Top 10 AI Tools for Earnings Analysis (Buyer’s Guide)

Professionals who regularly conduct earnings analysis as part of their job function know that accuracy, comprehensiveness, and speed are non-negotiable. Access to company filings is only part of the equation — you need tools and systems that enable you to quickly read between the lines and pick out hidden meanings and key insights that will ultimately drive your strategy.

AI tools can offer a great solution for analysis and trend-spotting at scale. They can process, interpret, and synthesize vast volumes of unstructured financial information at a speed and scale that even the most seasoned analysts can’t match. They can instantly extract the most meaningful insights, including KPIs, risks, and guidance shifts, and draft analysis-ready summaries that would otherwise take hours of manual review. And they can do this with more accuracy and comprehensiveness than any human feasibly could.

However, AI-powered earnings analysis tools are not all created equal. Some platforms have built-in content sets, automation features, and workflow tools that are purpose-built for financial and business use cases. Others are capable of producing instant summarizations and extracting important insights from transcripts, but they may still need to be supplemented with other tools.

Below, we cover the top AI tools for earnings analysis available on the market today. We explore the capabilities, strengths, and weaknesses of each, and we provide recommendations for how you can choose the tool that is best suited for your business needs.

AlphaSense

Best for: End-to-end earnings analysis, combining advanced AI, integrated workflow tools, and deep external context that together drive richer insights and smarter decision-making

AlphaSense is a leading enterprise-grade AI platform built for robust financial and market research. AlphaSense uses AI to turn a vast universe of financial and market data into structured, digestible, actionable insights. And with integrated workflow support, as well as comprehensive monitoring and analysis tools, AlphaSense not only speeds up insight discovery, but enables you to take more confident strategic action.

Unlike some other tools in this list, AlphaSense is not just an earnings analysis tool, but rather an end-to-end intelligence solution. While it excels in accelerating earnings analysis, it also gives you the broader context you need to interpret executive messaging, spot risks or contradictions, and understand how a company fits into larger market trends. Instead of only looking at transcripts or filings, AlphaSense pulls in analyst reports, expert insights, news, regulatory updates, and market commentary. While many tools focus on summarizing earnings events, AlphaSense helps you understand why it matters, how it compares to peers, and how the market is reacting — resulting in more complete, confident analysis.

Consistently ranked as an industry leader by TrustRadius and G2, AlphaSense was also named for the second year in a row in Inc’s 2025 Best in Business list in the “Best AI Implementation” and “Best in Innovation” categories.

Curated, Premium Datasets

AlphaSense is the only tool that combines public and private financial data with expert call transcripts, broker research, and news in one place. This means you get all the numbers, as well as the qualitative narrative that provides context to those figures, so you can make smarter and better informed decisions.

Premium External Market Insights

Our library of qualitative content includes:

Wall Street Insights® collection of equity research that features more than 1,000 broker sources, including Goldman Sachs
Expert calls, which includes over 240K interviews with pre-qualified experts and the ability to conduct your own 1:1 calls with 70% cost savings compared to traditional expert networks
Company documents, such as earnings transcripts, company presentations, SEC and global filings, ESG reports, and press releases
News, trade journals, and regulatory coverage

Company Perspectives

AlphaSense streamlines access to SEC filings, earnings and events transcripts, financial documents, and more. Users can easily search across multiple companies and SEC filings, as well as explore past filings, create models, and benchmark company performance, without needing to pull up individual filings to manually track a company’s metrics.

Internal Content Integration

With AlphaSense, you can integrate and query your own internal content alongside the premium external sources listed above. This includes:

Internal research, notes, and presentations
CIMs and investment memos
VDRs
Reports from industry and market intelligence providers
Emails, newsletters, web pages, and RSS feeds

Internal content is easily and securely integrated through our Ingestion API or enterprise-grade connectors — like Egnyte, 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.

Financial Data

On the quantitative side, AlphaSense provides access to the following crucial insights:

Historical Financials & Estimates: Standardized statements and consensus data across 19,000+ public companies
Sector-Specific KPIs: Detailed operating metrics sourced from institutional-grade Canalyst models
Transaction Intelligence: Nearly 1M M&A deals and 750K private funding rounds, enriched with AI-generated deal rationale and strategic context
Dynamic Peer Sets: 125+ pre-built industry comparables with sector-specific metrics

AI Search & Summarization Technology

Our industry-leading generative AI tools are purpose-built to deliver business-grade insights, leaning on 10+ years of AI tech development. Our suite of tools currently includes:

Generative Search

Generative Search is a conversational search experience that allows users to ask natural-language questions and source intelligence at scale from across premium external content, internal knowledge, and quantitative data sources. Each answer provides citations to the exact snippet of text from where the information was sourced, so that it can always be referenced back.

