Monitors social media inboxes and web forms, classifies and summarizes leads with GPT-4.1, logs details to Google Sheets, creates Jira tasks, and notifies Slack, with weekly reports for team insights.
The AI agent automatically captures inbound social media inquiries and web-form leads and routes them into a structured workflow. It classifies each lead into categories like Sales, Support, Partnership, Influencer Inquiry, or General Lead and generates a concise summary. It logs lead data to Google Sheets, creates Jira tasks, notifies Slack in real time, and assembles a weekly report for team review.
Automates lead intake, triage, and routing across Slack, Jira, and Sheets.
Filter incoming messages for predefined marketing keywords and discard noise.
Classify leads into categories such as Sales, Support, Partnership, Influencer Inquiry, or General Lead.
Summarize each lead with GPT-4.1 into a concise one-liner.
Log structured lead data to Google Sheets, including username, source, category, summary and timestamp.
Create a Jira task automatically with the AI-generated summary and details.
Notify Slack with an alert containing key lead details and links.
The AI agent consolidates multi-tool actions into a single, auditable flow, reducing manual errors and providing traceable lead handling.
A simple 3-step flow.
The AI agent receives new messages from social media inboxes or web forms and triggers processing.
Uses GPT-4.1 to classify the lead into categories (Sales, Support, Partnership, Influencer Inquiry, General Lead) and generate a one-line summary.
Logs lead data to Google Sheets, creates a Jira task, and sends a Slack alert; schedules weekly reporting.
One realistic scenario.
Scenario: A LinkedIn message arrives from a potential partnership inquiry at 09:12. The AI agent captures it via the webhook, filters and classifies it as Partnership, generates a one-line summary, logs to Google Sheets with source LinkedIn, creates a Jira task in the Marketing-Lead project, and posts a Slack alert to the #leads channel. By week's end, the lead appears in the weekly report alongside other partnerships.
One supporting sentence.
Wants real-time visibility into inbound inquiries from social channels.
Needs fast triage to prioritize leads and track progress.
Handles multiple client campaigns and requires consistent lead routing.
Receives inquiries from communities and wants automated triage.
Requires auditable processes and centralized data.
Wants configurable pipelines with clear logging.
One supporting sentence with short explanation.
Classifies leads and generates concise summaries.
Logs structured lead data (username, source, category, summary, timestamp).
Creates tasks with the AI-generated summary and details.
Sends instant alerts and weekly digest to selected channels.
One supporting sentence with short explanation.
One supporting sentence with short explanation.
The AI agent uses a GPT-4.1 prompt with predefined categories (Sales, Support, Partnership, Influencer Inquiry, General Lead). It analyzes message content, source context, and keywords to assign a category and generate a concise one-line summary. The output is structured and stored with the lead data for downstream actions, such as ticket creation and Slack notification. You can customize categories and prompts to reflect your business context. The system also records timestamps to support auditing and weekly reporting.
Yes. You can add or remove keywords in the Lead Keyword Filter. The filter is implemented in a code node you can edit to fit your campaigns. Changes take effect without redeploying the entire AI agent. After updating keywords, run a test to verify that relevant messages are captured and irrelevant ones are ignored.
Data is stored in your configured Google Sheets and Jira projects with access controls. All transmissions rely on your existing authentication tokens and API keys. You can enforce least-privilege access and rotate credentials as part of standard security practices. Depending on your deployment, you can route data through a VPN or private network if required.
Weekly reports are generated on a configurable schedule, typically at a fixed day and time each week. The report aggregates leads from the previous week, computes category and source counts, and highlights notable examples. You can customize the report format and delivery channel (e.g., Slack or email) to fit your workflow. The schedule can be adjusted as your business rhythms change.
If a single integration fails, the AI agent logs the incident and continues processing other leads. It retries failed actions and surfaces errors in a central dashboard. You can re-run failed tasks or reconfigure credentials without stopping the workflow. This ensures downstream actions are not blocked by a single point of failure.
Yes. The agent is designed to ingest data from multiple sources via webhooks or forms. You can add new sources by configuring additional webhook endpoints and mapping the incoming fields to your existing Lead schema. The classification and logging logic remains consistent across sources, ensuring uniformity in the data model. This makes extending to new platforms straightforward with minor configuration.
All processing steps emit structured logs that include source, category, timestamp, and outcome. You can view these in your monitoring panel and export them for auditing. If errors occur, an alert is sent to your Slack channel and a Jira task is created for troubleshooting. Regular audits help keep data quality high and operations transparent.
Monitors social media inboxes and web forms, classifies and summarizes leads with GPT-4.1, logs details to Google Sheets, creates Jira tasks, and notifies Slack, with weekly reports for team insights.
