Farshid Sabet has never been one to shy away from complexity. With a career that includes leading AI chip innovation at Movidius and managing multi-billion-dollar divisions at Intel, he’s seen firsthand the growing chasm between enterprise data potential and real-world usability. That gap is exactly what inspired the founding of Corvic AI.
“We realized that the way enterprises were trying to work with AI, especially across complex, multimodal data, was simply too fragmented and not scalable,” Sabet explains. “You’d have to stitch together different tools, hire specialists, and even then, many projects failed to deliver the insights people were promised.”
Founded in 2023 and headquartered in Mountain View, California, Corvic AI is on a mission to make deep, actionable insights from enterprise data not only possible, but practical.
Cracking the Code of Multimodal Data
Most enterprise data isn’t just text. It’s sprawling across formats: PDFs, databases, images, graphs, real-time sensor streams. LLMs excel at understanding language and work well with text, but fall short when tasked with processing this broader spectrum. Corvic’s response is its proprietary “Mixture of Spaces™” (MoS) framework, which enables each type of data to be treated in its native format.
“We don’t assume all corpus of data can be processed as text,” says Sabet. “Instead, we organize and elevate each data type, creating contextual relationships between entities within various complex data types and structures. That way, when large language models engage with the data, they’re not wading through noise, they’re being guided by structured clarity.”
Making Smart Data Workflows Adapt Like Architects
If MoS is about structuring data, Corvic’s “Adaptive Chain of Actions™” (ACoA) is about deciding what to do with it. Think of it as a data architect that changes blueprints based on what kind of house you want to build, or in Corvic’s case, whether you’re analyzing fraud in banking , evaluating efficacy of new drug compound against cells, assess vulnerabilities in a manufacturing supply chain etc.
“The tools, flows, and algorithms you’d use for each case will be very different,” Sabet notes. “ACoA dynamically assembles the right process for each situation, configuring and integrating expert tools behind the scenes.”
The Agent Behind the Curtain
Corvic also incorporates “Agentic Function Calling™,” a system that makes enterprise data digestible for generative models without overwhelming them. Rather than brute-force embedding and passing the bucket to specialized power hungry processors (which can lead to hallucinations, inefficiencies, high cost), Corvic focuses on preparing and curating the data so it’s contextually relevant and easy for AI agents to answer complex questions with high degree of accuracy and eliminating hallucinations.
Serving Enterprise Giants Across Industries
While still early in its rollout, Corvic is already proving its impact in sectors where complexity is expected such as:
- Financial Services: Anti-money laundering, fraud detection, KYC
- Healthcare & Life Sciences: Drug discovery, patient safety, genetics
- Industrial & IoT: Predictive maintenance, root cause analysis
- Retail & Consumer: Customer service automation, personalization
“We started with companies that had massive amounts of complex data,” Sabet says. “And the truth is, almost every large organization is sitting on this kind of data, it just hasn’t been usable until now.”
Lessons from Big Tech, Applied to Startup Scale
Sabet’s experience scaling companies from early-stage to acquisition and public offerings gives Corvic an edge not just in engineering, but in go-to-market strategy. “You find smart people, pick problems ten years ahead of the curve, and build for real long-term impact. That’s always been the formula.”
It’s a philosophy that’s helped shape the company’s focus on enterprise clients and their very real, very urgent needs.
What’s Next for Corvic?
Following a $12M seed round led by M Ventures and Bosch Ventures, Corvic is expanding its team, deepening customer deployments, and preparing for a broader market presence. The company is also beginning to tell its story more publicly, though Sabet remains focused on substance over hype.
“We’re not another wrapper around ChatGPT. We’re building core infrastructure that makes AI adoption actually work at scale,” he says. As enterprises race to turn data into decisions, Corvic AI plans to pave a smarter track.
