Jira Software and Telegram integration

📘 Description This workflow is an AI-powered roto matte generation and first-pass compositing pipeline designed for VFX production. It transforms structured roto requests into multiple high-precision matte passes using AI, performs automated quality evaluation, generates production-ready Nuke scripts, and delivers fully organized assets and review tasks to the team—bridging the gap between manual rotoscoping and scalable AI-assisted matte generation. ⚙️ Step-by-Step Flow The workflow begins with a Google Sheets trigger that continuously monitors for new roto requests, acting as the intake layer for structured production data such as plate image URLs, subject descriptions, shot codes, subject type, and complexity. Once a new entry is detected, the system moves into a validation and extraction stage, where input fields are normalized, defaults are assigned, and essential attributes like sequence codes, frame ranges, QC thresholds, and project metadata are structured for downstream processing. The pipeline then performs prompt engineering and expands the request into four specialized roto passes: an alpha matte pass for clean silhouette extraction, an edge detail pass for fine hair and motion blur accuracy, a foreground isolation pass for compositing-ready subject separation, and a motion tracking reference pass enriched with tracking markers and velocity overlays. Each variation includes detailed instructions aligned with shot context and technical constraints to ensure precise AI-driven outputs. At the core of the workflow, an image-to-video generation layer constructs structured API requests and submits each variation as an independent job to the Seedance AI model, always using the plate image as a reference for accurate subject extraction. A polling mechanism continuously monitors each job at fixed intervals, ensuring that processing proceeds only after successful completion. Once rendering is complete, a metadata and automated QC layer evaluates each pass by assigning a quality score based on resolution and predefined thresholds, classifying outputs as either AI-approved or requiring manual intervention. A decision routing layer then determines the next stage—approved passes continue through the pipeline, while failed outputs trigger immediate Slack alerts for senior artist review and manual roto assignment. For approved outputs, the system generates a fully production-ready Nuke roto template, automatically configuring nodes for plate input, AI matte extraction, alpha application, edge refinement, and artist-level roto adjustments, along with structured EXR output paths and naming conventions. The pipeline then proceeds to asset handling, where generated videos are downloaded and distributed via email to requesters, while simultaneously creating Jira review tasks to ensure pipeline tracking and accountability. An aggregation layer consolidates all roto passes into a unified structured summary, combining QC results, video links, task references, and technical metadata. Finally, a team notification system delivers a comprehensive summary to the roto team via Telegram, including per-pass QC status, preview links, task tracking, output paths, and artist notes highlighting areas requiring refinement—ensuring seamless collaboration between AI outputs and human artists. 🚨 Error Handling • Global error trigger across the workflow • Instant Slack alerts with failure details • Prevents silent failures and ensures pipeline reliability 🧩 Prerequisites • Seedance API (AI video generation) • Google Sheets OAuth2 (trigger input) • Jira API (task tracking) • Gmail OAuth2 (asset delivery) • Slack OAuth2 (alerts & QC failures) • Telegram Bot (team notifications) 💡 Key Benefits ✔ Automated roto matte generation with AI-assisted precision ✔ Multiple specialized passes for production flexibility ✔ Built-in QC scoring and intelligent decision routing ✔ Auto-generated Nuke scripts with pre-configured nodes ✔ Integrated task tracking via Jira ✔ Seamless delivery via email and team notifications ✔ Scalable pipeline for high-volume roto workflows 👥 Perfect For Roto and paint teams in VFX studios Compositors working with Nuke pipelines Film and post-production environments AI-assisted rotoscoping workflows Studios handling high-volume shot processing