With Deep Research mode, users can automate the creation of in-depth analysis about companies, trends, or industry topics. The model conducts dozens of searches, parses through thousands of potentially relevant results, and reasons over all of it to produce comprehensive, detailed analysis about any topic — in a fraction of the time it would take a human.

During earnings season, Generative Search is particularly useful for analyzing sentiment changes QoQ, understanding how companies are discussing specific topics, and deep diving into analyst Q&A trends.

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.

During earnings season, AlphaSense users leverage Gen Grid to generate industry read-throughs, perform in-depth channel checks, extract key themes and sentiment from analyst Q&A, and summarize common KPIs across a portfolio or peer set.

Smart Summaries

Every earnings transcript in AlphaSense features an AI-generated Smart Summary, which creates a tearsheet of key takeaways, analyst Q&A, and the most critical topics discussed in each call. AlphaSense users leverage Smart Summaries during earnings season to extract the most crucial insights from each call in minutes, not hours, and ensure that nothing is missed.

Sentiment Analysis

Sentiment Analysis, a natural language processing (NLP)-based feature, parses content and identifies nuances in language such as tone and subjective meaning. It then uses color coding to help users identify instances of positive, negative, and neutral sentiment throughout the document.

Integrated Workflows

AlphaSense helps research professionals conduct key workflows with greater speed and confidence by incorporating the following features in the platform:

AlphaSense Excel Add-In: Excel tool with custom formulas and simple syntax, analysis templates, and pre-built Industry Comps to quickly get you up and running.
Canalyst Model Access: 4,500+ ready-to-use models with detailed financials, operating metrics, and segment breakdowns.
Purpose-built workflows: One-click agents that run full investment workflows, from company and deal screening to performing early due diligence.
Domain-Specific AI: Unlike generic AI tools, our financial AI understands sector dynamics, valuation methodologies, and market context.

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 return data without reading through pages of documents.
Snippet Explorer allows you to effortlessly assess any topic or theme and all its historical mentions in a single view.
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.

AlphaSense Pros:

Extensive content database that spans key market perspectives, including broker research, expert calls, company documents, news, and regulatory sites
Extensive quantitative insights and financial data workflow and analysis tools
Goes beyond earnings summaries, helping you understand the broader context driving company performance
14+ years of investment in AI
4,500+ pre-built financial models that update automatically
Live transcripts that allow users to view past, present, and future event transcripts in a calendar and view event transcripts in real time
Automated and customizable real-time alerts
Mobile app that includes all platform content and AI search capabilities
Internal note-taking, sharing, and collaboration features
Support for APIs and integrations
Enterprise-grade data production complying with global security standards: SOC2, ISO270001, FIPS 140-2, SAML 2.0
Excellent customer support team, including 24/7 chat with product specialists, a Live Help button on the website, and regular live AlphaSense Education webinars

AlphaSense Cons:

Custom visualization tools are limited at this time
Collaboration tools are limited to users with AlphaSense licenses
No free version; only a two-week free trial

Pricing

Subscription prices vary based on the number of users (for small- and medium-sized companies) and are customized based on the organization (enterprise- or company-level subscription packages). Contact the AlphaSense team to learn more, or start a free two-week trial here.

Aiera

Best for: Tracking and analyzing earnings calls, corporate events, and news for investment insights

Aiera is an event and financial intelligence platform that offers granular coverage of investor events and live earnings calls. It provides live and instant access to earnings calls, with real-time transcription and audio streaming, as well as news for actionable investment insights. It also features indicators that give users access to past and present financial statements, events, and financial disclosures.

Aiera has also recently integrated expert call transcripts through a partnership with Third Bridge, and broker research is available to users with specific entitlements. However, for users who require deep qualitative research and broad content coverage beyond public company events, Aiera may fall short.

Additionally, Aiera’s AI is optimized around public company disclosures and may lack depth across broker research, expert calls, private company data, etc.

Key features include:

Live Event Streaming

With this dashboard event, Aiera gives you instant access to live video and audio investor events. With one click, you can watch, pause, rewind, or speed up investor calls. Additionally, you can stream multiple live investor calls and transcribe them simultaneously. This way, you get the best takeaways from all calls at the same time.

Real-Time Transcription

Aiera uses a state-of-the-art transcription system that converts speech to text with almost no delay. You can also read and search through the call transcript, jumping to sections marked by your chosen keywords. These transcripts also help you stay ahead of potential market moves as investor calls are happening.

Search

From Aiera’s dashboard, you can search for key terms and find them across multiple documents and transcripts. You can also save search terms and track them over time or get real-time alerts on all new keyword mentions in new transcripts.

AI-Powered Analysis

Aiera’s AI tools summarize event transcripts as soon as a call ends. Aiera’s AI also generates key event themes and extracts key topics to consider. You can convert these insights into notes, share them across your organization, and export them to PDF or Word documents.

