Workflow Templates

Send personalized pet care tips from Google Sheets with AI Automate weekly pet wellness emails with AI-generated, location and age-specific advice. Who's it for Pet care businesses, veterinary clinics, pet subscription services, and animal shelters sending regular wellness content to pet owners. How it works Loads pets data from Google Sheets Filters pets who haven't received email in 7+ days Calculates age from birthdate (formats as "2 years and 3 months") AI generates tip - GPT-4o-mini creates climate-aware, veterinary-aligned advice based on pet type, age, and location Sends email via Gmail or SendGrid Updates timestamp in sheet to prevent duplicates Logs activity to tracking sheet Requirements APIs: Google Sheets, Airtable, Typeform or similar OpenAI (GPT-4o-mini) Gmail OAuth2 OR SendGrid, you can use Brevo, Mailchimp or any other. Google Sheet Structure: Sheet 1: Pets | Email | Owner_Name | Pet_Name | Pet_Type | Date_of_Birth | Country (ISO) | Status | Last_Email_Sent | |-------|------------|----------|----------|---------------|---------------|--------|-----------------| Sheet 2: Email_Log | Timestamp | Parent_Email | Pet_Name | Tip_Category | Status | |-----------|--------------|----------|--------------|--------| How to set up Create Google Sheet with structure above, add 2-3 test pets. Import workflow and add credentials. Update nodes: "Load Pet Info": Set your Sheet ID "Update Last_Email_Sent Date": Set Sheet ID "Log to Email_Log Sheet": Set Sheet ID Test manually with 1 active pet Enable schedule (default: Mondays 9am) How to customize Switch email provider: Enable "Send via SendGrid" node Disable "Send Health Tip using Gmail" node Update template ID Modify AI prompt: Edit "Generate Personalized Tip" node Adjust temperature Add/remove categories Use cases beyond pets Same workflow works for: Plant care** (growth stage tips) Baby milestones** (age-based parenting advice) Fitness coaching** (experience level workouts) Language learning** (study streak motivation) Just update sheet columns and AI prompt. Notes Choose only one mailing service. Country codes use ISO format (US, UK, AU, CA, etc.) AI considers location for seasonal advice.

What this workflow does This workflow monitors your Gmail inbox for new, unreplied emails and automatically generates a professional reply draft using AI. Instead of sending the email automatically, the draft is sent to Slack so a human can review and decide whether to send it. This makes it ideal for teams that want to save time on email replies while keeping full control over outgoing communication. How it works Checks Gmail on a schedule for new, unreplied emails Limits the number of emails processed per run to avoid overload Extracts the email body and sends it to an AI model Generates a polite, professional reply draft Sends the draft to a Slack channel for review Adds a Gmail label to prevent duplicate processing Setup time ~10–15 minutes Who this is for Customer support teams Freelancers and consultants Small businesses handling frequent email inquiries Anyone who wants AI-assisted email replies with human approval Requirements Gmail account Slack workspace OpenAI (or compatible AI) credentials

Description Automatically detect and escalate Product UAT critical bugs using AI, create Jira issues, notify engineering teams, and close the feedback loop with testers. This workflow analyzes raw UAT feedback submitted via a webhook, classifies it with an AI model, validates severity, and automatically escalates confirmed critical bugs to Jira and Slack. Testers are notified, and the original webhook receives a structured response for full traceability. It is designed for teams that want fast, reliable critical bug handling during UAT without manual triage. Context During Product UAT and beta testing, critical bugs are often buried in unstructured feedback coming from forms, Slack, or internal tools. Missing or delaying these issues can block releases and create friction between Product and Engineering. This workflow ensures: Faster detection of critical bugs Immediate escalation to engineering Clear ownership and visibility Consistent communication with testers It combines AI-based classification with deterministic routing to keep UAT feedback actionable and production-ready. Who is this for? Product Managers running UAT or beta programs Project Managers coordinating QA and release readiness Engineering teams who need fast, clean bug escalation Product Ops teams standardizing feedback workflows Any team handling high-volume UAT feedback Perfect for teams that want speed, clarity, and traceability during UAT. Requirements Webhook trigger (form, Slack integration, internal tool, etc.) OpenAI account (for AI triage) Jira (critical bug tracking) Slack (engineering alerts) Gmail or Slack (tester notifications) How it works Trigger The workflow starts when UAT feedback is submitted via a webhook. Normalize & Clean Incoming data is normalized (tester, build, page, message) and cleaned to ensure a consistent, AI-ready structure. AI Triage & Validation An AI model analyzes the feedback and returns a structured triage result (type, severity, summary, confidence), which is parsed and validated. Critical Bug Escalation Validated critical bugs automatically: create a Jira issue with full context trigger an engineering Slack alert Closed Loop The tester is notified via Slack or email, and the workflow responds to the original webhook with a structured status payload. What you get Automated critical bug detection during UAT Instant Jira ticket creation Real-time engineering alerts in Slack Automatic tester communication Full traceability via structured webhook responses About me : I’m Yassin a Product Manager Scaling tech products with a data-driven mindset. 📬 Feel free to connect with me on Linkedin

