Trusted by the world's leading firms
80%
of the top investment banks
80%
of the top asset management firms
80%
of the top private equity firms
88%
of the S&P 100
In today’s fast-moving financial landscape, staying ahead isn’t just about having access to more data — it’s about extracting the right insights from the data and using them to make faster, smarter decisions. In a world of shifting macroeconomic indicators, market volatility, and evolving regulatory frameworks, artificial intelligence is a beacon of opportunity.
AI enables financial services teams to process vast amounts of unstructured data, surface meaningful patterns, and generate actionable insights — all in a fraction of the time. Whether it’s identifying early market signals, streamlining compliance, or accelerating research, AI empowers investment professionals to cut through the noise and act with greater speed, confidence, and precision.
Below are some of the top use cases for AI in financial services:
Market and Investment Research
AI is transforming the way investment teams conduct their market and investment research by accelerating time to insight and maximizing the value extracted from each content source. Generative AI can parse through company documents, industry briefs, lengthy regulatory filings, expert call transcripts, analyst reports, and other qualitative sources in seconds, distilling the most crucial insights that are relevant to your specific research needs. With less time spent manually searching for information, you can spend more time on strategy and analysis.
Due Diligence
The traditional way of conducting due diligence involves manually parsing through multiple sources of information — which often results in missed insights, human error, and far too much wasted time. Enter: artificial intelligence.
AI can quickly process financial statements, contracts, transaction histories, and other critical documents, identifying anomalies, trends, or risks that might be missed in a manual review. This not only speeds up the due diligence process but also improves accuracy, as AI can detect patterns that indicate potential red flags in a company’s financial health. By automating data extraction and analysis, AI reduces the time and manual effort dealmakers spend, while improving the quality of the analysis.
Deal Sourcing
In the venture capital and private equity spaces, AI streamlines the deal sourcing process by automating the discovery and analysis of potential investment opportunities. By screening through vast amounts of data sources, it can help identify high-potential deals that align with specific investment criteria — all in less time and with minimized risk of missed opportunities.
Generative AI can also develop alpha-generating resources such as deal sourcing maps and outreach strategies, expand narrow or niche lists to include similar acquisition targets, and even help draft correspondence.
Financial Analysis
For investment teams, financial analysis usually involves piecing together financial information from 10K filings, earnings transcripts, or IR presentations. This typically requires consuming lengthy reports and difficult-to-locate documents and toggling between multiple screens or platforms. The process increases the likelihood of missing a key datapoint or failing to identify a pattern in the data. AI is able to parse through financial data in a fraction of the time, allowing teams to instantly extract key insights from the quantitative data and discover patterns that would otherwise be impossible to see.
Knowledge Sharing
Investment firms are increasingly prioritizing knowledge sharing and discovery initiatives, and generative AI is central to this endeavor. By instantly scouring huge volumes of internal and external data, genAI can accurately summarize and surface the content in a digestible format, answer any of your queries across the content, and accelerate speed to insight.
Automation and Acceleration
One of AI’s greatest advantages is its ability to perform tasks in a fraction of the time it would take a human — with greater accuracy and precision. Natural language and semantic search automate and expedite information retrieval, so that analysts don’t have to manually comb through documents. AI models can also rapidly synthesize unstructured text (such as news, regulatory updates, and expert calls) into digestible summaries and briefings, helping analysts understand complex issues in seconds.
Finally, AI enables real-time tracking of market movements, competitor events, and market trends. With features like real-time alerts and sentiment analysis, professionals can get notified right away of tonal changes in earnings transcripts or relevant macroeconomic developments.
Compliance Monitoring
Compliance monitoring is crucial for financial services firms, and AI simplifies this process, even with constantly evolving regulatory policies. AI can extract and summarize relevant updates from thousands of global regulatory bodies, legal publications, and government sites in real time. AI-powered document comparison tools can highlight changes between versions of laws, regulations, or internal policies. In other words, AI facilitates a proactive, rather than reactive, approach to compliance, which minimizes risk and protects firm reputation.
Why AlphaSense is the Top AI-Driven Tool for Financial Firms
Premium and Proprietary Financial Content
Having access to the right content in one centralized place — indexed and easily searchable — is critical for investment teams. AlphaSense’s platform aggregates 10,000+ private, public, premium, and proprietary external data sources to provide a holistic view of any company, industry, trend, or market. Our content includes:
- Wall Street Insights® collection of equity research that features more than 1,000 broker sources, including Goldman Sachs
- Expert call transcript library with over 200,000 vetted interviews covering more than 18,000 private companies, as well as the ability to conduct your own 1:1 expert calls for less. Learn more about the combined offering of AlphaSense and Tegus.
- Company documents, such as earnings transcripts, company presentations, SEC and global filings, ESG reports, and press releases
- 13M+ documents about private companies, including news, trade journals, and regulatory sources
- Over 5M patent publications tagged to private companies
Enterprise Intelligence
Alongside the premium external sources found in the AlphaSense platform, investment teams can also search, summarize, and interrogate their proprietary internal data using AI. Enterprise Intelligence is built for robust, security-conscious teams, offering scalability features such as user management, broad system connectors, infrastructure compatibility, and collaboration tools.
Some core capabilities of AlphaSense’s Enterprise Intelligence include:
- Instant GenAI-Powered Answers – Our purpose-built genAI chat and summarization capabilities deliver instant, accurate, and secure summarizations of both premium external and proprietary internal content.