Market Monitoring

Aiera helps you monitor the market, keeping you updated on all events, news, company filings, and corporate actions. You can also set real-time alerts on any trending topics and upcoming events.

Custom Transcriptions

Aiera enables you to transcribe personal meetings and calls. Using NLP technology, Aiera can generate meeting transcripts, which you can share with colleagues and team members. These transcripts can also be uploaded for compliance.

Aiera Pros:

Live access to earnings calls and investor events
Live speech-to-text transcriptions
Uses NLP technology to enhance transcript accuracy
Deep search functionality
AI-powered transcript and document analysis
Integrated with OpenAI, allowing users to build custom AI assistants or use Aiera’s GPT-powered tools for deeper insights
Supports adding internal calls and documents for analysis
Mobile app for iOS enables users to access live event streaming and real-time transcription on the go

Aiera Cons:

Content breadth is narrow compared to complete investment research platforms
Coverage of premium, proprietary content is conditional and entitlement-aware
Strong bias toward earnings and investor calls with less emphasis on other intelligence sources
Supplementary tools will be required for full-scale market or investment research

Pricing

Aiera does not publicly disclose its pricing information. You can find more details on its pricing page, or request a demo.

Fintool

Best for: Using AI to automate financial research and uncover deeper insights from financial documents

Fintool is a generative AI tool designed specifically for financial professionals, such as analysts, portfolio managers, and investors. In the company’s own words, Fintool is engineered to discover financial insights beyond the reach of timely human analysis.

Fintool uses advanced machine learning algorithms to process and interpret financial documents — primarily SEC filings and earnings transcripts, but also M&A calls, investor day presentations, and special event transcripts — helping users make informed investment decisions with real-time data analysis and risk assessment. Notably, since it only works for the use case of earnings analysis, Fintool is limited in its utility for holistic market research.

Key features include:

Conversational Interface

The platform provides a conversational interface, where users can ask natural language questions about SEC filings, earnings calls, and conference transcripts. The tool responds with citations to all sources used and also suggests follow-up questions.

Data Extraction in Tabular Format

Fintool organizes financial metrics, KPIs, and unstructured data from filings and transcripts into easy-to-use tables, which can then be exported in CSV form. Users can customize these tables with natural language prompts.

AI Capabilities

Fintool employs a combination of advanced AI models — including ones from OpenAI, Claude, and Gemini — to process and analyze financial data. Fintool’s search infrastructure combines keyword-based and semantic search techniques, allowing users to perform complex financial queries with high relevance and accuracy. The platform also uses a three-agent verification system to ensure the reliability of its responses, minimizing errors and misinformation.

Real-Time Alerts

Fintool reads thousands of filings in the background and can notify users of specific relevant updates on a real-time basis.

Internal Data Upload

Fintool allows users to upload their own internal data into the tool, with enterprise-grade security. Fintool seamlessly integrates with cloud providers to help users discover and leverage their internal content more effectively.

Fintool Pros:

Provides access to SEC filings and earnings transcripts
Excels at automating routine tasks such as report generation and updating financial models
Has AI search capabilities
Employs a multi-agent verification system to ensure reliability of its responses
Allows users to upload their internal data; platform integrates with cloud providers
Quickly analyzes complex financial data and generates actionable insights
Cites exact snippets of source documents in generated responses
Tabular interface for company screening leveraging the user’s own criteria
AI-powered table generation via natural language prompts
Robust compliance and data security

Fintool Cons:

No content sources outside filings and earnings transcripts
Lack of premium proprietary content sources, like broker research or expert calls
Potential limitations in handling specific or niche financial queries that require deep human expertise
No integrations
Lack of transparency around how the model interprets and handles queries
LLM is customized only for investor workflows

Pricing

Fintool offers two pricing plans, one for small to medium-sized businesses, and the other for enterprise organizations. They do not disclose specific pricing for either, so you will need to contact them directly for more information.

Fiscal.ai

Best for: AI-generated charts and models, as well as limited financial data, for financial analysis

Fiscal.ai is an AI-powered investment research platform combining institutional-grade financial data, analytics, and conversational AI. Fiscal.ai only offers access to filings, earnings transcripts, and financial data (from S&P Capital IQ). It does not, however, provide access to sources such as broker research and expert call transcripts, which are crucial for holistic and comprehensive market research. Compared with many other tools in this list, Fiscal.ai is highly cost-effective, and it differentiates itself with AI-powered chart and model generation.

Fiscal.ai’s genAI is limited to answering only company research and metric questions — asking industry research questions yields responses with errors and AI hallucinations. Fiscal.ai also does not offer integrations with internal content, which means its genAI cannot be leveraged to improve the discoverability of internal research.

Key features include:

Natural Language Querying

Fiscal.ai allows users to input queries in natural language, making it easy to search for specific financial data, company information, or market trends. This feature eliminates the need for complex financial databases or coding knowledge, enabling users to extract relevant information from documents like earnings transcripts quickly and efficiently.