Description Automatically triage Product UAT feedback with AI, deduplicate it against your existing Notion backlog, create/update the right Notion item, and close the loop with the tester (Slack or email). This workflow standardizes incoming UAT feedback, runs AI classification (type, severity, summary, suggested title, confidence), searches Notion to prevent duplicates, and upserts the roadmap entry for product review. It then confirms receipt to the tester and returns a structured webhook response. Context Feature requests often arrive unstructured and get lost across channels. Product teams waste time re-triaging the same ideas, creating duplicates, and manually confirming receipt. This workflow ensures: Faster feature request triage Fewer duplicates in your roadmap/backlog Consistent structure for every feedback item Automatic tester acknowledgement Full traceability via webhook response Who is this for? Product Managers running UAT or beta programs Product Ops teams managing a roadmap backlog Teams collecting feature requests via forms, Slack, or internal tools Anyone who wants AI speed with clean backlog hygiene Requirements Webhook trigger (form / Slack / internal tool) OpenAI account (AI triage) Notion account (roadmap/backlog database) Slack and/or Gmail (tester notification) How it works Trigger: feedback received via webhook Normalize & Clean: standardizes fields and cleans message AI Triage: returns structured JSON (type, severity, title, confidence…) Notion Dedupe & Upsert: search by suggested title → update if found, else create Closed Loop: notify tester (Slack or email) + webhook response payload What you get One workflow to capture and structure feature requests Clean Notion backlog without duplicates Automatic tester confirmation Structured output for downstream automation About me : I’m Yassin a Product Manager Scaling tech products with a data-driven mindset. 📬 Feel free to connect with me on Linkedin

This automated workflow monitors your website's keyword rankings daily and sends instant alerts to your team when significant ranking drops occur. It fetches current ranking positions, compares them with historical data, and triggers notifications through Slack and email when keywords drop beyond your defined threshold. Good to know The workflow uses SERP API for accurate ranking data; API costs apply based on your usage volume Ranking checks are performed daily to avoid overwhelming search engines with requests The system tracks ranking changes over time and maintains historical data for trend analysis Slack integration requires workspace permissions and proper bot configuration False positives may occur due to personalized search results or data center variations How it works Daily SEO Check Trigger** initiates the workflow on a scheduled basis Get Keywords Database** retrieves your keyword list and current ranking data Filter Active Keywords Only** processes only keywords marked as active for monitoring Fetch Google Rankings via SERP API** gets current ranking positions for each keyword Wait For Response** Wait for gets current ranking positions Parse Rankings & Detect Changes** compares new rankings with historical data and identifies significant drops Filter Significant Ranking Drops** isolates keywords that dropped beyond your threshold (e.g., 5+ positions) Send Slack Ranking Alert** notifies your team channel about ranking drops Send Email Ranking Alert** sends detailed email reports to stakeholders Update Rankings in Google Sheet** saves new ranking data for historical tracking Generate SEO Monitoring Summary** creates a comprehensive report of all ranking changes How to use Import the workflow into n8n and configure your SERP API credentials Set up your Google Sheet with the required keyword database structure Configure Slack webhook URL and email SMTP settings Define your ranking drop threshold (recommended: 5+ position drops) Test the workflow with a small keyword set before full deployment Schedule the workflow to run daily during off-peak hours Requirements SERP API account** with sufficient credits for daily keyword checks Google Sheets access** for keyword database and ranking storage Slack workspace** with webhook permissions for team notifications Email service** (SMTP or API) for stakeholder alerts Keywords database** properly formatted in Google Sheets Database/Sheet Columns Required Google Sheet: "Keywords Database" Create a Google Sheet with the following columns: | Column Name | Description | Example | |-------------|-------------|---------| | keyword | Target keyword to monitor | "best seo tools" | | domain | Your website domain | "yourwebsite.com" | | current_rank | Latest ranking position | 5 | | previous_rank | Previous day's ranking | 3 | | status | Monitoring status | "active" | | target_url | Expected ranking URL | "/best-seo-tools-guide" | | search_volume | Monthly search volume | 1200 | | difficulty | Keyword difficulty score | 65 | | date_added | When keyword was added | "2025-01-15" | | last_checked | Last monitoring date | "2025-07-30" | | drop_threshold | Custom drop alert threshold | 5 | | category | Keyword grouping | "Product Pages" | Customising this workflow Modify ranking thresholds** in the "Filter Significant Ranking Drops" node to adjust sensitivity (e.g., 3+ positions vs 10+ positions) Add competitor monitoring** by duplicating the SERP API node and tracking competitor rankings for the same keywords Customize alert messages** in Slack and email nodes to include your brand voice and specific stakeholder information Extend to multiple search engines** by adding Bing or Yahoo ranking checks alongside Google Implement ranking improvement alerts** to celebrate when keywords move up significantly Add mobile vs desktop tracking** by configuring separate SERP API calls for different device types

