Feature Request

Business Problem: Currently, when the platform updates its underlying AI models, all users are forced onto the new version immediately. In a professional production environment, even subtle changes in how a model interprets instructions can lead to unpredictable behavior and output regression. For users who have spent significant time "Prompt Engineering" their AI for specific, high-precision tasks (such as intent routing, data extraction, or strict formatting), these forced updates often break existing logic. A model that was previously reliable may suddenly change its tone, formatting, or compliance with negative constraints, forcing teams to manually re-test and re-adjust their entire automation setup. Desired Outcome: Model Version Selection: Provide a dropdown menu within the AI Agent/Workflow settings that allows users to select specific model versions (e.g., GPT 5.2 vs. latest). Version Locking: Allow users to "Lock" their AI to a specific version so it does not update automatically when the platform releases a new default. Legacy Support: Ensure that older versions remain available for a reasonable grace period, giving businesses time to migrate and test their instructions before the old version is sunset. Impact on AI Results: Forced updates compromise the reliability of AI-driven automation. Without version control, we cannot guarantee a consistent experience for our customers. Providing versioning options will allow professional users to build stable, mission-critical automations without the fear of their logic breaking overnight due to platform-wide updates.

Hello! Can you please help to to that stories mentions open the conversation? Thanks!

Business Problem Currently, conversation closure is highly dependent on manual intervention by human agents. This reliance on memory and manual effort leads to several critical issues: Operational inefficiencies: Conversations remain open indefinitely when a contact stops cluttering the workspace. Broken automation loops: Open conversations often prevent AI agents or specific Workflows from re-triggering when a contact eventually returns, leading to perceived platform malfunctions and missed follow-ups. Skewed reporting: Unclosed conversations distort reports, making it difficult for businesses to measure actual resolution times and for respond.io to demonstrate true platform value. Desired Outcome To have an option to auto-close conversations based on a pre-determined timing.This ensures a "clean" inbox state, accurate reporting, and the seamless re-triggering of AI and automation for future interactions.

Problem Statement: Currently, our AI features can’t send images or files to customers. This is a major roadblock for both sales and support teams, who often need to share product images, brochures, guides, or troubleshooting documents to give customers the full context or help them solve problems. Without this, customer interactions are less effective and require manual intervention for something as simple as sending a file. Desired Outcome: AI should be able to recognize when an image or file is needed and send the appropriate material automatically, based on the conversation. This would allow customers to get complete answers and resources instantly, boosting satisfaction, speeding up resolutions, and letting teams focus on more complex tasks—without having to jump in just to attach a file.

I would like to be able to delete or edit a message that I sent by mistake on the Messages module, and for it to also be removed for edited rom the recipient's device. 🔴 Important Note: This is NOT a limitation on respond.io . This is a limitation set by Facebook's team to all WhatsApp API accounts.

Business Problem: Digital marketing teams running Google Ads face challenges connecting ad performance directly to messaging outcomes. While Google Ads supports Click-to-WhatsApp CTAs, attribution is unreliable because WhatsApp does not allow referrer tracking. Without proper attribution, businesses cannot measure ROI accurately, optimize campaigns, or connect Google Ads conversions to lifecycle reporting. Desired Outcome: Provide clear source and campaign attribution for leads entering via Google Ads Click-to-WhatsApp campaigns. Surface Google Ads campaign performance in lifecycle reporting alongside other marketing channels. Use Cases: A retail business runs Google Ads campaigns with Click-to-WhatsApp buttons. Each incoming lead is automatically tagged with campaign source for accurate ROI measurement. A company wants to optimize ad spend by sending conversion goals (e.g., qualified leads, closed deals) back to Google Ads for smarter bidding. Marketing teams can view Google Ads contribution directly in lifecycle reports

Business Problem : For some businesses on the Growth plan, having access to more than one workspace is important for testing, separating teams, or managing different operational setups. However, the current jump from 1 workspace on Growth to 10 workspaces on Advanced is too large for customers who need only a small increase, not a full plan upgrade. Without a flexible option for additional workspaces, Growth plan users may be forced to upgrade for a capability they need in moderation, while paying for other Advanced plan features that may not be relevant to their use case. Desired Outcome : Offer additional workspaces as a paid add-on to the Growth plan. This would: Give customers a more flexible path to scale workspace usage based on actual needs Let teams test or separate operations without requiring an upgrade to a higher-tier plan Improve packaging by allowing customers to pay for the specific capability they need, without bundling it with unrelated advanced features

Business Problem: The current Google Sheets integration is affected by the Google Sheets API rate limit of 60 requests per user, per project, per minute. This is a limitation from Google's side ref . As a result, when a workflow runs for a large batch of contacts (for example, 100 contacts), some of the “Add Google Sheet Row” actions may fail or be skipped once the rate limit is reached. This causes: Missing rows / incomplete data in Google Sheets Inconsistent workflow outcomes Risk of losing important contact or campaign information Desired Outcome: Improve the Google Sheets workflow step so it can handle rate limits more reliably and prevent data loss when processing larger volumes of contacts.

Business Problem Customers are currently unable to increase their AI Credits once they reach their limit, forcing them to wait until the next billing cycle. This creates a significant disruption in critical business work flows, such as automated customer support and lead qualification, which rely on uninterrupted AI availability. Desired Outcome To enable customers to top up their AI Credits both manually and or automatically (e.g. similar to MAC overcharges).