Real-Time Market Insights

Fiscal.ai provides real-time market insights by processing the latest news, earnings reports, and market movements. Users can get up-to-date information on stock prices, market trends, and economic indicators, helping them make timely investment decisions.

Document Analysis

One of Fiscal.ai's key capabilities is its ability to analyze financial documents such as SEC filings, annual reports, and earnings call transcripts. It extracts key insights, summarizes critical points, and highlights important information, allowing users to digest large amounts of data without spending hours reading through documents.

Integration with Financial Data Sources

The tool integrates with various financial data sources, ensuring that users have access to a comprehensive range of information. This includes data from stock exchanges, financial news outlets, and regulatory bodies, providing a holistic view of the market landscape. However, this does not include access to broker research or expert calls — which are key to an effective and differentiated market research strategy.

Customizable Dashboards

Fiscal.ai offers customizable dashboards where users can monitor their preferred data feed, news, and market updates. This feature allows users to personalize their interface according to their specific needs and interests, ensuring they have quick access to the most relevant information.

Sentiment Analysis

Fiscal.ai includes sentiment analysis tools that evaluate the tone and sentiment of financial news, reports, and social media discussions. This helps users gauge market sentiment, identify potential market-moving events, and understand the broader impact of news on stock prices and investor behavior.

Fiscal.ai Pros:

User-friendly interface, similar to ChatGPT’s
Able to generate models and charts in-platform via natural language prompts
Cost-effective for smaller businesses or individual users
Employs guardrails against genAI hallucination and verifies accuracy of information to ensure reliable results
Provides paragraph-level citations and multiple sources for each snippet of a response
Robust compliance and SOC2 Type II accreditation

Fiscal.ai Cons:

Only includes filings, earnings transcripts, and financial data (from S&P Capital IQ)
No premium proprietary external sources such as broker research or expert calls
Customized for investor workflows but lacks deep, domain-specific training of a fully verticalized LLM
Cannot upload documents and data at scale, which is crucial for enterprise organizations
Lack of transparency around how the LLM model interprets and handles queries

Pricing

Fiscal.ai has several pricing tiers to fit different user needs, with each pricing tier granting access to a unique number of chat prompts and dashboards. The free tier is limited to 10 chat prompts and offers limited access to financial data, KPI data, event transcripts, and estimates and rankings. It also limits users to one dashboard with 30 rows. The next tier (Pro) is priced at $39 per month and includes 100 chat prompts, as well as a wider breadth of financial data, KPI data, event transcripts, and estimates and rankings. It limits users to five dashboards with 50 rows and adds notification capabilities. The Enterprise tier is priced at $199 per month and includes 500 chat prompts per month, as well as unlimited access to all the financial data, KPI data, and event transcripts that Fiscal.ai offers and unlimited dashboards and rows.

Verity

Best for: Centralizing internal equity research and automating analyst workflows

Verity is an equity research platform for modern fund managers. It integrates AI and NLP capabilities to help streamline how analysts manage, organize, and generate investment theses and financial models. It also automates and accelerates earnings analysis by combining structured financial data with generative AI summarizations, sentiment analysis, and workflow tools.

However, Verity is not designed for broad, full-scale market research. It lacks access to key third-party content, such as broker research, expert calls, and press releases. There is no news aggregation or industry trend analysis. Verity also lacks monitoring capabilities beyond a firm’s own research inputs and does not provide real-time alerts for external data updates. Finally, while Verity provides AI tools for research management, financial modeling, and summarizing earnings calls, it does not have AI capabilities for synthesizing industry insights, trends, or conducting peer comparisons.

VerityData

VerityData provides access to a wide range of structured data, including financial reports, filings, and key performance indicators from publicly traded companies. This product aims to deliver high-quality, reliable financial data that investment professionals can use to make informed decisions. Users can also take advantage of Verity’s data feeds and APIs to build better qualitative and analytical models.

Research Management System

Verity’s purpose-built RMS centralizes analyst notes, models, earnings summaries, and internal research content. This content can be organized by ticker, theme, or analyst. It can also be tagged and retrieved with Verity’s powerful search and filtering capabilities.

Finance-Specific LLM

Verity’s proprietary AI model is trained on financial documents and workflows and is adept at extracting key insights, KPIs, and management commentary from earnings calls, filings, and investor presentations. The AI also flags anomalies, estimates, and tone shifts in real time. Semantic search allows analysts to query research using natural language and surface relevant insights instantly.

Automated Models

Analysts can automatically populate or update Excel-based models based on new financial data, filings, or transcripts. Verity’s AI also recognizes line items and assumptions, reducing manual data entry.

AI-Powered Summarization

Verity’s AI generates summaries of earnings calls, investor day transcripts, and reports. It summarizes changes, compared to past periods or events, and it can produce thesis-aligned bullet points that match an analyst’s own coverage.