What this workflow does This workflow implements a two-stage news automation system designed for reusable and topic-driven email delivery. News articles are continuously collected from multiple platforms using RSS feeds and stored in a vector database with semantic embeddings and category metadata. Instead of fetching news on demand, the workflow separates daily ingestion from weekly delivery. This allows the same news data to be reused across different topics, audiences, or delivery schedules. On a weekly basis, relevant articles are retrieved from the vector store based on defined areas of interest and item limits. The selected news is then processed by an AI agent, which converts the raw articles into a structured, email-ready format before sending the final content to users. How it works News articles are collected daily from multiple RSS feeds Articles are categorized and stored in a vector database On a weekly trigger, topic preferences are evaluated Relevant articles are retrieved using vector-based search An AI agent formats the content for email delivery The email is sent to the user Setup To use this workflow, complete the following steps: Add and configure your RSS feed sources Connect a vector database and embedding model Configure AI model credentials for content generation Set up email service credentials Define weekly scheduling and topic inputs Test retrieval and email output Customization You can customize this workflow by: Adding or removing RSS feed sources Adjusting news categories or topic filters Changing the number of articles retrieved per topic Modifying the AI agent’s writing tone or structure Reusing the vector store for other content workflows Updating email frequency or delivery format Requirements RSS feed URLs Vector database credentials AI model credentials Email service credentials

Match Resumes to Jobs Automatically with Gemini AI and Decodo Scraping Sign up for Decodo HERE for Discount This automation intelligently connects candidate profiles to job opportunities. It takes an intake form with a short summary, resume link, and optional LinkedIn profile, then enriches the data using Decodo and Gemini. The workflow analyzes skills, experience, and role relevance, ranks top matches, and emails a polished HTML report directly to your inbox—saving hours of manual review and matching effort. Who’s it for? This template is designed for recruiters, hiring managers, and talent operations teams who handle large candidate volumes and want faster, more accurate shortlisting. It’s also helpful for job seekers or career coaches who wish to identify high-fit openings automatically using structured AI analysis. How it works Receive an intake form containing a candidate’s resume, summary, and LinkedIn URL. Parse and summarize the resume with Gemini for core skills and experience. Enrich the data using Decodo scraping to gather extra profile details. Merge insights and rank job matches from Decodo’s job data. Generate an HTML shortlist and email it automatically through Gmail. How to set up Connect credentials for Gmail, Google Gemini, and Decodo. Update the Webhook path and test your form connection. Customize variables such as location or role preferences. Enable Send as HTML in the Gmail node for clean reports. Publish as self-hosted if community nodes are included.

