Vectara announces recent funding rounds totaling $53.5 million and introduces Mockingbird, a new large language model ideal for high-accuracy tasks in the health, legal, finance, and manufacturing industries.
Vectara, the trusted Generative AI product platform, has closed a $25 million Series A round led by FPV Ventures and Race Capital. Additional investors include Alumni Ventures, WVV Capital, Samsung Next, Fusion Fund, Green Sands Equity, and Mack Ventures. This funding round, combined with last year’s $28.5 million seed funding round, brings the total funding to $53.5 million, aimed at advancing the state of Retrieval Augmented Generation (RAG) as a Service for regulated industries.
With this funding, Vectara will advance internal innovations, ramp up its go-to-market resources and expand its offering in Australia and EMEA regions. As part of the round, Pegah Ebrahimi, co-founder and managing partner of FPV Ventures, will join Vectara’s board of directors.
“At FPV we want to partner with founders who are building technologies that address the opportunities and risks associated with generative AI,” said Pegah Ebrahimi, Co-Founder and Managing Partner of FPV Ventures. “There are specific challenges unique to enterprises when it comes to implementing LLMs that I saw first-hand as a former CIO, from accuracy to safety to cost. Vectara’s RAG-as-a-service is uniquely positioned to solve this, enabling anyone in any size enterprise to ship real value add use cases more efficiently.”
Introducing Mockingbird for RAG Technology
As part of its ongoing commitment to innovation, Vectara is excited to unveil Mockingbird, a new, fine-tuned generative Large Language Model (LLM) specifically designed for RAG applications. Mockingbird is engineered to reduce hallucinations and improve structured output, providing reliable performance with low latency and cost efficiency.
Combining Mockingbird with Vectara’s Hughes Hallucination Evaluation Model (HHEM) makes it particularly beneficial for regulated industries such as health, legal, finance, and manufacturing, where accuracy, security, and explainability are critical. As the demand grows for AI integration with downstream systems and the use of functional calls for autonomous agents, Mockingbird’s ability to produce structured outputs will be a significant advantage.
“Vectara’s new Mockingbird took HuckAI from being an overly polite librarian to giving answers I would expect from a senior coworker,” said Founder of HuckAI Sunir Shah. “The responses are clearer, easier to follow, and provide direct answers to difficult questions, helping our users get more work done. I switched immediately.”
Unlike general-purpose LLMs, Mockingbird is tailored to meet the specific demands of RAG, delivering superior performance and operational excellence. For RAG output quality, Mockingbird surpasses GPT-4 by 26% in Bert-F1, demonstrating its unparalleled capability. With faster performance, Mockingbird sets a new benchmark in operational excellence, integrating seamlessly within Vectara’s ecosystem and ensuring reliable performance and increased security without any third-party dependencies.
“The company’s push into models is an interesting move – others have been resistant to invest in an area well held by leaders like OpenAI. But it highlights limitations in both the high cost and genericism of the most performant public models and should put Vectara in a position to offer more control and deployment flexibility as the market demands it,” said S&P Global’s Melissa Incera. “Data from our upcoming Voice of the Enterprise: AI & Machine Learning, Infrastructure survey shows a year-over-year increase in organizations primarily deploying generative AI via end-to-end services and software providers as opposed to those building from scratch.”
The Pioneer of Retrieval Augmented Generation
“Retrieval Augmented Generation (RAG) has swiftly become a cornerstone of enterprise AI strategies. We are immensely proud to see Vectara being embraced by countless enterprise customers, machine learning developers, and prompt engineers. Vectara is on track to become the industry standard for RAG, especially for regulated industries, and we are thrilled to expand our support and investment in this journey,” said Alfred Chuang, General Partner at Race Capital.
AI hallucinations remain a critical concern across various industries, especially in regulated sectors. Vectara has already made significant strides in addressing this issue through its industry-first open-source Hughes Hallucination Evaluation Model and leaderboard, which thousands utilize to mitigate hallucinations. Mockingbird represents a significant advancement toward driving accuracy in AI-generated answers and minimizing the risks associated with hallucinations.
“The recent $25 million Series A funding will enable us to further innovate and expand our offerings, ensuring we continue to lead the way in trusted generative AI technology,” said Amr Awadallah, Co-Founder and CEO of Vectara. “With Mockingbird, we’re not just pushing the boundaries of AI trustworthiness; we’re empowering regulated industries to leverage reliable AI solutions with confidence, paving the way for a future where AI can be a dependable partner in mission-critical tasks.”
Several investors have returned to contribute to the Series A funding round, further proving their commitment to the vision and solidifying their view of the massive opportunity ahead for RAG. Early investors in Vectara include Race Capital, Databricks Ventures, Feld Ventures, GTM Capital, Fusion Fund, Top Harvest Capital, BECO Capital, Vertex, Essence, and Spark Labs. This funding brings the company’s total financing to $53.5 million.
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