New features and improvements, most recent first.
This update allows users to fuel voice campaigns through a live connection with Google Sheets, moving beyond static CSV uploads. After a quick Google account link and automatic column mapping, the system checks the sheet every 15 minutes to automatically synchronize and queue new leads, paving the way for upcoming webhook and CRM integrations.
This new feature allows users to automate recurring operational actions and continuous workflows within Dapti based on set periodicities. Designed to build daily product habits and reduce manual tracking, the system automates follow-ups, with upcoming integrations planned for Gmail and Google Calendar to seamlessly sync Dapti-generated tasks and reminders directly into the user's daily workflow.
This update eliminates abrupt hang-ups by integrating a guaranteed farewell message directly into the End Call tool, managing transitions seamlessly via a new configuration toggle. Additionally, the platform now automatically handles unintelligible audio from noisy environments, prompting users to repeat themselves instead of falling silent, ensuring a natural and continuous conversational flow.
This feature introduces Model Context Protocol (MCP) support to connect Dapta directly with external AI systems like Claude. It allows users to programmatically manage API keys, install plugins, and build or modify agents through cloud platforms, enabling seamless agent management and creation from external AI environments.
The Call Analysis tab now features an "Improve with AI" option for the Call Objective field. Designed to assist users in defining clear goals, this tool analyzes the agent's prompt and context to automatically generate an objective suggestion in the matching language. Moving forward, the product team is refining the AI logic to ensure it suggests a single, concise objective rather than multiple combined goals, keeping post-call success metrics and "cost per result" tracking highly accurate and easy to evaluate.
To sustain the speed and computing power your agents require, Dapti is transitioning to a usage-based credit model. The Free plan now includes 2,000 monthly credits for testing, while the Pro plan ($99/mo) comes packed with 100,000 monthly credits to scale your operations without friction. With an average message costing just 150 credits (~$0.15), your Pro allocation is built to go a long way.
This feature introduces automated email alerts triggered by specific conditions defined during post-call analysis, utilizing boolean or selector variables. The system is designed to streamline follow-ups based on call outcomes, with future iterations planned to include advanced variable selection, dynamic inputs, and Slack integration.
To deliver a more fluid and natural user experience, this new toggle allows agents to be interrupted while processing and delivering text responses from tools. Enabled by default across most text-generating tools, this feature gives users more control over active interactions, with the temporary exception of the "Ankle" tool, which is undergoing further validation.
This feature allows users to view, track, and restore historical versions of their text agents with ease. Version histories load dynamically and include detailed timestamps for every modification, giving users full control to revert changes and maintain conversational consistency.
The prompt editor received a major update to streamline the creation process for non-technical users. It introduces a rich-text "Preview" tab that hides technical code, refined "Improve with AI" functionality to modify only specific sections, and Notion-style "slash" commands for easier content structuring. Additionally, updated model selection guidance now recommends model 4.1 for speed and cost-efficiency, and 5.1 for complex tool-calling tasks.
A new invoices screen was introduced to resolve a bug that limited table displays. The updated UI features smart filters, live data from Stripe, and contextual actions. It is currently in production and responsive for mobile use.
This update introduces a comprehensive quality framework that evaluates agent performance across three core pillars: Goal/Result Quality (task achievement), Conversational Quality (communication execution), and Technical Quality (latency and system performance). Designed to provide a holistic view of operations, future iterations will display these metrics along with "cost per result" directly to the user to optimize decision-making and agent efficiency.
Rebuild the "Improve with AI" functionality in Voice Agents: fix the shortening/deleting of prompts, use the Dapti engine, improve UX with "Entire Prompt" or "Only a Section" options.
A new transfer type is available for retail agents, allowing an agent to contact a target before completing a transfer. This enables the target to receive context about the call. This feature is exclusive to retell agents and automatically creates specific prompts and actions, such as "cancel" or "bridge". This functionality is not yet available for WhatsApp or text agents.
This feature was created to evaluate calls from the Call Log, displaying scores and details to help iterate and quickly improve the quality of voice agents.
Improve date range filters for analysis: support presets, custom ranges, consistent formatting, and avoid interpretation errors that break reports or scheduling.
Redesign the contextual roles and permissions system in accounts and workspaces, with granular RBAC, inheritance, wildcards, impersonation, and secure multi-account access.
Update Flow Studio UI with more consistent interfaces: better tables, advanced filters, dynamic columns, and a clearer experience for campaigns and automations.
This newly built landing page provides a comprehensive overview of text agents, detailing how they function through building, training, launching, and understanding. It highlights key integrations for WhatsApp and website widgets, showcases various industry use cases, and includes customer success stories
Now Available on both the App Store and Google Play, this initial release focuses on an inbox feature that allows human operators to monitor and respond to text agent conversations. It provides a familiar WhatsApp-style interface for managing active conversations across different workspaces.
