The artificial intelligence platform provider announced the opening of its San Francisco office at 575 Market Street, marking a strategic expansion that positions the company closer to Silicon Valley’s technical talent pool and AI research ecosystem. The move coincides with the appointment of Aabhas Sharma as Chief Technology Officer, a hire the company describes as critical to scaling its next generation of product and engineering capabilities. The dual announcements from Hebbia reflect a broader pattern of growth for the New York-based company, which has recently completed several high-profile acquisitions and partnerships that extend its platform’s capabilities across financial services workflows.
Strategic Positioning in the Bay Area
The decision to establish operations at 575 Market Street places Hebbia within one of technology’s most concentrated innovation hubs. According to a recent blog post on Hebbia’s website, the Bay Area location offers proximity to leading AI research laboratories and a deep pool of engineering talent. The expansion addresses three operational priorities: maintaining direct access to emerging AI breakthroughs, recruiting from Silicon Valley’s technical workforce, and strengthening relationships with investors and financial institutions across the region.
Hebbia serves over a third of the largest asset managers by assets under management. The platform has found adoption among prestigious firms, including BlackRock, KKR, Carlyle, and Centerview Partners, as well as government agencies such as the U.S. Air Force. The AI-powered platform raised $130 million in Series B funding in July 2024 at a valuation of approximately $700 million, led by Andreessen Horowitz with participation from Index Ventures, Google Ventures, and individual investor Peter Thiel.
The San Francisco office represents the company’s effort to combine what executives describe as Wall Street’s market opportunity with Silicon Valley’s technical capabilities. This geographic strategy positions the firm to serve financial institutions while drawing from the region’s concentrated AI expertise.
Leadership Addition: Aabhas Sharma Joins as CTO
Sharma brings extensive experience scaling technology organizations across multiple industries. Prior to joining Hebbia, he served as Chief Technology Officer at Found, a financial services platform serving self-employed professionals throughout the United States. His tenure at Found began in May 2021, where he initially served as Head of Engineering before being promoted to CTO in April 2022.
Before Found, Sharma held director-level engineering positions at Uber and Postmates. At Uber, he directed engineering teams responsible for maintaining one of the world’s largest global marketplaces. His experience at Postmates, where he worked for several years before the company’s acquisition by Uber in December 2020, included roles spanning from software engineer to director of engineering, product, and design. Sharma holds both bachelor’s and master’s degrees in computer science from Purdue University.
According to Sharma, his decision to join followed a year-long evaluation process where he examined Hebbia’s metrics, customer base, technology infrastructure, and strategic vision. He described the thoroughness of this process as similar to his previous career transition to Found, where he joined as one of the first ten employees and helped scale the company from Series A through Series C funding rounds.
Sharma will oversee both technology and product development. His responsibilities include expanding the engineering, product, and design organizations, which the company plans to double over the next year. Hebbia recently announced it processed more documents in a single month than in its entire previous history, indicating the scale of technical challenges ahead.
Recent Acquisitions and Strategic Partnerships
The San Francisco expansion and executive hire occur amid a series of strategic moves that broaden the platform’s capabilities. In June 2025, Hebbia acquired FlashDocs, a startup specializing in automated slide deck generation. Founded in 2024 by Morten Bruun and Adam Khakhar, FlashDocs processes over 10,000 slides daily, transforming structured outputs into enterprise-quality presentations within seconds.
The acquisition expanded the platform beyond information retrieval and analytical workflows into content generation. FlashDocs co-founders now lead API business development and artifact generation initiatives, enabling the platform to automate the creation of investment memos, board presentations, and diligence summaries. This addresses what CEO George Sivulka called the “last-mile” problem, where insights extracted through AI analysis previously required manual reformatting into client-ready deliverables.
The company has also established several data integration partnerships. In July 2025, Hebbia announced a collaboration with Third Bridge, a global expert network providing market intelligence to investors. The integration delivers Third Bridge’s library of expert interviews directly within the platform, allowing users to cross-reference industry insights with proprietary documents and public filings.
