AI-powered Classification
Lutra’s AI-powered classification system helps users organize their Outlook inboxes with precision and flexibility. By understanding the context and intent behind email content, Lutra goes beyond basic keyword detection, ensuring accurate categorization and streamlined organization
Capabilities
Context-Aware Classification: Lutra’s AI can classify emails based on nuanced content, such as identifying inquiries, complaints, sales leads, or internal updates. It uses the latest language models to understand the content and map it to corresponding categories.
Customizable Categories: Sort emails into predefined categories aligned with your or your organizational needs.
Playbook Automation: Create playbooks that run the classification process for you automatically.
Common Use Cases
Customer Support: Automatically tag and prioritize support emails, routing them to the right team or agent.
Sales Management: Sort and label incoming leads, ensuring fast follow-ups and reducing response times.
Internal Organization: Categorize meeting requests, internal memos, and team updates for better inbox management.
Project Coordination: Group emails by project or client for easier tracking and reference.
Industry Newsletters for Data Extraction: Classify emails containing industry newsletters to extract relevant data for analysis or sharing with your team.
Partner Emails for Project Timelines: Identify and organize emails from project partners to extract timelines, due dates, and key milestones.
Customer Support Requests: Classify customer inquiries to route them to the appropriate teams or systems for faster resolution.
Invoice and Payment Tracking: Organize invoices or payment confirmation emails to extract financial data for accounting or reconciliation purposes.
User Defined Categories
Lutra allows users to define their own categories based on specific needs or organizational preferences.
How to use Lutra
Lutra will automatically ask for account permissions when it needs to connect to them, you do not need to configure the integrations beforehand. To see what accounts have been connected to Lutra, you can visit the integrations page.
Start a new Chat with Lutra, and ask it to retrieve emails in your Outlook, for example, you can ask it to:
"Retrieve the last 3 emails in my Outlook inbox"
"Retrieve the last 3 emails sent to [email protected]"
Ask Lutra to perform analysis on the emails, for example:
"Classify the sentiment of the emails into positive, negative, neutral"
"For emails that have a negative sentiment, classify into X, Y, Z, categories for the issue the user ran into"
Export the data into a Google sheet or other resources for example:
"Save the data you extracted into a new Google sheet"
"Send me an email with a summary of the data you extracted."
"Send the #general channel a message with the data extracted"
Save the process as a playbook to scale and automate it.
Click on the
Create a Playbook button to make a playbook.Ask Lutra to scale up the process on many more emails, or schedule the playbook to automate it.
Tips for best results
Start Small: It’s always a good idea to test Lutra on a small number of examples before scaling up. Start with a limited dataset or a few emails to ensure the process runs smoothly.
Provide Feedback: Lutra uses AI to adapt and improve based on your feedback. If the initial results don’t meet your expectations, let Lutra know. It can fine-tune its approach, improving both the data it extracts and how it structures the output.
Provide feedback directly, for example:
"You missed the data X, Y, Z, please try again."
"Please add these categories A, B, C to the possible labels"
Scale and Automate: Once you’re happy with the results, you can scale up the process by asking Lutra to create playbooks to run on many more emails.
Review Details: You can review the execution logs to see all the details of how Lutra performs tasks. Click on the log entries in the Chat view to expand them to see details.