Storytell.aivBeta
Storytell.ai is an advanced AI-powered SaaS platform, crafted for enterprise use, that converts unstructured data into actionable insights. It enhances the decision-making process by simplifying data
What is Storytell.aivBeta?
Storytell.ai is a cloud-based platform designed to help organisations make sense of unstructured data. It uses AI to extract key insights from documents, spreadsheets, emails, and other data sources, then presents those insights in a structured format that teams can act on. The platform integrates with common enterprise tools like SharePoint and Salesforce, so data flows naturally into your existing workflows. It's built for medium to large organisations that need multiple teams to collaborate on data analysis without creating isolated information silos. The DistillAI algorithm identifies important patterns automatically, whilst Story Tiles allow you to organise and share findings flexibly across departments.
Key Features
DistillAI algorithm
Automatically extracts key insights and patterns from unstructured data sources
Story Tiles™
Flexible data organisation tool that lets teams structure and share information in customisable formats
Enterprise integrations
Connects with SharePoint, Salesforce, and other business systems
Collaboration workspace
Ambient cloud environment designed for cross-functional teams to work together
SOC2 Type 2 certification
Enterprise-grade security for regulated industries
Data aggregation
Consolidates information from multiple sources into a single analysable view
Pros & Cons
Advantages
- Reduces time spent on manual data analysis and report writing
- Integrates with existing enterprise software rather than requiring separate systems
- Designed specifically for compliance-heavy industries with proper security certifications
- Enables better collaboration between departments by centralising insights
Limitations
- Freemium tier may have limited features; pricing for full functionality is unclear
- Requires enterprise data infrastructure; not suited for small teams or individuals
- Depends on good data quality as input; poorly structured source data may produce inconsistent results
Use Cases
Sales teams analysing customer feedback and deal notes to identify trends
Technical writers using documentation and product data to create accurate manuals
Compliance officers reviewing unstructured reports and communications for regulatory issues
Product teams consolidating user research, support tickets, and feature requests into practical advice
Finance departments extracting data from invoices, contracts, and audit documents