How It Works This workflow automates tenant screening by analyzing payment history, credit, and employment data to predict rental risks. Designed for property managers, landlords, and real estate agencies, it solves the challenge of objectively evaluating tenant reliability and preventing payment defaults.The system runs daily assessments, fetching rent payment history, credit bureau reports, and employment records. An AI agent merges this data, calculates risk scores, and routes alerts based on severity. High-risk tenants trigger immediate email notifications for intervention, medium-risk cases post to Slack for monitoring, while low-risk updates save quietly to databases. Automated collection workflows initiate for high-risk cases. Setup Steps Configure payment history, credit bureau, and employment credentials in fetch nodes Add OpenAI API key for risk analysis and set Gmail/Slack credentials for alerts Customize risk score thresholds and routing rules in workflow logic Prerequisites Payment system API, credit bureau access, employment verification API Use Cases Rental application screening, existing tenant monitoring Customization Modify risk scoring criteria, adjust alert thresholds Benefits Reduces defaults through early detection, eliminates screening bias

This workflow automates customer email support by combining Gmail, AI classification, and a knowledge base to provide instant, accurate, and friendly responses. It’s designed for businesses that want to improve customer satisfaction while reducing manual workload. 🚀 How it Works Gmail Trigger The workflow listens for new incoming Gmail messages. Text Classification Each email is classified using AI as either Customer Support or Other. If it’s Other, the workflow stops. If it’s Customer Support, the email continues to the AI agent. AI Agent with Knowledge Base The AI agent: Reads the customer’s message. Searches the Pinecone Knowledge Base for FAQs and policies. Generates a helpful, polite, and detailed reply using an OpenRouter model. Signs off as Mrs. Helpful from Tech Haven Solutions. Reply to Gmail The drafted email is automatically sent back to the customer. 💡 Value ✅ Save Time – No more manual triaging and drafting of replies. ✅ Consistency – Every answer is based on your own FAQ/policies. ✅ Customer Satisfaction – Fast, friendly, and accurate responses 24/7. ✅ Scalable – Handle higher email volume without scaling headcount. 🔑 Credentials Needed To use this workflow, connect the following accounts: Gmail OAuth2** → for receiving and sending emails. OpenRouter API** → for text classification and AI-generated replies. OpenAI API** → for embeddings (to connect FAQs with AI). Pinecone API** → for storing and retrieving knowledge base content. 🛠 Example Use Case A customer writes: > “Hi, I placed an order last week but haven’t received a shipping confirmation yet. Can you check the status?” The workflow will: Detect it’s a support-related email. Retrieve order policy information from the knowledge base. Generate a friendly response explaining order tracking steps. Automatically reply to the customer in Gmail. ⚡️ Setup Instructions Import this workflow into your n8n instance. Connect your Gmail, OpenRouter, OpenAI, and Pinecone credentials. Populate your Pinecone knowledge base with FAQs and policies. Activate the workflow. From now on, all support-related emails will be automatically answered by your AI-powered support agent.

