
D&B Hoovers is a sales intelligence and revenue workflow platform that helps organizations identify, prioritize, and act on buying signals. By combining trusted company and contact data with buyer intent, website engagement insights, trigger events, and AI-powered assistance, D&B Hoovers helps revenue teams uncover opportunities sooner and make more informed decisions throughout the sales cycle.
Built on the Dun & Bradstreet Data Cloud, D&B Hoovers provides comprehensive business intelligence, including company profiles, corporate family structures, decision-maker contacts, industry information, financial insights, company news, and market intelligence. Advanced search and segmentation capabilities allow users to identify high-potential accounts and build targeted prospect lists based on business characteristics, growth indicators, and buying signals.
D&B Hoovers integrates into existing sales and revenue workflows, helping teams reduce research time, prioritize outreach, monitor account activity, and engage buyers with greater relevance. Real-time business triggers and account intelligence help organizations understand changing customer needs, identify opportunities, and focus efforts on the accounts most likely to convert.
Whether supporting prospecting, account planning, pipeline generation, or revenue operations, D&B Hoovers provides the trusted intelligence and contextual insights needed to help teams work more efficiently and drive better business outcomes.
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Dragonfly serves as a seamless substitute for Redis, offering enhanced performance while reducing costs. It is specifically engineered to harness the capabilities of contemporary cloud infrastructure, catering to the data requirements of today’s applications, thereby liberating developers from the constraints posed by conventional in-memory data solutions. Legacy software cannot fully exploit the advantages of modern cloud technology. With its optimization for cloud environments, Dragonfly achieves an impressive 25 times more throughput and reduces snapshotting latency by 12 times compared to older in-memory data solutions like Redis, making it easier to provide the immediate responses that users demand. The traditional single-threaded architecture of Redis leads to high expenses when scaling workloads. In contrast, Dragonfly is significantly more efficient in both computation and memory usage, potentially reducing infrastructure expenses by up to 80%. Initially, Dragonfly scales vertically, only transitioning to clustering when absolutely necessary at a very high scale, which simplifies the operational framework and enhances system reliability. Consequently, developers can focus more on innovation rather than infrastructure management.
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LeadSift
LeadSift, a B2B intent data provider, helps organizations identify and prioritize prospects and accounts that they should be targeting. We use millions of Unstructured Public Web Data data to identify prospects who are more interested in competing topics and other relevant topics. Once we have identified a signal, we use a sophisticated mapping process that reveals who these prospects are and their work environment to determine if it is relevant. The final output is a contact that has been actively researching a company or topic. LeadSift data allows organizations to optimize their ad spend, marketing nurturing campaigns, and sales outreach.
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Explorium
Explorium is a B2B data platform that helps organizations access, enrich, and activate business intelligence for sales, marketing, and AI-driven go-to-market operations. The platform combines information from more than 100 data sources into a unified collection of company profiles, professional contacts, market signals, and business intelligence. Its data coverage includes more than 146 million business entities, 767 million professional profiles, 90 million geospatial data points, and 4,000 distinct data signals. Explorium provides firmographic, technographic, contact, event, and other contextual information that can be used to identify target companies and understand potential sales opportunities. AgentSource APIs are designed for AI agents, with structured data access, consistent identifiers, and informative error responses that simplify integration into automated workflows. The platform also supports Model Context Protocol (MCP) and Server-Sent Events (SSE) to connect business data with AI applications and agent frameworks. Automated target discovery and personalized signal creation help organizations identify relevant accounts and generate custom indicators based on their specific go-to-market requirements. Natural-language querying, contact enrichment, and messaging tools enable agents to retrieve information and develop more relevant prospecting communications. Explorium supports sales intelligence, lead generation, account targeting, data enrichment, and the development of AI-powered sales agents through customizable data delivery and API-based integrations.
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