Description This workflow sends an instant email alert when a task in a Google Sheet is marked as Urgent, and then sends a Telegram reminder notification after 2 hours if the task still hasn’t been updated. Then a Jira ticket is created so the task enters in the formal workflow and another Telegram message is sent with the details of the issue created. It helps teams avoid missed deadlines and ensures urgent tasks get attention — without requiring anyone to refresh or monitor the sheet manually. Context In shared task lists, urgent items can be overlooked if team members aren't actively checking the spreadsheet. This workflow solves that by: Sending an email as soon as a task becomes Urgent Waiting 2 hours Checking if the task is still open Sending a Telegram reminder only if action has not been taken Creating a Jira issue Sending a Telegram message with the details of the issue created This prevents both silence and spam, creating a smart and reliable alert system. Target Users Project Managers using Google Sheets Team leads managing shared task boards Remote teams needing lightweight coordination Anyone who wants escalation notifications without complex systems Technical Requirements Google Sheets credential Gmail credential Telegram Bot + Chat ID Google Sheet with a column named Priority Jira credential Workflow Steps Trigger: Google Sheets Trigger (on update in the “Priority” column) IF Node – Checks if Priority = Urgent Send Email – Sends alert email with task name, owner, status, deadline Mark Notified = Yes in the sheet Wait 2 hours IF Status is still not resolved Send Telegram reminder create an Issue on Jira based on the information provided Send Telegram message with the details of the ticket Key Features Real-time alerts on critical tasks Simple logic (no code required) Custom email body with dynamic fields Works on any Google Sheet with a “Priority” column Telegram notification ensures the task doesn’t get forgotten Expected Output Personalized email alert when a task is marked as "Urgent" Email includes task info: title, owner, deadline, status, next step Telegram message after 2 hours if the task is still open Automatic creation of a Jira issue with the higgest priority Telegram message to notify about the new Jira ticket How it works Trigger: Watches for “Priority” updates 🔍 Check: If Priority = Urgent AND Notified is empty 📧 Email: Sends a personalized alert ✏️ Sheet Update: Marks the task as already notified ⏳ Wait: 2-hour delay 🤖 Check Again: If Status hasn’t changed → send Telegram reminder, create Jira ticket and send the details. Tutorial video: Watch the Youtube Tutorial video About me : I’m Yassin a Project & Product Manager Scaling tech products with data-driven project management. 📬 Feel free to connect with me on Linkedin

Cloudflare Incident Monitoring & Escalation Workflow 🚀 Try Decodo — Web Scraping & Data API (Coupon: TRUNG) Decodo is a powerful public data access platform offering managed web scraping APIs and proxy infrastructure to collect structured web data at scale. It handles proxies, anti-bot protection, JavaScript rendering, retries, and global IP rotation—so you can focus on data, not scraping complexity. Why Decodo Managed Web Scraping API with anti-bot bypass & high success rates Works with JS-heavy sites; outputs JSON/HTML/CSV Easy integration (Python, Node.js, cURL) for eCommerce, SERP, social & general web data 🎟️ Special Discount Use coupon TRUNG to get the Advanced Scraping API plan — 23,000 requests for $5. Who this workflow is for For DevOps, SRE, IT Ops, and Platform teams running production traffic behind Cloudflare who need reliable incident awareness without alert fatigue. Use it if you want: Continuous Cloudflare incident monitoring Clear severity-based routing Automatic escalation into JIRA Clean Slack & Telegram notifications Deduplicated, noise-controlled alerts What this workflow does This workflow polls the Cloudflare Status API, detects unresolved incidents, scores their impact, and routes them to the right channels. High-impact incidents are escalated to JIRA. Lower-impact updates are notified (or skipped) to reduce noise. How it works (high level) Runs on a fixed schedule (e.g. every 5 minutes) Fetches current Cloudflare incidents Stops early if no active issues exist Normalizes and scores incidents (severity, impact, affected service) Deduplicates previously-alerted incidents Builds human-readable notification payloads Routes by impact: High → create JIRA incident + notify Low → notify or suppress Sends alerts to Slack and Telegram Requirements Decoco Scrapper API credential n8n (self-hosted or Cloud) Cloudflare Status API (public) Slack bot (chat:write) Telegram bot + chat ID JIRA project with issue-create permission Optional LLM credentials (summarization/classification) Notes All secrets are stored in n8n Credentials Workflow is idempotent and safe to rerun No assumptions about root cause or remediation Built for production-grade incident visibility with n8n.