Verity Pros:

Has access to public company filings, including 10-K/10-Q filings
Offers access to behavioral analytics
Has collaborative features and a user-friendly interface
Has generative AI capabilities for increased productivity
Has enterprise search capabilities, including the ability to upload internal documents
Supports APIs and integration
Supports updates and notifications
Has AI and NLP search features

Verity Cons:

AI is focused on summarization and model updates; no open-ended genAI capabilities
Lacks proprietary content sources like expert calls and broker research
Lacks sentiment analysis capabilities
Limited real-time data
Limited monitoring capabilities
Limited customization options compared to competitor platforms

Pricing

Verity does not publicly disclose specific pricing for its platform. It offers customized pricing based on an organization’s size and research needs. Contact Verity directly for detailed pricing information.

Hudson Labs

Best for: Rapidly analyzing public company disclosures to extract structured insights, guidance, and red flags with minimal manual effort

Hudson Labs is an AI-powered platform specifically built for institutional investors and designed to streamline and automate traditional equity research workflows. The tool can summarize earnings calls, extract guidance, perform risk analysis, generate investment memos, and surface red-flag signals.

However, Hudson Labs only provides access to publicly available company documents, including earnings transcripts, SEC filings, investor presentations, and press releases. Without premium, proprietary content such as broker research and expert call transcripts, it lacks crucial context that is needed for full-scale investment research.

Additionally, though Hudson Labs is an AI-powered tool, its AI is mostly used for rapidly digesting documents and extracting guidance, KPIs, and risk signals across many companies. The AI search is only capable of searching across primary disclosures, not a broad universe of research, news, or third-party content. Additionally, Hudson Labs does not provide market sentiment around events, valuation modeling, or forecasting. It also lacks real-time alerts for market events. For all of the above reasons, Hudson Labs is not a complete investment research platform.

Hudson Labs incorporates the following key features:

Source-Verified Document Analysis

Hudson Labs sources all its answers from qualitative data within its content library — SEC filings, earnings transcripts, investor presentations, and press releases. The tool occasionally also sources answers from the public web, depending on the user’s query. Each answer has an attribution for easy verification. However, the platform does not aggregate any premium or proprietary content that is integral for holistic market intelligence or due diligence.

Multi-Document, Multi-Period Synthesis

This tool allows queries across multiple documents and over time, and then it consolidates all results into tables or structured outputs.

Guidance and Soft Commentary Extraction

Hudson Labs extracts guidance, hedges, and soft commentary linked to numbers. This allows users to get more context for the story beneath the numbers, which can be highly useful for risk detection and comparative tracking.

Forensic Risk Assessment

Hudson Labs flags potential risks found in documents, which could include internal control weaknesses, auditor changes, SEC enforcement risk, and bankruptcy warnings. These are core components of risk-based financial due diligence and can help users identify potential accounting manipulation or governance risks early.

Workflow Features

To support streamlined workflows and collaboration, Hudson Labs incorporates the ability to save queries, create projects, execute custom queries, export results, share links, and more.

Hudson Labs Pros:

Well-suited for granular document analysis and metric extraction
Institutional-grade AI with source verification
Well-suited for financial and disclosure due diligence
Produces structured outputs, such as tables and numeric summaries
Highly useful for extracting guidance, red flags, forward-looking statements, and changes in language in publicly available financial documents

Hudson Labs Cons:

Not suitable for holistic thematic or macro-industry research
Coverage is limited to U.S. public companies and ADRs
Not suited for investment research on private targets
Limited workflow tools beyond financial due diligence
Platform content is limited to U.S. filings and investor communications
No premium or proprietary content sets

Pricing

Hudson Labs offers two pricing tiers:

Core – $100/month; limited queries and features; meant for individual users
Institutional – custom pricing; includes all features listed above

Contact Hudson Labs directly to receive a custom quote for the institutional plan.

Hebbia

Best for: Deep analysis and extracting insights from large unstructured internal datasets

Hebbia is a multi-agent AI productivity platform built to help financial, legal, and corporate teams extract insights from complex, unstructured documents at scale. Hebbia goes beyond traditional search by combining chat-style queries with multi-agent reasoning, allowing users to analyze documents they upload (such as SEC filings, contracts, earnings transcripts, and other internal data) with full transparency and source-level attribution. Hebbia works well for use cases like investment memo drafting, M&A due diligence, and contract review, replacing hours of manual research with fast AI-driven analysis.

However, Hebbia primarily relies on user-uploaded documents. It does not include proprietary content such as broker research or expert calls, and it does not function as a comprehensive content library. Hebbia also does not include real-time financial data, and it has limited pre-built workflows for finance.

Advanced Search Engine

Hebbia offers an advanced search engine that uses AI to delve into unstructured data across documents, emails, and databases. It allows users to input natural language queries to find relevant information quickly, making it easier to locate critical insights hidden within large data sets.

