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Major AI providers like OpenAI, Google, xAI and others have all launched various AI agents that conduct exhaustive or "deep" research across the web on behalf of users, spending minutes at a time to compile extensively cited white papers and reports that, in their best case versions, are ready to be circulated to colleagues, customers and business partners without any human editing or reworking.
But they all have a significant limitation out-of-the-box: they are only able to search the web and the many public facing websites on it -- not any of the enterprise customer's internal databases and knowledge graphs. Unless, of course, the enterprise or their consultants take the time to build a retrieval augmented generation (RAG) pipeline using something like OpenAI's Responses API, but this would require a fair bit of time, expense, and developer expertise to set up.
But now AlphaSense, an early AI platform for market intelligence, is trying to do enterprises -- particularly those in financial services and large enterprises (it counts 85% of the S&P 100 as its customers) -- one better.
Today the company announced its own "Deep Research," an autonomous AI agent designed to automate complex research workflows that extends across the web, AlphaSense's catalog of continuously updated, non-public proprietary data sources such as Goldman Sachs and Morgan Stanley research reports, and the enterprise customers' own data (whatever they hook the platform up to, it's their choice).
Now available to all AlphaSense users, the tool helps generate detailed analytical outputs in a fraction of the time traditional methods require.
"Deep Research is our first autonomous agent that conducts research in the platform on behalf of the user -- reducing tasks that once took days or weeks to just minutes," said Chris Ackerson, Senior Vice President of Product at AlphaSense, in an exclusive interview with VentureBeat.
Underlying model architecture and performance optimization
To power its AI tools -- including Deep Research -- AlphaSense relies on a flexible architecture built around a dynamic suite of large language models.
Rather than committing to a single provider, the company selects models based on performance benchmarks, use case fit, and ongoing developments in the LLM ecosystem.
Currently, AlphaSense draws on three primary model families: Anthropic, accessed via AWS Bedrock, for advanced reasoning and agentic workflows; Google Gemini, valued for its balanced performance and ability to handle long-context prompts; and Meta's Llama models, integrated through a partnership with AI hardware startup Cerebras.
Through that collaboration, AlphaSense uses Cerebras Inference running on WSE-3 (Wafer-Scale Engine) hardware, optimizing inference speed and efficiency for high-volume tasks. This multi-model strategy enables the platform to deliver consistently high-quality outputs across a range of complex research scenarios.
New AI agent aims to replicate the work of a skilled analyst team with speed and high accuracy
Ackerson emphasized the tool's unique combination of speed, depth, and transparency.
"To reduce hallucinations, we ground every AI-generated insight in source content, and users can trace any output directly to the exact sentence in the original document," he said.
This granular traceability is aimed at building trust among business users, many of whom rely on AlphaSense for high-stakes decisions in volatile markets.
Every report generated by Deep Research includes clickable citations to underlying content, enabling both verification and deeper follow-up.
Building on a decade of AI development
AlphaSense's launch of Deep Research marks the latest step in a multi-year evolution of its AI offerings. "From the founding of the company, we've been leveraging AI to support financial and corporate professionals in the research process, starting with better search to eliminate blind spots and control-F nightmares," Ackerson said.
He described the company's path as one of continuous improvement: "As AI improved, we moved from basic information discovery to true analysis -- automating more of the workflow, always directed by the user."
AlphaSense has introduced several AI tools over the past few years. "We've launched tools like Generative Search for fast Q&A across all AlphaSense content, Generative Grid to analyze documents side by side, and now Deep Research for long-form synthesis across hundreds of documents," he added.
Use cases: from M&A analysis to executive briefings
Deep Research is designed to support a range of high-value workflows. These include generating company and industry primers, screening for M&A opportunities, and preparing detailed board or client briefings. Users can issue natural language prompts, and the agent returns tailored outputs complete with supporting rationale and source links.
Proprietary data and internal integration set it apart
One of AlphaSense's primary advantages lies in its proprietary content library. "AlphaSense aggregates over 500 million premium and proprietary documents, including exclusive content like sell-side research and expert call interviews -- data you can't find on the public web," Ackerson explained.
The platform also supports integration of clients' internal documentation, creating a blended research environment. "We allow customers to integrate their own institutional knowledge into AlphaSense, making internal data more powerful when combined with our premium content," he said.
This means firms can feed internal reports, slide decks, or notes into the system and have them analyzed alongside external market data for deeper contextual understanding.
Commitment to continuous information updates and a security focus
All data sources in AlphaSense are continuously updated. "All of our content sets are growing -- hundreds of thousands of documents added daily, thousands of expert calls every month, and continuous licensing of new high-value sources," Ackerson said.
AlphaSense also places significant emphasis on enterprise security. "We've built a secure, enterprise-grade system that meets the requirements of the most regulated firms. Clients retain control of their data, with full encryption and permissions management," Ackerson noted.
Deployment options are designed to be flexible. "We offer both multi-tenant and single-tenant deployments, including a private cloud option where the software runs entirely within the client's infrastructure," he said.
Growing precision, custom enterprise AI demand
The launch of Deep Research responds to a broader enterprise trend toward intelligent automation. According to a Gartner prediction cited by AlphaSense, 50% of business decisions will be augmented or automated by AI agents by 2027.
Ackerson believes AlphaSense's long-standing commitment to AI gives it an edge in meeting these needs. "Our approach has always been to ride the wave of better AI to deliver more value. In the last two years, we've seen a hockey stick in model capability -- now they're not just organizing content, but reasoning over it," he said.
A new tool for a complex business environment
With Deep Research, AlphaSense continues its push to simplify the work of professionals operating in fast-moving and data-dense environments. By combining high-quality proprietary content, customizable integrations, and AI-generated synthesis, the platform aims to deliver strategic clarity at speed and scale.