A 2025 partnership with FactSet brought the financial data provider’s market information, company financials, and estimates data into the platform. Users can now combine structured insights from FactSet with unstructured intelligence surfaced through the company’s document analysis technology.
Additionally, Hebbia announced in August 2025 an integration with Microsoft Azure AI Foundry, incorporating advanced language models into its Matrix platform. This collaboration provides financial institutions with enterprise-grade security and infrastructure while enabling professionals to accelerate tasks, including due diligence, market intelligence, and contract analysis.
Platform Capabilities and Market Position
Hebbia employs a multi-agent orchestration approach rather than a single-model chatbot architecture. The platform breaks down complex queries into structured analytical steps, routes tasks to specialized AI models, and processes full documents rather than excerpts. According to OpenAI, which powers several of the platform’s models, the system achieves 92 percent accuracy on benchmarks spanning quantitative and qualitative tasks across complex legal and financial documents.
The platform’s capabilities address document-intensive workflows across financial services. Investment banking teams reportedly save 30 to 40 hours per deal on tasks including marketing material creation and client meeting preparation. Private equity firms save 20 to 30 hours per deal on screening, due diligence, and expert network research. Law firms have reduced credit agreement review time by 75 percent, generating savings of approximately $2,000 per hour in legal fees.
The company was founded in 2020 by George Sivulka, a Stanford University PhD student studying electrical engineering. The initial product focused on semantic search capabilities using large language models. The launch of Matrix in 2022 marked a strategic pivot toward comprehensive document analysis and workflow automation for financial and legal professionals.
Current client adoption spans multiple sectors within financial services. Asset managers use the platform for due diligence, investment research, and portfolio monitoring. Investment banks employ it for deal sourcing and market intelligence. Private credit teams automate the extraction of loan terms and covenants, eliminating manual contract review processes.
Technical Infrastructure and Research Initiatives
The platform provides what Hebbia describes as an infinite effective context window, allowing users to analyze larger document sets than competing solutions. This capability stems from the system’s approach to processing documents, which maintains full text rather than working with excerpted portions.
Recent research efforts have focused on model evaluation frameworks. Researchers Jake Skinner and Davis Li published work in 2025 on consensus-based evaluation methods for large language models, introducing permutation-based statistical testing combined with multi-model comparisons. This research underpins the platform’s model orchestration system, which routes specific tasks to appropriate AI models based on performance characteristics.
Hebbia has also developed the Financial AI Benchmark, a platform for measuring model capabilities across finance-specific workflows. These evaluation tools help the company optimize which models handle particular tasks, contributing to the platform’s reported accuracy improvements.
Hiring and Growth Trajectory
Hebbia plans a significant expansion of its technical workforce. Current hiring efforts target engineers interested in complex technical problems, product managers seeking to redefine knowledge worker workflows, and designers focused on creating interfaces for AI-native applications. The focus on Bay Area hiring reflects the region’s concentration of professionals with relevant expertise.
Sharma emphasized in his announcement letter that the company’s growth trajectory continues to accelerate. The platform currently serves over 1,000 distinct use cases across finance, legal, and professional services sectors. Monthly document processing volumes have reached levels that exceed Hebbia’s entire historical totals, indicating both platform adoption and increasing complexity of customer workflows.
The expansion occurs as financial institutions face pressure to automate document-intensive processes while maintaining accuracy and regulatory compliance. The company’s approach of combining multiple AI models with human oversight addresses concerns about reliability that have slowed enterprise AI adoption in regulated industries.
The San Francisco office and leadership appointment position Hebbia to capitalize on the momentum generated through recent acquisitions and partnerships. Hebbia’s strategy of building comprehensive workflow automation rather than point solutions aligns with enterprise demand for integrated platforms that address complete process lifecycles rather than isolated tasks.
As financial services organizations continue investing in AI infrastructure, platforms that demonstrate accuracy, transparency, and integration capabilities stand to capture significant market share. The combination of geographic expansion, experienced technical leadership, and strategic partnerships provides the foundation for continued growth across Hebbia’s target markets.