Matrix

A core product of Hebbia, Matrix allows users to query multiple documents simultaneously, providing answers with linked source citations. This tool can be useful for earnings analysis because it lets users query across earnings transcripts, filings, investor presentations, and other uploaded documents — all at the same time.

Document Understanding

Hebbia's AI models are capable of deep document understanding, enabling users to extract and summarize information from text-heavy sources. This feature can be useful for earnings analysis because the tool can extract key metrics and disclosures from earnings materials, reducing the time spent manually reading through documents.

Intelligent Indexing

The tool automatically indexes documents and data, organizing information in a way that makes it easily searchable and accessible. This intelligent indexing allows users to structure unorganized data sources, enhancing their ability to retrieve relevant information efficiently.

Customizable AI Models

Hebbia provides customizable AI models that can be tailored to specific industry needs or business requirements. Users can adjust the AI to focus on particular keywords, topics, or types of data, ensuring that the tool delivers the most relevant insights for their specific use cases.

Integration Capabilities

Hebbia integrates seamlessly with existing workflows and tools, such as customer relationship management systems, cloud storage solutions, and other enterprise software. This integration allows users to incorporate Hebbia’s capabilities into their current processes without disrupting their workflows.

Hebbia Pros:

Able to summarize individual documents
Can index any document of any type, via portal or API
Features intelligent semantic search
Pre-indexes company filings and research
Supports uploads of private company data
Offers a full suite of collaborative tools and access controls
Features end-to-end encryption and robust compliance

Hebbia Cons:

Relatively new in the market; product is still developing and learning
Limited to internal content and public external content; no premium or proprietary external sources such as broker research or expert calls
Must import data from external sources
Cites sources but does not link to exact snippets
Lack of transparency around guardrails against AI hallucination
Lacks sentiment analysis features
No company insights, snapshots, or tearsheets

Pricing

Hebbia does not publicly disclose its pricing information. For more details on pricing or to book a demo, reach out to Hebbia directly.

Rogo

Best for: Converting public company disclosures into analyst-ready research deliverables

Rogo is a relatively new-to-market generative AI platform built specifically for investment banks and private equity investors. This is an enterprise-grade platform with proprietary financial AI that helps financial services firms automate their workflows, uncover insights, and make data-driven decisions.

Rogo searches, analyzes, and cites across millions of documents, including your proprietary internal library and Rogo’s library of content, to save time and unlock insights. However, Rogo’s external content is not proprietary and does not include expert calls or sell-side research, both of which are integral for comprehensive financial research.

Rogo’s AI uses a variety of OpenAI models, but the LLM is built for financial services use cases. However, users report that Rogo’s AI is prone to significant hallucinations, which is a serious issue for investment research.

Analyst Chat

This is Rogo’s LLM-powered chat-based experience, similar to OpenAI’s ChatGPT. According to Rogo, Analyst allows users to “analyze datasets to generate instant, accurate answers, supported by auditable citations.”

Data Integration and Search

Rogo allows users to search across their own internal data, as well as Rogo’s library of over 65 million sources, including market research reports, SEC and international filings, company and event transcripts, live news, and private company information.

Agent Framework

This is Rogo’s workflow automation feature, which incorporates purpose-built agents that are designed for financial workflows and help users automate various repetitive tasks, such as slide creation, meeting prep, document summarization, and more. Agent can be very useful for extraction of themes across earnings calls, as well as complex financial analyses and identification of market trends across historical data.

Customizable Platform

The Rogo platform allows users to create customizable reports. Technical teams can also use their APIs and SDKs to pair agents together and develop cost-effective scalable AI solutions that are made for internal use cases.

Enterprise Capabilities

Users can upload internal content through Rogo API, third-party connectors, or cloud solutions. They can also integrate their internal data, including slide decks, CIMs, investment memos, models, spreadsheets, structured data, data rooms, meeting notes, etc. for easy reference and searchability.

Rogo prioritizes security, privacy, and compliance — they adhere to all industry best practices and compliance standards, ensuring that user data stays private.

Rogo Pros:

Facilitates enhanced productivity
High customizability
Purpose-built for financial services needs and workflows
Allows users to integrate their internal data and upload internal content through APIs or third-party connectors
Offers enterprise-grade security and data privacy
Easy-to-use interface

Rogo Cons:

Primarily serves investment banking and private equity users; limited applications outside these roles
Platform has a cluttered look and feel
Search results often yield very high-level data that lacks depth and comprehensiveness
No ability to parse over large document sets in grid format
No live transcripts
Lack of proprietary content sets, especially sell-side research and expert calls
No expert call services
No mobile app

Pricing

Rogo does not publicly disclose its pricing, and packages will vary depending on the specific needs and scale of the financial institution. Contact Rogo directly for detailed pricing information.

