Dhisana AI is an intelligent automation platform designed for revenue teams, offering AI agents to automate processes from prospecting to post-sale. It enhances efficiency by providing real-time insights, personalized outreach, and predictive analytics, helping businesses increase engagement, save time, and accelerate deal cycles without manual effort.
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How to use Dhisana AI?
Dhisana AI automates sales and revenue workflows by deploying AI agents for tasks like account discovery, lead prioritization, and meeting preparation. Users can set up agentic flows to handle outreach, analyze conversations, and forecast revenue, reducing manual work and improving team productivity across the entire funnel.
Dhisana AI 's Core Features
Automates account discovery by scouring data sources to build rich profiles of ideal customers, enabling teams to focus on high-potential opportunities.
Prioritizes leads in real-time based on fit, intent, and engagement analysis, accelerating conversions and improving early-stage efficiency.
Personalizes outreach at scale with tailored emails and messages, adjusting content based on engagement signals to boost response rates.
Prepares comprehensive meeting briefs by researching prospects and analyzing past interactions, ensuring sales reps are fully informed for calls.
Transcribes and analyzes sales conversations to flag key details like pain points and sentiment, providing full visibility for effective coaching.
Monitors buyer intent signals and alerts teams instantly when prospects show purchase intent, helping never miss opportunities.
Recommends next-best actions for deal acceleration, such as follow-up timing or content, to remove friction and close deals faster.
Dhisana AI 's Use Cases
Sales development representatives use it to automate cold outreach and lead scoring, saving over 10 hours weekly and increasing engagement by 38%.
Account executives leverage meeting briefs and real-time coaching to improve call performance and close deals 25% faster.
Sales managers utilize pipeline risk aggregation to identify stalled deals and focus on high-impact coaching, enhancing team efficiency.
Revenue operations teams automate data enrichment and lead routing, maintaining clean data without manual spreadsheets for seamless operations.
Customer success managers monitor product usage to predict churn risk and send renewal reminders, driving expansion and reducing attrition.
Chief revenue officers access AI-driven forecasts and insights to uncover growth levers and make data-informed decisions in real-time.
