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Sunnyvale-based Brevian wants to make it easier for business users to build custom AI agents. Currently, the company is focused on support teams and security analysts — areas where both the use cases and training sets are well defined — but plans to expand to other areas over time. The company is coming out of stealth today and announcing a $9 million seed funding round.
Brevian, which styles its name as BREV/ΛN, was founded by Vinay Wagh (CEO) and Ram Swaminathan (CTO), who came to this startup journey from very different directions. Wagh was previously a product director at Databricks and the head of products at Bracket Computing. During his time at Databricks, he worked on getting the company ready to sell to large enterprises and then launch its serverless product, Databricks SQL Serverless. “That went GA in February, and I was looking at everything going on, Wagh said. “When I saw ChatGPT and other things, for me, it was just: how is this applicable in the enterprise? Instantly, our alignment was that all these missing pieces are going to be needed. There’s so much promise, but unless somebody solves this piece, it’s not going to work well. That was the inspiration to get out there — there’s stuff happening. And then I met Ram [Swaminathan] through a common friend.”
While Wagh worked a lot on the data side, Swaminathan’s background is on the computer science and machine learning side. After working in academia for a while, he spent nine years at Bell Labs and seventeen years at HP Labs, working on everything from coding theory to cryptography and early machine learning efforts. Then he went to LinkedIn, where he headed up the AI trust team before leaving in late 2022 to join Wagh in founding Brevian as its CTO.
“I didn’t really have a product sense,” he told me. “You write papers, you write patents — but can you really build a product that can impact a large number of people? And LinkedIn was a perfect target: go there, you help protect a platform that serves jobs and connections to people. That’s it. It’s a great impact on society. I really enjoy working with product people and engineering, and coordinate all these things and really create value.”
At the core of all enterprise projects around generative AI is security, the team argues. AI vendors need to ensure that no personal information leaks, for example. When the company launched, a lot of enterprises decided to ban ChatGPT inside their organizations because there was no way to guarantee that employees wouldn’t feed sensitive data into the chat prompts.
In its early days, Brevian focussed mostly on security. “We quickly turned around models that detect [personally identifiable information],” Wagh explained. “We noticed that this prompt injection attack vector was increasing, so we built an intent-based system to detect prompt injection. And so what we ended up doing at that time […] was collecting all the prompts that break alignment, and we ran a model across all of them and it was catching all of them.”
Interestingly, Wagh noted, that even today enterprises worry a lot about security in the context of large language models, but they don’t actually quite know what they are really worried about beyond these leaks. The real challenge, the team quickly realized, was that what was holding enterprise adoption back wasn’t actually so much security but the challenge of building systems that solved real problems for them.
“Our vision was to enable business users in the enterprise to be able to use AI to simplify their daily tasks. All of that fit in within the vision to expand from security and build these AI agents.”
Brevian’s seed round was led by Felicis partner Jake Storm (and this marks Felics’ largest seed round check yet). He noted that a year ago, everybody was talking about AI infrastructure, but few people were talking about applications — and the importance of securing those. “2023 was kind of [the year of ]AI infra. 2024 is the year of AI apps — and we just felt like they were so far ahead,” he told me.
With this funding round, Brevian aims to accelerate product development and expand its team to meet growing customer demand through its early release program.
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