Perplexity

Best for: Discovering and synthesizing publicly available information with fast, citable answers

Perplexity is an AI-powered generative answer engine designed to streamline research by extracting and synthesizing information from various public sources. The platform leverages sophisticated natural language processing (NLP) techniques to understand and analyze vast amounts of text data, making it a potentially useful asset for earnings analysis. Perplexity also has a Deep Research mode that initiates multiple searches, reads various sources, synthesizes findings, and produces a long-form structured report.

It’s important to note that Perplexity is not purpose-built for financial or business workflows, so even though it can be useful for summarizing earnings calls or extracting certain metrics, it will likely need to be supplemented with another tool. Perplexity cannot access documents that are not publicly available (though the Enterprise version does have integrations with data sources like FactSet and Crunchbase), and it lacks features such as sentiment analysis, real-time alerts, and financial workflow tools.

Perplexity also has an Enterprise Pro version of its platform, specifically designed for teams. This version has added data privacy, enhanced security, and SOC2 certification, so that teams can safely upload their internal organizational data and use the tool for better knowledge discovery and collaboration.

Related Reading: AlphaSense vs Perplexity

Perplexity’s features include:

Natural Language Search

Perplexity allows users to input queries in natural language and receive detailed, mostly accurate responses. This makes it easy for users to gather insights from highly complex and unstructured data sets without needing to know specific technical commands. These responses are sourced from real-time data from the web, and each response includes clear source attribution for easy verification. However, Perplexity only links to webpages and not to exact snippets of information in the sources.

Conversational AI Model

Perplexity operates through a conversational AI interface, enabling users to ask follow-up questions and refine their queries. This interactive capability makes it easier to dig deeper into research topics and uncover more specific insights during the research process. The AI even recommends “next step” questions to help users gain even deeper insights.

However, the default AI model is optimized for quick searches and web browsing, not complex tasks or comprehensive, full-scale research. Access to more advanced AI models is only available for Pro and Enterprise Pro users.

Quick Summaries

Perplexity excels at summarizing large volumes of text and extracting key insights. The AI system can ingest long or complex documents — from articles and reports to transcripts you upload — and quickly provide digestible takeaways or answer your queries about the document.

Enterprise Pro for Teams

Perplexity launched the Enterprise Pro version of its product in late 2024, specifically designed for organizations and teams. This version includes all the capabilities of the standard Perplexity, but with added features focused on data privacy, security, and team collaboration. These features include:

Internal Knowledge Search

This enterprise search functionality allows users to search for information across both the web and their own internal databases. Internal knowledge bases are limited to files users upload directly to Perplexity.

Spaces

A feature designed to streamline collaboration for enterprise teams, Spaces are private collaborative workspaces that function as shared project hubs. Members can save threads, upload files, and work on research tasks together.

Customization and Integrations

Perplexity Enterprise Pro integrates with multiple third-party data sources and apps, which is crucial for supporting enterprise teams’ workflows. Perplexity has also recently announced integrations with data sources like FactSet and Crunchbase, which would allow enterprise users to query those databases using the Perplexity search engine.

Enterprise-Grade Privacy and Security

The Enterprise Pro version of Perplexity meets all enterprise-grade security and data privacy standards, including SOC 2 Type II. In this version, any uploaded files or queries made are not used to train the AI model, ensuring all proprietary information stays confidential. For additional data security, Perplexity offers admin-level user management control and content encryption.

Perplexity Pros:

Utilizes real-time data from the web in its answers, ensuring relevant and timely responses
Excels at fast, broad, web-based research
Handles complex queries and generates responses that are contextually rich and highly relevant
Enterprise version incorporates collaboration and customization features
Enterprise users can select more advanced AI models for their search
Great at integrating diverse data sources
Cites source documents for generated responses
Can analyze and extract insights from an uploaded document
Ability to create charts and tables summarizing data
Most useful features are only available for the higher-cost subscription tiers
Has a free version with limited features

Perplexity Cons:

No built-in premium content sets
AI is not purpose-built for financial or business use cases
Inaccuracies are common since the tool pulls from public web data
The tool struggles with highly complex or technical queries, leading to longer response times and incomplete answers
Cannot cite exact snippets from where information was sourced
Internal Knowledge Search only searches across uploaded documents, not the user’s entire internal knowledge database
Limited exporting or reporting features

Pricing

Perplexity offers several pricing tiers for both individuals and enterprises. Visit their pricing page to learn more about the subscription plans they offer.

ChatGPT

Best for: Getting high-level publicly available information on a company or industry, brainstorming ideas, and generating content

ChatGPT is a consumer-grade generative AI tool developed by OpenAI and is widely considered to have set off the genAI boom in 2022. Known for its accessibility and ease of use, ChatGPT soared to popularity for its ability to answer questions or summarize large volumes of information in seconds.

