Overview
AlphaSense
AlphaSense is a leading all-in-one market intelligence and AI search platform built for robust financial and market research. This tool is designed for research and business professionals looking to implement a qualitative research strategy powered by automated features and proprietary AI technology.
Consistently ranked as an industry leader by TrustRadius and G2, AlphaSense was also recognized by Forbes as a top 50 AI company in 2023.
Here’s how our platform enables you to extract insights and answers from both high-value internal and external content with the power of artificial intelligence and generative AI—all on a single platform.
Features and Capabilities
Extensive Out-of-the-Box Content Library
AlphaSense allows you to combine valuable internal content with 10,000+ private, public, premium, and proprietary external data sources into one platform.
Our external content sources include trade journals, news, regulatory documents, earnings transcripts, investor presentations and other company documents, and SEC and global filings. AlphaSense users also have access to two premium and proprietary content offerings. These are:
- Wall Street Insights® – A collection of broker research from Wall Street’s leading firms, covering global sector themes, industries, and companies from 1,000+ sell-side and independent firms, available within the AlphaSense platform. Research professionals can even preview the contents of a broker report, saving them wasted time and money on potentially fruitless research.
- Expert Transcript Library – Tens of thousands of proprietary one-on-one call transcripts with industry experts, competitors, customers, partners, and former and current executives, with the ability to conduct your own 1:1 expert calls for less.
AlphaSense and Tegus
As of July 2024, AlphaSense and Tegus have joined forces, bringing unparalleled access to even more insights, and covering more industries and companies than ever before.
Both platforms come with extensive libraries of high-quality research, as well as data and AI tools that allow users to extract the most value from the insights they find.
Tegus has an extensive and fast-growing library of high-quality expert research, which includes coverage of 35,000+ public and private companies across TMT, consumer goods, energy, and life sciences sectors. Additionally, Tegus’ financial data offering, which includes financials, KPIs, and fully drivable models on more than 4,000 public companies, as well as its BamSEC self-serve solution to search and access securities filings, adds new and unique offerings to AlphaSense’s extensive product suite and datasets.
Additionally, Tegus’s Canalyst feature provides instant access to over 4,000 global fundamental models and over 60 industry dashboards, all hand-built and sourced by sector-focused analysts in Vancouver. Unlike building your own models and comp sheets, using Tegus’s off-the-shelf models, dashboards, and data reduces your time spent on undifferentiated work, allowing you to compete on your ability to analyze the data, not aggregate it.
Enterprise Intelligence
In addition to the external content sources listed above, AlphaSense’s Enterprise Intelligence solution allows you to upload and search through your own internal content. That includes:
- Internal research, notes, and presentations
- CIMs and investment memos
- Reports from industry and market intelligence providers
- Emails, newsletters, web pages, and RSS feeds
In this way, AlphaSense centralizes all your knowledge in one place—the internal and external—and allows you to leverage our industry-leading search, summarization, and monitoring tools to enhance and accelerate your research.
Our genAI capabilities deliver instant, accurate, and secure summarizations with the ability to ask follow-up questions across both your proprietary internal content and hundreds of millions of premium external documents.
AlphaSense meets the highest industry standards–including SOC2, ISO27001 compliant, regular, accredited third-party penetration testing, FIPS 140-2 standard encryption on all content, and SAML 2.0 integration.
AI Search & Summarization Technology
Our industry-leading suite of generative AI tools is purpose-built to deliver business-grade insights, leaning on 10+ years of AI tech development. This includes our RAG approach and our proprietary AlphaSense Large Language Model (ASLLM)—trained specifically on business and financial data—which matches or beats the leading third-party LLMs over 90% of the time.
Our suite of tools currently includes:
Our generative AI chat experience transforms how users can extract insights from hundreds of millions of premium content sources. Our chatbot 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 AI is there to help you get up to speed on a company or topic by instantly getting you the answers you need. You can dig deeper into topics by asking follow-up questions or choosing a suggested query. Each answer will always provide citations to the exact snippet of text from where the information was sourced.
This feature allows you to glean instant earnings insights (reducing time spent on research during earnings season), quickly capture company outlook, bull/bear cases, 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. We also apply this same technology to our collection of expert calls.
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 sentiments across time. Users can take advantage of it to make better-informed investment decisions and improve risk management strategies.
Integration Capabilities
Customers can easily integrate content at enterprise scale through our Ingestion API or enterprise-grade connectors—like Microsoft 365/Sharepoint, Box, Google Drive, S3, and more.
Our integration capabilities allow for more streamlined collaboration with members across your organization and improve overall team productivity. Our proprietary AI technology allows you to search across all internal and external company content to find crucial insights, catching what other platforms miss in a secure and automated way.
AlphaSense also offers content processing and content management. Content processing allows company recognition within user documents, while content management features support custom tags, metadata and folder structures to better search through internal content.
Monitoring, Analysis, and Collaboration Tools
AlphaSense is designed to help users find insights faster. In order to do that, we offer a number of tools that extend beyond search and summarization to help users accelerate research tasks.
- Customizable dashboards create a centralized information hub for monitoring key companies and themes, while tailored alerts provide real-time updates.
- Powerful collaboration tools like Notebook+ and commenting features help teams manage and share insights more effectively.
- Table Tools allow you to move faster with spreadsheet-style visualizations directly from company filings, so you can chain together, edit, and optimize tables for analysis.