- Ease of Integration – Through an AlphaSense-managed solution in our secure cloud or a customer-managed solution in the cloud of your choice, Enterprise Intelligence integrates your content at enterprise scale through our Ingestion API or Enterprise-Grade Connectors, easily supporting the uploading and management of tens of millions of documents.
- Out of the box functionality – Automatically integrate and tag PDFs, SharePoint docs, CIMs, Excel sheets, and more. Get quick context using genAI summaries with in-line citations — verifiable with one click.
- Enterprise-Grade Data Protection – AlphaSense Enterprise Intelligence’s cloud environment complies with global security standards — SOC2, ISO270001 compliant, conducts regular, accredited third-party penetration testing, offers FIPS 140-2 standard encryption on all content & supports SAML 2.0 integration.
Best-In-Class AI Features
AlphaSense’s suite of AI features equips investment teams with the resources and functionality they need for comprehensive research workflows, all while providing a competitive advantage.
Generative Search
Our genAI chat experience transforms how users can extract insights from hundreds of millions of premium content sources. Generative Search is trained to think like an analyst, so it understands the market research intent behind your natural language queries.
Whenever you search for information, Generative Search helps you get up to speed on a company or topic by instantly getting you the answers you need. For example, you can ask Gen Search to discuss the electric vehicle investments of automotive companies, analyze R&D spending within pharmaceutical companies, or summarize existing internal research that has already been done on a particular market, to name a few.
Each answer will always provide citations to the exact snippet of text from where the information was sourced. Generative Search is constantly evolving and incorporates a variety of reasoning models and agentic workflows.
Deep Research
Operating within Generative Search, the Deep Research mode provides our users with access to leading-edge generative AI reasoning models across their most valuable content sets, transforming how research is conducted for idea generation, due diligence, M&A prep, and so much more.
When you use Deep Research mode to ask a question, it will perform dozens of searches, parse through thousands of potentially relevant results, and reason over all of it to produce comprehensive, detailed analysis about any topic — like having a team of highly-skilled analysts who can work at superhuman speed on your behalf.
And while other deep research tools only have access to content scrapable on the open web, the analysis produced by AlphaSense’s Deep Research is sourced from 500M+ premium documents on public and private markets, alongside your firm’s own proprietary data.
Generative Grid
Generative Grid applies multiple genAI prompts to many documents at the same time to quickly provide organized answers to research questions at scale, in an easy-to-read table format. This enables clients to summarize documents using pre-built criteria to save time when executing repeatable workflows.
Generative Grid pulls data from both premium external documents in the AlphaSense platform and users’ internal content. From there, users can choose from more than two dozen prebuilt templates, or create their own to automate routine workflows. Each summary provides a direct citation to the source material it was pulled from.
Some of the top Gen Grid use cases include:
- Staying on top of your coverage universe during earnings season
- Summarizing reports from portfolio companies
- Analyzing merger proxy filings
- Speeding up CIM reviews to quickly spot opportunities
- Extracting key insights from a set of expert call transcripts
Smart Summaries
This feature allows you to glean instant earnings insights (reducing time spent on research during earnings season), quickly capture company outlook and bull/bear cases from analyst research, and generate an expert-approved SWOT analysis straight from former competitors, partners, and employees. All Summaries provide you with citations to the exact snippets of text from where the summaries are sourced — combining high accuracy with easy verification.
This unique feature is proprietary to AlphaSense and has the ability to understand both the keyword and search intent behind any of your queries, factoring in search results that include variations in business language. For example, a search for “TAM” will also bring back results on “addressable market” and “market size.”
Relevancy Algorithm
AlphaSense’s advanced algorithm also eliminates noise (i.e., content with matching keywords but ultimately irrelevant to your specific search objective) and surfaces only the most relevant results based on market research workflows. This algorithm saves you precious time and energy, allowing you to get straight to analysis and other high-level tasks.
Sentiment Analysis
Sentiment Analysis, a natural language processing (NLP)-based feature, parses through content and identifies nuances in the tone and subjective meaning of text. It then uses color coding to help readers identify the document’s positive, negative, and neutral sentiments.
This technology assigns each search term a numerical sentiment change score to help users track any slight change in market sentiment over time. Users can take advantage of it to make better-informed investment decisions and improve risk management strategies.
What Our Clients Say
AlphaSense clients include 80% of the top financial firms in the world. Here are a few reasons they rely on AlphaSense:
One of the things I like about AlphaSense is that, if I do type in a company, it will leverage everything across the expert transcript library, sell-side research, and the third party research and organize it by the most relevant pieces of information. It helps me find things I would never see if I wasn’t using the platform.
We use AlphaSense to make decisions much quicker right now, which helps us save resources. It also helps us to combine data much quicker and exchange information better across the team, and this means we can make better decisions for our clients.
My research has been greatly impacted by Generative Search’s ability to recognize the intent of my query then align that with the essence of information in specific documents across a broad set of potential documents. There’s phenomenal alignment between my demand and the document library’s supply. I love it.
AlphaSense has the best and most accurate language processing when I’m searching across filings, transcripts, and other resources. The searchability with AlphaSense is second to none.
I had the opportunity to explore a demo of an AI platform that competes with Alphasense. In comparison, I found Alphasense to be significantly more comprehensive, with its responses being clearer and more direct. The competing platform provided anecdotal pieces of information in response to specific company-related questions that lacked traceability.