Since the tool’s debut, upgraded versions have been released, including ChatGPT Plus, ChatGPT Pro, and ChatGPT Enterprise. All versions of ChatGPT have a Deep Research mode, which creates long-form reports by searching, reading, evaluating, and synthesizing information across multiple sources. The Enterprise version of the tool comes with enhanced security and data protection, customization options for specific company needs, and integration options with third-party tools, APIs, and systems. The tool 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.

ChatGPT is not purpose-built for financial or business workflows, but it can be used for basic earnings analysis, as long as the transcripts are publicly available or uploaded by the user. It can quickly summarize transcripts and extract key themes, guidance changes, risks, and more. However, it cannot access paywalled transcripts, and it cannot pull real-time earnings data. ChatGPT also lacks any built-in structured financial datasets, as well as features such as sentiment analysis, real-time alerts, and financial workflow tools.

Related Reading: AlphaSense vs ChatGPT

ChatGPT’s features include:

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.

Data Summarization

ChatGPT can quickly summarize large amounts of information, making it ideal for condensing lengthy reports, earnings transcripts, 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.

Document Drafting

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.

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.

ChatGPT Pros:

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

ChatGPT Cons:

Not purpose-built for business or finance workflows
Only provides citations to whole webpages, not snippets of text
Cannot replace an enterprise-grade market intelligence tool
No guardrails in place to protect against hallucination or inaccurate information
Limited transparency around how the model interprets and handles queries
Lack of domain-specific expertise in highly technical areas

Pricing

ChatGPT offers several pricing tiers, depending on your specific needs. They are:

Free – best for casual users who just want basic access
ChatGPT Plus – $20/month; best for individuals wanting faster response times, higher usage limits, and access to newer features and models
ChatGPT Pro – $200/month; best for researchers or professionals needing extensive access, more advanced features, and higher performance
ChatGPT Team – $30/month/user; best for teams needing collaboration, shared resources, admin controls
ChatGPT Enterprise – custom quotes available; best for large organizations needing security, compliance, team management, admin controls, and enterprise-grade features

How to Choose the Right Earnings Analysis Tool for You

AI tools for earnings analysis are not all made equal. While each of the tools on this list is effective and reliable for certain use cases, that does not mean they will automatically be a worthwhile investment for your organization. Particularly if you are looking for a tool that will fit the needs of an enterprise organization, or one that is capable of more than just earnings analysis, you need to ensure that it has all the necessary features to support your workflow.

Here are the questions to answer when selecting an AI tool for earnings analysis:

What are your business needs? Are you simply looking for a tool that will help you with summarizing earnings transcripts or extracting key insights, or do you need a holistic comprehensive tool that will help you conduct earnings analysis while also providing a complete context of relevant market information? Consider whether you need a tool that is capable of supporting additional use cases, beyond just earnings analysis.

What types of content and data do you require? Some teams only need AI assistance on internally uploaded transcripts, while others require access to built-in content libraries. Content varies across tools — from none at all, to public web data, to premium and proprietary data sets. Consider the level of content access you need, and also what data you will need the AI to analyze.

How much customization and workflow automation do you need? Earnings workflows differ across buy-side, sell-side, IB/PE, and corporate strategy teams. Consider whether the tool has customizable dashboards, watchlists, and alerts so that you get real-time visibility into the companies, sectors, and signals that matter. Also consider how intuitive and user-friendly the tool is, so that the various customizations you do actually streamline and accelerate your earnings analysis, rather than add unnecessary complexity.

How robust and reliable is the AI? Artificial intelligence can dramatically increase the speed and scale of earnings analysis, while pulling out deeper insights and helping with pattern recognition. But some tools are much better equipped for financial and business use cases. Consider whether you need a tool that provides source citations, has a transparent model, and is trained specifically on financial and business data. Choose a tool that has invested in a highly accurate and trustworthy AI model.

What level of data protection and compliance do you need? For organizations with sensitive data, it’s critical to select a tool that has robust compliance and end-to-end data security standards. For individual or consumer-grade usage, compliance and data privacy are less important.

Does the tool integrate with your internal systems and data? Seamless integration can make or break earnings season efficiency. Ensure your tool connects with internal research libraries, shared drives, data rooms, and APIs, so that you can easily analyze all your data — both internal and external — in one centralized location.

Try AlphaSense for Free

AlphaSense is the only tool on this list that checks all the boxes, which is why it’s consistently the top choice for AI-powered earnings analysis and overall market intelligence for the world’s top firms.

By integrating qualitative and quantitative data along with market-leading AI technology that is purpose-built for business and finance use cases, AlphaSense enables smarter, faster workflows that cut hours of manual effort so you can focus on high-value strategy and analysis.

If you are part of a forward-thinking organization that is looking to accelerate and enhance your market intelligence process with the power of premium content and AI, AlphaSense is the right tool for you.

Get started for free today.