📄 Smart Lead Capture, Scoring & Slack Alerts This workflow captures new leads from Typeform, checks for duplicates in HubSpot CRM, enriches and scores them, assigns priority tiers (Cold, Warm, Hot), and instantly notifies your sales team in Slack. 🔧 How It Works Typeform Trigger → Monitors form submissions and passes lead details into the workflow. HubSpot Deduplication → Searches HubSpot by email before creating a new record. Conditional Routing → If no match → Creates a new contact in HubSpot. If match found → Updates the existing contact with fresh data. Lead Scoring (Function Node) → Custom JavaScript assigns a score based on your rules (e.g. company email, job title, engagement signals, enrichment data). Tier Assignment → Categorizes the lead as ❄️ Cold, 🌡 Warm, or 🔥 Hot based on score thresholds. Slack Notification → Sends formatted lead alerts to a dedicated sales channel with priority indicators. 👤 Who Is This For? Sales teams who need to prioritize hot leads in real-time. Marketing teams running inbound lead capture campaigns with Typeform. RevOps teams that want custom scoring beyond HubSpot defaults. Founders/SMBs looking to tighten lead-to-revenue pipeline with automation. 💡 Use Case / Problem Solved ❌ Duplicate contacts clogging HubSpot CRM. ❌ Manual lead triage slows down response time. ❌ HubSpot’s default scoring is rigid. ✅ Automates lead creation + scoring + notification in one flow. ✅ Sales teams get immediate Slack alerts with context to act fast. ⚙️ What This Workflow Does Captures lead data directly from Typeform. Cleans & deduplicates contacts before pushing to HubSpot CRM. Scores and categorizes leads via custom logic. Sends structured lead alerts to Slack, tagged by priority. Provides a scalable foundation you can extend with data enrichment (e.g., Clearbit, Apollo). 🛠️ Setup Instructions 🔑 Prerequisites Typeform account with API access → Typeform Developer Docs HubSpot CRM account with API key or OAuth → HubSpot API Docs Slack workspace & API access → Slack API Docs (Optional) n8n automation platform to build & run → n8n Hub 📝 Steps to Configure Typeform Node (Trigger) Connect your Typeform account in n8n. Select the form to track submissions. Fields typically include: first name, last name, email, company, phone. HubSpot Node (Search Contact) Configure a search by email. Route outcomes: Not Found → Create Contact Found → Update Contact HubSpot Node (Create/Update Contact) Map Typeform fields into HubSpot (email, name, phone, company). Ensure you capture both standard and custom properties. Function Node (Lead Scoring) Example JavaScript: // Simple lead scoring example const email = $json.email || ""; let score = 0; if (email.endsWith("@company.com")) score += 30; if ($json.company && $json.company.length > 2) score += 20; if ($json.phone) score += 10; let tier = "❄️ Cold"; if (score >= 60) tier = "🔥 Hot"; else if (score >= 30) tier = "🌡 Warm"; return { ...$json, leadScore: score, leadTier: tier }; Customize rules based on your GTM strategy. Reference → n8n Function Node Docs Slack Node (Send Message) Example Slack message template: 🚀 New Lead Alert! 👤 {{ $json.firstname }} {{ $json.lastname }} 📧 {{ $json.email }} | 🏢 {{ $json.company }} 📊 Score: {{ $json.leadScore }} — {{ $json.leadTier }} Send to dedicated #sales-leads channel. Reference → Slack Node in n8n 📌 Notes & Extensions 🔄 Add enrichment with Clearbit or Apollo.io before scoring. 📊 Use HubSpot workflows to trigger nurturing campaigns for ❄️ Cold leads. ⏱ For 🔥 Hot leads, auto-assign to an SDR using HubSpot deal automation. 🧩 Export data to Google Sheets or Airtable for analytics.

🔗 Automated Blockchain Transaction Audit System Transform your blockchain compliance workflow with this enterprise-grade automation that monitors transactions across Ethereum and Solana networks, automatically generates professional audit reports, and maintains complete documentation trails. 🚀 What This Workflow Does This comprehensive automation system: 📊 Multi-Chain Monitoring**: Real-time transaction tracking for Ethereum (via Alchemy API) and Solana networks 🤖 AI-Powered Risk Analysis**: Intelligent scoring algorithm that evaluates transaction risk (0-100 scale) 📄 Automated PDF Generation**: Professional audit reports created instantly using APITemplate.io ☁️ Cloud Storage Integration**: Seamless uploads to Google Drive with organized folder structure 📋 Database Management**: Automatic Notion database entries for complete audit trail tracking 📧 Smart Notifications**: Multi-channel alerts to finance teams with detailed transaction summaries 🔒 Compliance Verification**: Built-in KYC/AML checks and regulatory compliance monitoring 💼 Perfect For FinTech Companies** managing blockchain transactions DeFi Protocols** requiring audit documentation Enterprise Finance Teams** handling crypto compliance Blockchain Auditors** automating report generation Compliance Officers** tracking regulatory requirements 🛠 Key Integrations Alchemy API** - Ethereum transaction monitoring Solana RPC** - Native Solana network access APITemplate.io** - Professional PDF report generation Google Drive** - Secure cloud document storage Notion** - Comprehensive audit database Email/SMTP** - Multi-recipient notification system Etherscan/Solscan** - Smart contract verification ⚡ Technical Highlights 10 Optimized Nodes** with parallel processing capabilities Sub-30 Second Processing** for complete audit cycles Enterprise Security** with credential management Error Handling** with automatic retry mechanisms Scalable Architecture** supporting 1000+ transactions/hour Risk Scoring Algorithm** with customizable parameters 📊 Business Impact 80% Cost Reduction** in manual audit processes 95% Error Elimination** through automation 100% Compliance Coverage** with immutable audit trails 70% Time Savings** for finance teams 🔧 Setup Requirements Before using this workflow, ensure you have: Alchemy API key for Ethereum monitoring APITemplate.io account with audit report template Google Drive service account with folder permissions Notion workspace with configured audit database SMTP credentials for email notifications Etherscan API key for contract verification 📈 Use Cases Transaction Compliance Monitoring**: Automatic flagging of high-risk transactions Regulatory Reporting**: Scheduled audit report generation for authorities Internal Auditing**: Complete documentation for financial reviews Risk Management**: Real-time scoring and alert systems Multi-Chain Portfolio Tracking**: Unified reporting across blockchain networks 🎯 Why Choose This Workflow This isn't just another blockchain monitor - it's a complete document management ecosystem that transforms raw blockchain data into professional, compliant documentation while maintaining enterprise-grade security and scalability. Perfect for organizations serious about blockchain compliance and audit trail management! 🚀 🔄 Workflow Process Webhook Trigger receives blockchain event Parallel Monitoring queries Ethereum & Solana networks AI Processing analyzes transaction data and calculates risk Document Generation creates professional PDF audit reports Multi-Channel Distribution uploads to Drive, logs in Notion, sends notifications Verification & Response confirms all processes completed successfully Ready to automate your blockchain compliance? Import this workflow and transform your audit processes today! ✨

