Standardizes and aggregates thousands of sell-side financial models into a single, comparable format, allowing users to view consensus estimates and individual analyst assumptions line-by-line.
Uses NLP to analyze earnings call transcripts, extracting key management commentary, sentiment, and specific metrics mentioned, then tracking them over time.
Provides a cloud-based environment where users can download standardized financial data, adjust assumptions, and build their own forecast models or scenarios.
Applies AI to parse sell-side research reports, regulatory filings, and other documents to extract investment ratings, price targets, and key rationale.
Allows users to set custom alerts for specific events, such as consensus estimate revisions, rating changes, or mentions of key terms in earnings calls.
A portfolio manager at a hedge fund uses Visible Alpha to conduct deep due diligence on a potential investment. They compare the detailed financial assumptions of the top ten analysts covering the stock, identify outliers in growth or margin forecasts, and analyze several quarters of earnings call transcripts to gauge management's execution against past guidance. This helps them build a more robust investment thesis and identify risks or opportunities the market may have missed.
An equity research analyst uses the platform to monitor the evolution of consensus estimates for companies in their sector ahead of earnings season. By tracking how estimates have changed in the weeks leading up to a report and analyzing the sentiment from the most recent earnings call, the analyst can better predict potential earnings surprises or guidance shifts, informing their own forecasts and client recommendations.
A corporate strategist at an asset management firm uses Visible Alpha to benchmark a company against its peers. They extract key metrics like revenue growth, margins, and capex assumptions from analyst models across the peer group, and use transcript analysis to compare how different managements discuss common industry challenges. This provides a data-rich view of relative positioning and operational efficiency within an industry.
A quantitative analyst downloads standardized historical and forecast data from Visible Alpha for a universe of stocks. They use this clean, consistent dataset as the foundation to build and backtest their own proprietary factor models or machine learning algorithms, saving significant time on data collection and cleaning while ensuring comparability across companies.
A sell-side research department utilizes the platform to monitor the coverage and views of competing firms. This helps them understand the consensus landscape, ensure their own models are comprehensive, and identify gaps where they can provide unique insights to clients. It also streamlines the process of updating models with the latest industry data points extracted from competitor reports.
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15Five operates in the people analytics and employee experience space, where platforms aggregate HR and feedback data to give organizations insight into their workforce. These tools typically support engagement surveys, performance or goal tracking, and dashboards that help leaders interpret trends. They are intended to augment HR and management decisions, not to replace professional judgment or context. For specific information about 15Five's metrics, integrations, and privacy safeguards, you should refer to the vendor resources published at https://www.15five.com.
20-20 Technologies is a comprehensive interior design and space planning software platform primarily serving kitchen and bath designers, furniture retailers, and interior design professionals. The company provides specialized tools for creating detailed 3D visualizations, generating accurate quotes, managing projects, and streamlining the entire design-to-sales workflow. Their software enables designers to create photorealistic renderings, produce precise floor plans, and automatically generate material lists and pricing. The platform integrates with manufacturer catalogs, allowing users to access up-to-date product information and specifications. 20-20 Technologies focuses on bridging the gap between design creativity and practical business needs, helping professionals present compelling visual proposals while maintaining accurate costing and project management. The software is particularly strong in the kitchen and bath industry, where precision measurements and material specifications are critical. Users range from independent designers to large retail chains and manufacturing companies seeking to improve their design presentation capabilities and sales processes.
3D Generative Adversarial Network (3D-GAN) is a pioneering research project and framework for generating three-dimensional objects using Generative Adversarial Networks. Developed primarily in academia, it represents a significant advancement in unsupervised learning for 3D data synthesis. The tool learns to create volumetric 3D models from 2D image datasets, enabling the generation of novel, realistic 3D shapes such as furniture, vehicles, and basic structures without explicit 3D supervision. It is used by researchers, computer vision scientists, and developers exploring 3D content creation, synthetic data generation for robotics and autonomous systems, and advancements in geometric deep learning. The project demonstrates how adversarial training can be applied to 3D convolutional networks, producing high-quality voxel-based outputs. It serves as a foundational reference implementation for subsequent work in 3D generative AI, often cited in papers exploring 3D shape completion, single-view reconstruction, and neural scene representation. While not a commercial product with a polished UI, it provides code and models for the research community to build upon.
