Genesys pushes virtual agents beyond chat with MCP and A2A. Genesys is expanding its Agentic Virtual Agent with deeper enterprise connectivity, multi-agent interoperability, improved reasoning and more natural voice interactions. 03 Sep 2026 06:38 IST Genesys is expanding its Agentic Virtual Agent as enterprises look to move customer-facing AI beyond answering questions and toward completing work across business systems. Announced at Xperience 2026 in Las Vegas, the latest Genesys Cloud enhancements add improved AI reasoning, voice capabilities, development tools and deeper connections with enterprise applications and other AI agents. The direction reflects a broader change in customer-service automation. Traditional chatbots typically work within predefined conversational flows. Agentic systems are being designed to understand intent, determine what needs to happen next and take action across business applications, while operating within controls set by the enterprise. Genesys said organizations including Global Payments, MTN South Africa, Utility Warehouse, UOL and Charles Sturt University are adopting its Agentic Virtual Agent. According to the company, some deployments have generated multimillion-dollar annualized savings, while customers have reported Net Promoter Score improvements of more than 70 points. Genesys did not provide details for every deployment behind these figures. Improving AI reasoning and reliability. Genesys is adding the Scaled Cognition APT-2 large action model to Agentic Virtual Agent. Unlike a conventional large language model focused primarily on generating responses, a large action model is intended to help an AI system reason through a task and determine the actions required to complete it. Genesys said APT-2 is designed to improve reasoning accuracy, factual grounding and execution reliability. The model supports longer workflows, richer agent specifications, faster responses and multilingual interactions. This is intended to help virtual agents handle more complicated customer requests while remaining within enterprise-defined guardrails. Reliability is becoming particularly important as AI agents gain the ability to interact directly with customer records, payment systems, service platforms and other operational applications. Making voice agents more natural. Genesys is also improving voice interactions through new native capabilities and integrations with ElevenLabs and Deepgram. An End-of-Turn Detection capability is designed to determine when a customer has finished speaking. This can reduce awkward pauses and interruptions that often make automated voice interactions feel unnatural. Contextual Tuning will allow the virtual agent to adjust its terminology, tone and speaking style according to the organization and the context of an interaction. Genesys is also integrating ElevenLabs for voice generation and Deepgram for real-time conversational speech recognition. Deepgram integration is available now, according to Genesys. ElevenLabs capabilities are expected during the third quarter of the company's current fiscal year, covering August 1-October 31, 2026. Connecting AI agents to enterprise systems. One of the more significant changes is deeper support for Model Context Protocol (MCP). MCP provides a standardized way for AI systems to connect with external tools and data sources. In practical terms, it can allow an AI agent to move beyond conversation and interact with the applications needed to complete a customer's request. Building on capabilities gained through its Pinkfish acquisition, Genesys said Agentic Virtual Agent can connect through more than 500 enterprise integrations and access over 25,000 MCP-compatible tools. These connections can extend into customer relationship management (CRM), enterprise resource planning (ERP), IT service management, billing, knowledge management and collaboration applications. Consider a customer querying an incorrect bill. Instead of merely explaining the billing process, an agent could potentially retrieve account information, check relevant policies and initiate the backend steps required to resolve the issue. The important shift is from generating an answer to executing a workflow. A2A brings multi-agent collaboration. Genesys is also introducing support for Agent2Agent (A2A) interoperability. While MCP helps an AI agent access tools and systems, A2A is intended to enable different AI agents to communicate and work together. Genesys said its virtual agent will be able to collaborate with specialized AI agents operating on enterprise platforms such as Salesforce and ServiceNow. A customer-facing Genesys agent, for example, could identify a billing problem and delegate part of the process to another specialized enterprise agent. The agents could coordinate different stages of the workflow while maintaining the context of the original customer interaction. This multi-agent architecture could become increasingly important as enterprises deploy separate AI agents for customer service, IT operations, finance, sales and other business functions. Developers get more ai-assisted tools. Genesys is also simplifying the process of building virtual-agent workflows. With spec-driven development, teams will be able to describe desired experiences and outcomes using existing material such as standard operating procedures, process documents and interaction transcripts. AI can then help translate this information into configurations that can be tested and governed inside Genesys Cloud. Developers can also use tools including Anthropic Claude Code, OpenAI Codex, Cursor and Kiro to create specifications before bringing them into the Genesys environment for testing and governance. Genesys is additionally introducing AI-assisted authoring that can analyze how an Agentic Virtual Agent has been designed and recommend improvements. New testing, reporting and audit capabilities are intended to help teams examine agent behavior before deployment and understand the actions an agent takes once it is running. Taking agentic AI to WhatsApp and digital channels. Genesys also plans to extend Agentic Virtual Agent across digital channels, including WhatsApp. This means the customer-facing interaction may occur through messaging, while MCP and A2A provide connections to the business applications and specialized AI agents working behind the scenes. The combination is important because the value of agentic AI increasingly depends not on how convincingly an AI system can converse, but on whether it can safely complete the task that prompted the conversation. Early deployments show the business case. Genesys cited Brazilian fashion retailer Riachuelo as one example of customer adoption. According to Genesys, Riachuelo replaced its traditional chatbot with Genesys Agentic Virtual Agent and increased customer retention from 30% to 84%. The company also reported a 60-point improvement in customer satisfaction and productivity gains of more than 400% without increasing staff. Zeppelin Rental GmbH is using the technology to allow customers to describe job-site requirements in natural language rather than searching manually through product catalogs. Mike Szilagyi, Senior Vice President and Head of Product at Genesys, said enterprise AI is entering a phase increasingly defined by what it can accomplish for customers. "We're further strengthening Genesys Cloud Agentic Virtual Agent with more context, intelligence and capabilities to act across the enterprise, work with other AI agents and carry increasingly complex customer requests through resolution," he said. The APT-2 model, new development tools and Deepgram integration are available now, according to Genesys. Native voice enhancements, A2A interoperability and AI-assisted authoring are expected to become generally available during the fourth quarter of the company's fiscal year, between November 1, 2026 and January 31, 2027. For enterprises, the larger development is the gradual disappearance of the boundary between a chatbot and a business application. As virtual agents gain access to tools, workflows and other agents, customer-service AI is beginning to move from answering questions toward actually getting work done.

