators from Nvidia, Amazon and Snowflake, has more than 150 limited partners altogether at a wide range of companies.
"Lots of firms have an operator network," Georges said. "We want to be one that's genuinely useful."
Georges's investing thesis rests on a shift he sees in how enterprises buy AI. He said the "experimental sandbox" phase is ending. "Enterprises are dialing in heavily on the unit economics right now," he noted. "They aren't just paying for open-ended chatbots anymore; they are paying for deterministic solutions. The real value is coming from solutions that integrate deeply into legacy workflows and actually execute the work." Examples include automating code reviews and parsing legal documents.
Georges is preparing for a world where enterprises no longer buy per-user seats for SaaS tools. "We'll be buying completed jobs and outcomes driven by multi-agent workflows," he said.
Toward that end, BAG Ventures wants core technical teams that have worked together before, have a minimum viable product and at least one partner, and have "a very clear path to monetization within 24 hours."
He also wants to back founders building products that go deep into enterprise workflows and capture proprietary data that can't be scraped. With frontier AI labs launching more products themselves, not even a technically sound product from a startup is enough to succeed in the long run otherwise, he observed, and "if a startup is just a thin wrapper around a frontier model API, they're going to get wiped out." It's why they look for teams building products that go deep into enterprise workflows and capture proprietary data that can't be scraped. "We want companies that own the intent layer and have the customer lock-in to survive the next big model release."
The firm is also looking at startups selling into highly regulated industries, where data privacy needs may require specialization. "That means securing internal data flows, building acceptable-use guardrails, and deploying continuous automated red-teaming," said Georges. "We're already seeing this approach work well with our portfolio company Defendremate."
Georges also said enterprises will need Identity and Access Management tools for non-human workers, like AI agents. "Startups that can build the next level of 'zero trust' architecture and orchestration rails specifically for agentic systems are going to fill a massive and very lucrative gap," he said.
