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Conversational Analytics & Business Intelligence
UNSCRAMBL is a revenue intelligence platform that analyzes customer conversations using AI to extract actionable data. Built for sales and revenue teams, it automates insights from calls and emails, improving workflows, deal visibility, and forecasting accuracy. Ideal for optimizing outreach, pipeline management, and data-driven lead generation strategies.
UNSCRAMBL is a revenue intelligence platform that analyzes customer conversations using AI to extract actionable data. Built for sales and revenue teams, it automates insights from calls and emails, improving workflows, deal visibility, and forecasting accuracy. Ideal for optimizing outreach, pipeline management, and data-driven lead generation strategies.
UNSCRAMBL is an AI-powered revenue intelligence platform designed for sales, founders, and GTM teams to extract structured data from unstructured customer interactions. It captures insights from calls, emails, and meetings, transforming them into actionable data that enhances CRM accuracy and pipeline visibility. Key features include automated data capture, workflow automation, deal intelligence, and seamless integrations with CRM and sales tools. Teams use UNSCRAMBL to improve lead generation, optimize outreach strategies, and track buying signals without manual data entry. Its ability to convert conversations into searchable, analyzable data enables better forecasting and faster decision-making. By automating data enrichment and aligning insights across workflows, UNSCRAMBL helps revenue teams operate with higher precision and efficiency. It fits into the modern sales stack as a conversation intelligence and data automation layer that bridges communication channels with CRM systems, ensuring consistent, real-time insights across the revenue pipeline.
UNSCRAMBL’s ideal customer profile includes data-driven enterprise teams, including sales, RevOps, and business analysts, at B2B companies managing complex data environments. It fits organizations focused on automating analytics workflows, improving decision-making, and enabling non-technical teams to access insights for reporting, forecasting, and GTM execution.
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UNSCRAMBL uses natural language processing to let users ask questions in plain English, automatically translating them into queries and delivering insights, eliminating the need for SQL or manual data analysis workflows.
It connects with enterprise data warehouses, cloud databases, CRM systems, and business applications, enabling unified data access and automated workflows across multiple sources.
Teams use it to extract insights from sales and customer data, track pipeline metrics, and optimize outreach strategies through real-time analytics and automated reporting.
Yes, it automates report creation and dashboard updates by continuously analyzing data, reducing manual effort and ensuring up-to-date insights for business workflows.
By surfacing patterns, trends, and customer signals from integrated data sources, it helps teams refine targeting, improve segmentation, and optimize lead generation workflows.
Unlike traditional BI platforms, it focuses on conversational analytics, allowing users to interact with data through chat interfaces and automate insights without complex setup or queries.
Yes, it integrates directly with collaboration platforms such as Microsoft Teams, enabling users to access analytics, run queries, and share insights within existing workflows.
It processes data in near real-time, ensuring dashboards and insights reflect the latest information, which is critical for fast-moving sales and marketing workflows.
Yes, it is built for enterprise scalability, supporting large datasets, multiple users, and complex data environments with secure and governed access.
Teams can onboard quickly by connecting data sources and using the natural language interface, allowing immediate access to insights without extensive setup or training.
We help B2B teams build predictable pipeline, optimize their tech stack, and scale revenue. Whether it's growth or product, let’s talk.