Quick Overview This workflow runs on a weekday morning schedule (or manually) to pull the active Jira sprint and its issues, compute sprint health metrics, use an OpenRouter-hosted OpenAI model to assess slip risk, and post a motivating alert to a Slack channel when the sprint is behind. How it works Runs every weekday at 08:00 (or when executed manually). Calls the Jira Software Cloud Agile API to fetch the board’s active sprint and all issues in that sprint, including status, labels, and story points. Calculates sprint timing, completion percentage, slip margin, velocity gap, and a list of potentially blocked issues based on labels or status. Sends the computed metrics to an OpenRouter (OpenAI) chat model to return a structured JSON risk assessment (on_track, at_risk, or critical) with recommendations and tickets to watch. Parses the model output into JSON and merges it with the computed sprint metrics for reporting. If the risk level is not on_track, a second OpenRouter (OpenAI) agent drafts a team-focused status update and posts it to the configured Slack channel.
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WHandle WhatsApp support chats with OpenRouter, Pinecone, and Gemini
Quick overview This template implements a WhatsApp support suite that logs inbound events to a dashboard API, routes conversations through an OpenRouter-powered AI agent with Pinecone RAG and memory, exposes a webhook for human outbound replies, and provides a webhook to summarize recent chats for handoff. How it works Triggers on WhatsApp Cloud API events and routes status updates (sent/delivered/read) to a dashboard API endpoint for storage. For inbound messages, looks up the contact in the dashboard API and normalizes the message into a consistent schema (sender, type, timestamp, and best-effort content). If the message contains media (image/video/audio/document), fetches the WhatsApp media URL, downloads the file, uploads it to the dashboard’s media endpoint, and attaches the resulting media URL and MIME type. Stores inbound messages and reactions in the dashboard API, then checks via the cases endpoint whether the sender already has an open case. If the inbound message is text and no open case is found, queries Pinecone as a tool (using Google Gemini embeddings), uses an OpenRouter chat model with conversation memory to draft a reply or create a new case via the dashboard API,
Manage Google and Trustpilot reviews with OpenAI and Slack
Quick overview This workflow runs hourly to fetch new Google Business Profile and Trustpilot reviews, deduplicates them, uses OpenAI via a LangChain agent to draft sentiment-aware replies, escalates negative reviews in Slack, and routes positive replies to Slack for approval before posting the reply back to Trustpilot. How it works Runs every hour on a schedule. Fetches the latest reviews from the Google Business Profile API and the Trustpilot API and combines the results. Deduplicates reviews by tracking previously seen review IDs in workflow static data and stops if there are no new reviews. Processes each new review and uses OpenAI (via a LangChain agent) to generate structured JSON containing sentiment, a draft reply, and an optional suggested resolution. Sends negative reviews to a Slack channel for the owner along with the suggested resolution. Sends positive draft replies to Slack for one-tap approval (with a 24-hour timeout) and, if approved, publishes the reply to the Trustpilot API. Sends a Slack alert to the ops channel if the workflow errors. Setup Configure authentication and replace placeholders for the Google Business Profile reviews endpoint (account and location) i
WSend weekly blended ad performance reports with Meta, Google Ads, GA4 and OpenAI
Quick overview This workflow runs every Monday at 8am to pull the last 7 days of performance from Meta Ads, Google Ads, and GA4, calculate blended KPIs, generate an OpenAI-powered narrative summary, email an HTML report via Gmail, and post an internal update (and errors) to Slack. How it works Runs every Monday at 8am on a scheduled trigger. Fetches the last 7 days of spend and engagement metrics from the Meta Ads Insights API, campaign cost and conversion metrics from the Google Ads API, and conversions and revenue by channel from the GA4 Reporting API. Combines the three datasets and calculates blended KPIs including total spend, total conversions, total revenue, and ROAS. Sends the computed metrics to an OpenAI chat model to generate a 3–4 sentence client-friendly performance summary with one risk and one recommendation. Builds a simple HTML report containing the KPIs and AI summary. Emails the HTML report to the client via Gmail and posts a brief confirmation with spend and ROAS to a Slack channel. If the workflow fails, posts an error alert message to an ops Slack channel. Setup Configure authentication for the HTTP requests to Meta Ads (access token), Google Ads (OAuth/access