- Image Search allows you to discover insights buried in charts to quickly capture data without reading through pages of documents.
- Snippet Explorer allows you to effortlessly look at any topic or theme and all its historical mentions in a single view.
- Our Black-lining feature allows you to automatically identify any QoQ changes in SEC filings.
- Automated Monitoring allows you to set up real-time alerts that send instant updates on any relevant market movements, news, emerging trends, and competitor activities. We also generate snapshots of companies and topics regularly that keep you ahead of the curve with actionable insights.
Strengths
- Extensive content database that spans key market perspectives, including broker research, expert calls, company documents, news & regulatory sites.
- Incorporates AI search technology, machine learning, and sentiment analysis
- Generative AI features, like Smart Summaries for earnings, expert calls, and broker reports
- GenAI tools can be applied to integrated internal content
- Automated and customizable alerts
- All-in-one research platform
- User-friendly interface
- Internal note-taking, sharing and collaboration features
- Support for APIs and integrations
- Supports enterprise-level organizations and teams
- Enterprise-grade data production complying with global security standards: SOC2, ISO270001, FIPS 140-2, SAML 2.0
- Excellent customer support team, including 24/5 chat with product specialists, a Live Help button on the website, and regular live AlphaSense Education webinars
Weaknesses
- Visualization tools are limited at this time
- Collaboration tools are limited to users with AlphaSense licenses
ChatGPT
When ChatGPT first became popular around 2022, its main appeal was its accessibility. Anyone, from professionals to students, could use it to answer questions or to summarize large volumes of information in seconds. The conversational interface, ability to ask follow-up questions to each query, and the tool’s capability to perform complex tasks like data analysis and content creation made this tool markedly different than a traditional search engine—and potentially much more valuable.
However, the cracks began to show fairly quickly. While the free version of ChatGPT was the most accessible, it was also found to be the most liable to confidently generate false information, or hallucinate. The overall consensus among users was that the free version can be useful, but each generated answer must be verified by the user.
Since the basic version of ChatGPT is trained only on publicly available web data, it’s considered a consumer-grade tool. It cannot be safely used by business or financial professionals, especially since there are no security or data privacy standards in place.
Since the tool’s debut, upgraded versions have been released, including ChatGPT Plus and ChatGPT Enterprise. While the former is largely similar to the free version, except with faster response times, enhanced accuracy, and the ability to handle more complex tasks, Enterprise is quite different from both.
Marketed as the version of ChatGPT ideal for organizations, Enterprise comes with enhanced security and data protection, customization options for specific company needs, and integration options with third-party tools, APIs, and systems. However, ChatGPT is not a full-fledged enterprise generative AI tool, as it’s incapable of searching through an organization’s entire internal knowledge base. It can search through public web data, as well as internal documents you upload directly, but this leaves a vast amount of knowledge—both external and internal—on the table.
Additionally, while ChatGPT Enterprise does provide citations to sources, it only links to whole webpages, rather than specific snippets. This is in contrast to AlphaSense’s genAI, which links to the exact snippets of text from where the information is sourced.
Since ChatGPT Enterprise is not trained specifically on business or financial data, and the model is not purpose-built for market intelligence and investment workflows, this tool is inadequate for enterprise search and holistic market research.
Features and Capabilities
Natural Language Understanding
ChatGPT excels at processing and understanding natural language, allowing users to input complex queries in plain English. This makes it easy for users to gather insights from highly complex and unstructured data sets without needing to know specific technical commands.
Content Generation
One of ChatGPT’s key capabilities is its ability to generate human-like text, which can be applied to drafting reports, summaries, and even high-level market analysis. This feature helps reduce the time spent on routine writing tasks, freeing up resources for higher-level strategic and analytical work.
Data Summarization
ChatGPT can quickly summarize large amounts of information, making it ideal for condensing lengthy reports, news articles, or financial filings into key takeaways. This helps users extract the most relevant insights without having to sift through large volumes of data manually.
Conversational Interface
The platform provides a conversational interface, allowing users to ask follow-up questions, refine queries, and interactively explore datasets. This makes it more intuitive and user-friendly compared to traditional data tools, enabling faster and more flexible research.
Integration with External Data Sources
ChatGPT Enterprise (the premium version of ChatGPT) can be integrated with various external systems and databases, allowing users to pull in real-time data or access specific datasets for analysis. This capability is crucial if users are needing to ensure accuracy in the answers they receive. However, ChatGPT and ChatGPT Plus lack this capability.
Strengths
- Able to process large amounts of information in seconds
- Versatile use cases across wide range of text-based tasks
- Well-financed, which is driving rapid innovation
- Has a free tier, which makes it highly accessible to individuals and small businesses
- Highly intuitive user experience with no learning curve
- Able to generate images, tables, and charts via natural language prompts
- Enterprise version integrates with company data for easy file upload
Weaknesses
- Trained on publicly available data, rather than business-grade or financial data
- Output is only as good as the data the model is trained on, so hallucination and inaccuracy are highly likely
- Only provides citations to whole webpages, not snippets of text
- Can only search through uploaded documents, not the entire internal knowledge base
- No guardrails in place to protect against hallucination or inaccurate information
- Lack of transparency around how the model interprets and handles queries
- Lack of domain-specific expertise in highly technical areas