Description This workflow turns scattered user feedback into a structured product backlog pipeline. It collects feedback from three channels (Telegram bot, Google Form/Sheets, and Gmail), normalizes it, and sends it to an AI model that: Classifies the feedback (bug, feature request, question, etc.) Extracts sentiment and pain level Estimates business impact and implementation effort Generates a short summary Then a custom RICE-style priority score is computed, a Jira ticket is created automatically, a Notion page is generated for documentation, and a monthly product report is sent by email to stakeholders. It helps product & support teams move from “random feedback in multiple tools” to a repeatable, data-driven product intake process with zero manual triage. Context In most teams, feedback is: spread across emails, forms, and chat messages manually copy–pasted into Jira (when someone remembers) hard to prioritize objectively nearly impossible to review at the end of the month This workflow solves that by: Centralizing feedback from Telegram, Google Forms/Sheets, and Gmail Automatically normalizing all inputs into the same JSON structure Using AI to categorize, tag, summarize, and score each request Calculating a RICE-based priority adapted to your tiers (free / pro / enterprise) Creating a Jira issue with all the context and acceptance criteria Generating a Notion page for each feedback+ticket pair Sending a monthly “Product Intelligence Report” by email with insights & recommendations The result: less manual work, better prioritization, and a clear story of what users are asking for. Target Users This template is designed for: Product Managers and Product Owners SaaS teams with multiple feedback channels Support / CS teams that need a structured escalation path Project Managers who want objective, data-driven prioritization Any team that wants “feedback → backlog” automation without building a custom platform Technical Requirements You’ll need: Google Sheets credential Gmail credential Telegram Bot + Chat ID Google Form connected to a Google Sheet Jira credential (Jira Cloud) Notion credential OpenAI/ Anthropic credential for the AI analysis node An existing Jira project where tickets will be created A Notion database or parent page where feedback pages will be stored Workflow Steps The workflow is organized into four main sections: 1) Triggers (Multi-channel Intake) Telegram Trigger – Listens for new messages sent to your bot Google Form / Sheet Trigger – Listens for new form responses / rows Gmail Trigger – Listens for new emails matching your filter (e.g. [Feedback] in subject) All three paths send their payloads into a “Data Normalizer” node that outputs a unified structure: 2) Request Treated and Enriched (AI Analysis) Instant Reply (Telegram only) – Sends a quick “Thanks, we’re analysing your feedback” message User Enrichment – Enriches user tier based on mapping Message a Model (AI) classifies the feedback extracts tags scores sentiment, pain, business impact, effort generates a short summary & acceptance criteria JSON Parse / Merge – Merges AI output back into the original feedback object 3) Priority Calculation & Jira Ticket Creation Priority Calculator applies a RICE-style formula using: pain level business impact implementation effort user tier weight assigns internal priority: P0 / P1 / P2 / P3 maps to Jira priority: Highest / High / Medium / Low Create Jira Issue – Creates a ticket with: summary from AI description including raw feedback, AI analysis, and RICE breakdown labels based on tags priority based on the calculator Post-processing – Prepares a clean payload for notifications & logging IF (Source = Telegram) – Sends a rich Telegram message back to the user with: Jira key + URL category, priority, RICE score, tags, and estimated handling time Append to Google Sheet (Analytics Log) – Logs each feedback with: source, user, category, sentiment, RICE score, priority, Jira key, Jira URL Create Notion Page – Creates a documentation page linking: the feedback the Jira ticket AI analysis acceptance criteria 4) Monthly Reporting (Product Intelligence Report) Monthly Trigger – Runs once a month Query Google Sheet – Fetches all feedback logs for the previous month Aggregate Monthly Stats – Computes: feedback volume breakdown by category / sentiment / source / tier / priority average RICE, pain, and impact top P0/P1 issues and top feature requests Message a Model (AI) – Generates a written “Product Intelligence Report” with: executive summary key insights & trends top pain points strategic recommendations Parse Response: Extracts structured insights + short summary Create Notion Report Page with: metrics, charts-ready tables, insights, and recommendations Append Monthly Log to Google Sheet – Stores high-level stats for historical tracking Send Email