Artificial Intillegence » Cold Emailing Automation (AI-Driven)

Build & Component Fixes:

Resolved esbuild compilation error caused by a duplicate ResponsiveContainer import in the Analytics FunnelChart component.

Fixed inbox route issues related to header handling by supporting both Map and object formats.

Added missing Lead model import and improved campaign ID handling to support both populated and non-populated campaign objects.

Enhanced the TemplateEditor component by adding missing toast notifications and improving AI generation error handling with proper try-catch blocks and user-friendly messages.

Analytics – Email Funnel Improvements:

Updated the Email Funnel chart from horizontal to vertical bar orientation.

Removed x-axis numerical labels and retained only meaningful category labels (Sent, Delivered, Opened, Clicked, Replied).

Implemented dynamic bar scaling based on actual data values with intelligent rounding and top padding, ensuring both small and large datasets render accurately.

Analytics – Recent Activity Enhancements:

Added status filter buttons (All, Sent, Opened, Clicked, Replied, Bounced) with color-coded active states.

Fixed campaign name display to correctly resolve both populated campaign objects and ID references.

Separated filtering logic so table filters do not affect charts.

Improved status detection logic using both log status and event tracking data with proper prioritization.

Dashboard – Recent Replies Fixes:

Corrected reply detection logic to identify replies via both status and event data.

Verified lead-to-campaign relationships before displaying replies.

Mapped email log data into the ReplyInbox format with lead details, campaign name, reply timestamp, and default reply type.

Sorted replies by most recent and limited results to the latest 10 entries.

Backend Security & Data Integrity:

Secured the email-logs API route with authentication middleware and user-based query scoping.

Updated campaigns API to populate leads for proper relationship verification.

Ensured all changes are linter-clean, tested, and include additional null checks and inline documentation.

Outcome:

Build issues resolved

Analytics charts and filters functioning correctly

Dashboard replies accurately reflect real campaign responses

Improved application security and data integrity

Overall stability, usability, and reliability significantly improved

Worked on application stability, analytics improvements, backend security, AI documentation automation, and knowledge transfer.

Application Fixes & Enhancements:

Fixed esbuild build error caused by duplicate import in FunnelChart component.

Resolved inbox route issues related to header handling, missing Lead import, and campaign ID access for both populated and non-populated data.

Improved TemplateEditor error handling by adding toast notifications and proper try-catch blocks for AI generation failures.

Updated Analytics Email Funnel chart to vertical bars, removed x-axis numbers, and added dynamic scaling for accurate visualization across small and large datasets.

Added status-based filters (All, Sent, Opened, Clicked, Replied, Bounced) to the Recent Activity table and fixed campaign name resolution.

Separated chart and table filtering logic to avoid data inconsistency.

Fixed Dashboard Recent Replies to correctly detect replies via status and events, verify lead-to-campaign relationships, and map data to the ReplyInbox format.

Secured email-logs API with authentication and user-based scoping, and populated campaign leads for verification.

Ensured all changes are tested, linter-clean, and improve overall functionality, security, and data integrity.

AI Automation – Documentation (Triveni Task):

Designed AI-driven automation to dynamically generate:

Business Support Documents (Business Requirement Documents) explaining end-to-end working flow and business logic.

Product Support Documents covering frontend-backend communication, API/URL flows, and technical support details.

Reviewed requirements and reference examples such as POS and AFC help guide documents.

Structured the approach for code-to-document automation to reduce manual documentation effort.

Knowledge Transfer:

Provided KT to Harish on the Fly Behavior Analysis ML Project.

Shared documentation and image-based explanations with Harish and Yogeesh for better understanding of implementation and requirements.

Outcome:

Build issues resolved

Analytics and dashboard stabilized

Backend security improved

AI documentation automation scoped and structured

KT completed successfully