GPT-4o Resume Screener with Error Handling - Google Sheets & Drive Pipeline How it works Enterprise-grade resume screening automation built for production environments. This workflow combines intelligent AI analysis with comprehensive error handling to ensure reliable processing of candidate applications. Every potential failure point is monitored with automatic recovery and notification systems. Core workflow steps: Intelligent Email Processing - Monitors Gmail with attachment validation and file type detection Robust File Handling - Multi-format support with upload verification and extraction validation Quality-Controlled AI Analysis - GPT-4o evaluation with output validation and fallback mechanisms Verified Data Extraction - Contact and qualification extraction with data integrity checks Dual Logging System - Success tracking in main dashboard, error logging in separate audit trail Error Recovery Features: Upload failure detection with retry mechanisms Text extraction validation with quality thresholds AI processing timeout protection and fallback responses Data validation before final logging Comprehensive error notification and tracking system Set up steps Total setup time: 25-35 minutes Core Credentials Setup (8 minutes) Gmail OAuth2 with attachment permissions Google Drive API with folder creation rights Google Sheets API with read/write access OpenAI API key with GPT-4o model access Primary Configuration (12 minutes) Configure monitoring systems - Set up Gmail trigger with error detection Establish file processing pipeline - Create Drive folders for resumes and configure upload validation Deploy dual spreadsheet system - Set up main tracking sheet and error logging sheet Initialize AI processing - Configure GPT-4o with structured output parsing and timeout settings Customize job requirements - Update role specifications and scoring criteria Error Handling Setup (10 minutes) Configure error notifications - Set administrator email for failure alerts Set up error logging spreadsheet - Create audit trail for failed processing attempts Customize timeout settings - Adjust processing limits based on expected file sizes Test error pathways - Validate notification system with sample failures Advanced Customization (5 minutes) Modify validation thresholds for resume quality Adjust AI prompt for industry-specific requirements Configure custom error messages and escalation rules Set up automated retry logic for transient failures Production-Ready Features: Comprehensive logging for compliance and auditing Graceful degradation when services are temporarily unavailable Detailed error context for troubleshooting Scalable architecture for high-volume processing Template Features Enterprise Error Management Multi-layer validation at every processing stage Automatic error categorization and routing Administrative alerts with detailed context Separate error logging for audit compliance Timeout protection preventing workflow hangs Advanced File Processing Upload success verification before processing Text extraction quality validation Resume content quality thresholds Corrupted file detection and handling Format conversion error recovery Robust AI Integration GPT-4o processing with output validation Structured response parsing with error checking AI timeout protection and fallback responses Failed analysis logging with manual review triggers Retry logic for transient API failures Production Monitoring Real-time error notifications via email Comprehensive error logging dashboard Processing success/failure metrics Failed resume tracking for manual review Audit trail for compliance requirements Data Integrity Controls Pre-logging validation of all extracted data Missing information detection and flagging Contact information verification checks Score validation and boundary enforcement Duplicate detection and handling Designed for HR departments and recruiting agencies that need reliable, scalable resume processing with enterprise-level monitoring and error recovery capabilities.