Enhancing AI agent security and efficiency: new tools and updates. September 03, 2026 By QwenAI.fans 8 views JetStream, Genesys, Anthropic, and OpenAI are all introducing significant updates to their AI agent platforms this week, enhancing security, efficiency, and usability. These advancements aim to address critical challenges in the deployment of AI agents, such as security, cost, and operational complexity. JetStream launches Clearance for enhanced security. JetStream debuts Clearance, a reasoning engine that evaluates and authorizes every action an AI agent takes before execution. This new tool blocks potentially dangerous sequences, such as data exfiltration, in real-time, rather than logging them after the fact. For businesses running large fleets of automation or customer-facing agents, Clearance provides a new level of control, reducing the risk of live-data exfiltration and compliance issues. \"If you're piloting agentic workflows, map the highest-risk multi-step actions and test whether a per-action gate would block risky parameter changes,\" advises JetStream. \"Monitor how often legitimate long-running agent jobs are paused to ensure SLAs aren't accidentally broken.\"\ Genesys unveils new products for Genesys Cloud. Genesys introduces four new products for its Genesys Cloud platform: Navigator, Orchestrator, Contextual Intelligence (CI), and an AI Control Plane (AICP). The company also updates its Agentic Virtual Agent (AVA) with a large-action model and new native voice features. These tools enable operators to treat AI agents like a connected workforce, improving context handoffs, policy-aware action sequencing, and oversight. \"Customer service is one of the earliest large-scale use cases for agentic AI,\" says a Genesys spokesperson. \"These pieces let operators treat AI agents like a connected workforce, which speeds safe automation while reducing orphaned-agent and handoff failures.\"\ Anthropic releases Fable 5.1 and Mythos 5.1. Anthropic releases Fable 5.1, an improved general-purpose agent model, and a gated Mythos 5.1 for vetted defenders and researchers. Fable 5.1 offers a 1M-token context window and a 75% reduction in prompt cache-read pricing. These enhancements make long-running agent workflows more practical and cost-effective, particularly for complex code, research, and knowledge work. \"Test Fable 5.1 on a sandboxed long-run workflow and measure cost savings from cache reads,\" recommends Anthropic. \"For sensitive defensive or life-sciences use cases, plan to apply for gated Mythos access and review its distinct safeguards.\"\ OpenAI's Astra undergoes tighter controls. Internal reports at OpenAI reveal that Astra, a powerful AI agent, has been assessed at the company's highest cybersecurity capability threshold. OpenAI plans a tightly controlled rollout with stronger safeguards and restricted access. This move underscores the need for robust security measures in any agent architecture that grants tooling, file access, or long-running execution to frontier models. \"Rework critical agent workflows to be checkpointed, able to resume or gracefully fail,\" advises OpenAI. \"Review how your incident response must handle a model-sourced vulnerability discovery, and track vendor access programs to see which models you can credibly apply to high-risk tasks.\"\ GitHub showcases PR Sous Chef workflow. GitHub publishes a spotlight on a production Copilot workflow called 'PR Sous Chef,' which checks open pull requests every 15 minutes, decides when human attention is needed, and triggers targeted Copilot actions. This workflow reduces noise by performing read-only triage, making it a practical example of how teams can run lightweight, opinionated coding agents. \"This is a concrete example of how teams can run lightweight, opinionated coding agents that reduce noise by performing read-only triage and optimizing developer time,\" says GitHub. References. ", "image_prompt": "A modern, professional illustration of AI agents working securely and efficiently, with elements representing security, cost savings, and seamless integration." }