AlphaSense Launches Deep Research to Unify Web and Enterprise Data

Leading AI providers such as OpenAI, Google, xAI, and others have released numerous AI agents that perform comprehensive or "deep" web research on users' behalf. These systems spend several minutes compiling heavily referenced white papers and reports which, in their best iterations, can be shared directly with colleagues, clients, and business partners without requiring human editing.

However, these tools face a notable out-of-the-box limitation: they can only search the web and public sites—not a company’s internal databases or knowledge graphs. Enterprises or their consultants could build a retrieval augmented generation (RAG) pipeline using, for example, OpenAI’s Responses API, but that demands considerable time, budget, and technical skill to implement.

Now, AlphaSense—an early AI platform for market intelligence—aims to give enterprises, especially in financial services and large corporations (including 85% of S&P 100 companies), a more advanced solution.

Today, the company unveiled its own “Deep Research,” an autonomous AI agent built to automate intricate research workflows that span the open web, AlphaSense’s continuously updated proprietary content (such as Goldman Sachs and Morgan Stanley research), and each client's internal data—whatever sources they choose to connect.

Available now to all AlphaSense users, the tool produces detailed analytical results far faster than traditional approaches.

“Deep Research is our first autonomous agent that conducts research directly in the platform on the user’s behalf—turning tasks that used to take days or weeks into a matter of minutes,” Chris Ackerson, Senior Vice President of Product at AlphaSense, told VentureBeat in an exclusive interview.

Core model architecture and performance enhancements

AlphaSense powers its AI tools—including Deep Research—with a flexible architecture that draws on a dynamic set of large language models.

Rather than depending on a single provider, the company selects models based on performance benchmarks, suitability for the use case, and ongoing developments in the LLM landscape.

Currently, AlphaSense uses three main model families: Anthropic, accessed via AWS Bedrock, for advanced reasoning and agent workflows; Google Gemini, praised for its balanced performance and capacity to manage long-context prompts; and Meta’s Llama models, integrated through a partnership with hardware startup Cerebras.

Through this partnership, AlphaSense runs Cerebras Inference on WSE-3 (Wafer-Scale Engine) hardware, boosting inference speed and efficiency for high-volume operations. This multi-model approach ensures the platform delivers high-quality, consistent results across diverse research scenarios.

New AI agent designed to match the output of a skilled analyst team—quickly and accurately

Ackerson highlighted the tool’s distinctive mix of speed, thoroughness, and transparency.

“To minimize hallucinations, we ground all AI-generated insights in source content, and users can trace any output back to the exact sentence in the original document,” he explained.

This fine-grained traceability seeks to build trust among business professionals, many of whom use AlphaSense for critical decisions in rapidly changing markets.

Every Deep Research report includes clickable citations to original content, allowing both validation and further exploration.

A decade of AI innovation as a foundation

The launch of Deep Research represents the latest phase in AlphaSense’s multi-year evolution of AI solutions. “Since the company’s founding, we’ve applied AI to help financial and corporate professionals during the research process—starting with smarter search to eliminate blind spots and tedious Control-F scrolling,” Ackerson noted.

He described the company’s journey as one of steady advancement: “As AI technology improved, we transitioned from simple information discovery to genuine analysis—automating more of the workflow while keeping the user in control.”

AlphaSense has rolled out multiple AI tools in recent years. “We introduced Generative Search for quick Q&A across AlphaSense content, Generative Grid for side-by-side document comparison, and now Deep Research for synthesizing long-form insights from hundreds of documents,” he added.

Use cases: from M&A analysis to executive summaries

Deep Research is built to assist in a variety of high-impact workflows, including company and industry primers, M&A opportunity screening, and detailed board or client briefings. Users can input prompts in natural language, and the agent returns customized outputs backed by reasoning and source links.

Proprietary data and internal integration as key differentiators

A major strength of AlphaSense is its exclusive content repository. “AlphaSense aggregates more than 500 million premium and proprietary documents, including exclusive resources like sell-side research and expert call transcripts—content unavailable on the public web,” Ackerson said.

The platform also allows integration of clients’ internal documents, creating a unified research ecosystem. “We enable customers to bring their internal knowledge into AlphaSense, amplifying the value of their proprietary data when merged with our premium sources,” he added.

This allows organizations to upload internal reports, slide decks, or meeting notes, and have them analyzed together with external market data for richer contextual insight.

Ongoing data enrichment and a security-first mindset

All data within AlphaSense is refreshed continuously. “Our content library is constantly growing—we add hundreds of thousands of documents each day, thousands of expert call transcripts monthly, and continuously license new high-value sources,” Ackerson stated.

AlphaSense also prioritizes enterprise-grade security. “We’ve developed a secure, enterprise-class platform that meets the standards of the most heavily regulated firms. Clients maintain control over their data, with full encryption and permissions management,” he noted.

Deployment models are highly adaptable. “We provide both multi-tenant and single-tenant setups, including a private cloud option where the software operates entirely within the client’s own infrastructure,” he said.

Rising demand for precision and tailored enterprise AI

The introduction of Deep Research aligns with a broader enterprise shift toward intelligent automation. As AlphaSense highlighted, a Gartner forecast indicates that by 2027, 50% of business decisions will be either augmented or automated by AI agents.

Ackerson believes AlphaSense’s longstanding investment in AI provides a competitive advantage in meeting these demands. “Our strategy has always been to leverage the latest AI advances to provide greater value. Over the past two years, model capabilities have exploded—they're no longer just organizing information, but reasoning through it,” he remarked.

A new capability for navigating complex business landscapes

With Deep Research, AlphaSense continues its mission to streamline the work of professionals in fast-paced, data-rich fields. By integrating exclusive proprietary content, flexible data connectors, and AI-powered synthesis, the platform promises to deliver strategic insights more rapidly and at greater scale.