This update introduces "Feedback" and "Tools" columns to the call log table. The Tools column displays the number and specifics of functions executed during a call. The Feedback column tracks call results, including positive/negative ratings (likes/dislikes) and user comments, all of which are now filterable.
Integrated directly into the platform, this section provides centralized access to video tutorials previously hosted only on YouTube. Users can toggle between English and Spanish content organized by feature. Future plans include adding quizzes for credits and certifications for implementation partners.
A mobile application is currently operational on Android devices. This initial version specifically supports the inbox functionality for text agents. The app allows users to manage these agent interactions while on the go, expanding the platform's accessibility beyond the desktop interface.
New skills enable the AI to perform complex tasks like analyzing its own performance metrics and querying database structures. Most notably, a new skill allows Dapti to automatically build and modify functional workflows in Flow Studio based on natural language requests, including node validation.
In the first experience, when the user selects Voice Agents, we changed the first screen that appears, only explaining the difference between a template agent (quick creation) and a custom agent (advanced creation).
This new hub features a "What’s New" section for product updates and a notification area for maintenance alerts, webinars, and office hours. Managed via a back-office dashboard, it allows targeting messages by user group, country, language, or subscription plan (free, pro, scala, or prime) to improve feature awareness.
The company is transitioning Pro plan users to a self-service onboarding model. Personalized 1-on-1 implementation sessions for these users will officially end next Friday. Moving forward, Pro users will be guided by a new smart, chatbot-like interface designed to help them build agents independently.
This feature integrates WhatsApp business connections with both voice and text agents. Users can connect a verified phone number to an agent through a new connections panel. Crucially, the number must undergo Meta business verification to function.
This tool extracts structured information, such as sentiment and success analysis, once a text conversation ends. Users define variables that are sent via a JSON to a flow URL for further processing, such as updating CRM fields.
Currently in beta, this feature allows users to purchase Colombian and Mexican phone numbers directly through the platform by completing a regulatory bundle. It requires submitting business or individual documentation, such as identification and address verification, for approval by Twilio.
This is an iteration of the gamification feature; we've prioritized some challenges and removed others. Each challenge awards credits but aims to guide the user to spend credits through web calls that already cost credits. It's still in the experiment phase, and we'll have more iterations in the coming weeks.
These updates focus on efficiency and safety during campaign execution. Users can now run manual campaigns immediately without waiting for scheduled times. Additionally, custom batch sizes allow for specific contact amounts per round, and phone number rotation prevents numbers from being "burnt" or flagged during active runs.
This feature replaces the old multi-step setup with a streamlined, template-based onboarding process. By offering pre-built options like lead qualification or receptionist agents, the platform saw completion rates jump from roughly 12% to 41%. It guides users through language selection and starting their first call.
The marketing team is testing a 14-day free trial on the pro plan that requires credit card entry but offers all features. This model aims to convert users to paid plans after two weeks of full access. Early results showed five paying users within the first week of validation.
This knowledge-base feature on Text Agents allows agents to answer questions using uploaded documents like PDFs, CSVs, or plain text. Users can create new "brains" or reuse existing ones across both voice and text agents. Recent efforts focus on polishing PDF quality and fixing bugs related to saving brain configurations.
The new filters in the voice selection feature allow users to refine their search by accent, gender, age, and voice model providers. These improvements, supported by metadata, enable faster, clearer selection and better customization for clients, including the ability to restrict exclusive voices to specific customers.
This gamification feature uses an "earn while you learn" model to onboard users. Users complete sequential tasks—such as creating company contexts, making test calls, and editing variables—to earn credits. It aims to accelerate user activation and demonstrate platform value through guided interaction
The redesigned home replaces empty dashboards with clear entry points and popular use cases for voice and text agents. Designed to drive day-one activation, it includes credit usage tracking and links to documentation and tutorials. The goal is to reduce onboarding drop-off and improve week-one retention.
This update moves template management from the channel level to the organization level, allowing use across multiple lines and agents. Users can create, save drafts, and submit templates for WhatsApp approval directly within the platform. New features include template duplication and the ability to attach multimedia documents.
The "human in the loop" feature allows AI agents to transfer active conversations to human operators via an "agent transfer" action. Users define transfer triggers and can auto-assign chats to specific teams or individual agents for manual handling
The "Call Me Back" feature creates a bridge between text and voice agents via a website widget. It provides a form for end customers to request an instant call, immediately dialing and connecting them with an AI voice agent.
