Bagel AI
Bagel AI is the inaugural AI-native Product Intelligence Platform that enables product teams to link product decisions directly to business outcomes by offering automatic evidence aggregation, AI-generated roadmap suggestions, ROI indicators, and actionable insights, along with connections to existing technologies.
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Description for Bagel AI
Bagel AI is the inaugural AI-native Product Intelligence Platform aimed at assisting product teams in linking product decisions directly to business outcomes. Its objective is to eradicate conjecture and prejudice in product decisions, hence facilitating the demonstration of ROI and linking product efforts to business outcomes.
Features of Bagel AI
- Automated Evidence Consolidation: The AI persistently learns and adjusts to a company's taxonomy, autonomously finding and extracting pertinent product deficiencies and issues from all feedback sources, resulting in an 85% reduction in duplicated data.
- AI-Generated Roadmap Concepts: The AI evaluates feedback, usage statistics, and revenue patterns to produce high-impact product concepts that correspond with current roadmaps, possibly yielding a +23% boost in Net New Revenue.
- Metrics Demonstrating ROI: The platform enables customers to monitor feature adoption, identify satisfaction patterns, and quantify financial impact, facilitating effective KPI measurement and potentially resulting in a 15% reduction in turnover.
- Actionable Insights: Bagel AI transforms unstructured feedback into actionable insights, integrating seamlessly into existing workflows and tools to deliver on-time updates to stakeholders.
- Integration with Current Tools: It integrates with tools like Salesforce, Gong, Zendesk, and Jira, extracting feedback from various sources such as transcripts, tickets, and CRM notes.
Use Cases for Bagel AI
- Prioritise features according to data and impact for product managers.
- Eliminate obstacles to deals and synchronise product priorities with revenue-generating prospects for sales executives.
- Address client requirements proactively to prevent attrition and monitor feature utilisation for customer success teams.
- Remove obstacles, enhance workflows, and establish a unified repository for input and implementation in product operations.
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