with a formatted HTML report to stakeholders with: key metrics top issues recommendations link to the full Notion report Key Features Multi-channel intake: Telegram + Google Forms/Sheets + Gmail AI-powered triage: automatic category, sentiment, tags, and summary RICE-style priority scoring with tier weighting Automatic Jira ticket creation with full context Notion documentation for each feedback and for monthly reports Google Sheets analytics log for exploration and dashboards Monthly “Product Intelligence Report” sent automatically by email Designed to be adaptable: you can plug in your own labels, tiers, and scoring rules Expected Output When the workflow is running, you can expect: A Jira issue created automatically for each relevant feedback A confirmation email A Telegram confirmation message when the feedback comes from Telegram A Google Sheet filled with normalized feedback and scoring data A Notion page per feedback/ticket with AI analysis and acceptance criteria Every month: a Notion “Monthly Product Intelligence Report” page a summary email with key metrics and insights for your stakeholders How it works Trigger – Listens to Telegram / Google Forms / Gmail Normalize – Converts all inputs to a unified feedback format Enrich with AI – Category, sentiment, pain, impact, effort, tags, summary Score – Computes RICE-style priority and maps to Jira priority Create Ticket – Opens a Jira issue + Notion page + logs to Google Sheets Notify – Sends Telegram confirmation (if source is Telegram) Report – Once a month, aggregates everything and sends a Product Intelligence Report Tutorial Video Tutorial video: Watch the Youtube Tutorial video About me I’m Yassin a Project & Product Manager Scaling tech products with data-driven project management. 📬 Feel free to connect with me on Linkedin

🎧 IT Voice Support Automation Bot – Telegram Voice Message to JIRA ticket with OpenAI Whisper > Automatically process IT support requests submitted via Telegram voice messages by transcribing, extracting structured data, creating a JIRA ticket, and notifying relevant parties. 🧑‍💼 Who’s it for Internal teams that handle IT support but want to streamline voice-based requests. Employees who prefer using mobile/voice to report incidents or ask for support. Organizations aiming to integrate conversational AI into existing support workflows. ⚙️ How it works / What it does A user sends a voice message to a Telegram bot. The system checks whether it’s an audio message. If valid, the audio is: Downloaded Transcribed via OpenAI Whisper Backed up to Google Drive The transcription and file metadata are merged. The merged content is processed through an AI Agent (GPT) to extract structured request info. A JIRA ticket is created using the extracted data. The IT team is notified via Slack (or other channels). The requester receives a Telegram confirmation message with the JIRA ticket link. If the input is not audio, a polite rejection message is sent. 📌 Key Features Supports voice-based ticket creation Accurate transcription using Whisper Context-aware request parsing using GPT-4.1 mini Fully automated ticket creation in JIRA Notifies both IT and the original requester Cloud backup of original voice messages (Google Drive) 🛠️ Setup Instructions Prerequisites | Component | Required | |----------|----------| | Telegram Bot & API Key | ✅ | | OpenAI Whisper / Transcription Model | ✅ | | Google Drive Credentials (OAuth2) | ✅ | | Google Sheets or other storage (optional) | ⬜ | | JIRA Cloud API Access | ✅ | | Slack Bot or Webhook | ✅ | Workflow Steps Telegram Voice Message Trigger: Starts the flow when a user sends a voice message. Is Audio Message?: If false → reply "only voice is supported" Download Audio: Download .oga file from Telegram. Transcribe Audio: Use OpenAI Whisper to get text transcript. Backup to Google Drive: Upload original voice file with metadata. Merge Results: Combine transcript and metadata. Pre-process Output: Clean formatting before AI extraction. Transcript Processing Agent: GPT-based agent extracts: Requester name, department Request title & description Priority & request type Submit JIRA Request Ticket: Create ticket from AI-extracted data. Setup Slack / Email / Manual Steps: Optional internal routing or approvals. Inform Reporter via Telegram: Sends confirmation message with JIRA ticket link. 🔧 How to Customize Replace JIRA with Zendesk, GitHub Issues, or other ticketing tools. Change Slack to Microsoft Teams or Email. Add Notion/Airtable logging. Enhance agent to extract department from user ID or metadata. 📦 Requirements | Integration | Notes | |-------------|-------| | Telegram Bot | Used for input/output | | Google Drive | Audio backup | | OpenAI GPT + Whisper | Transcript & Extraction | | JIRA | Ticketing platform | | Slack | Team notification | Built with ❤️ using n8n