Building agentic AI is relatively easy; scaling it to production and across business units is where the friction starts. Whether it’s debugging a race condition in a workflow or shaving milliseconds off voice latency, the gap between a prototype and a live system is defined by tooling.
That is the focus of this new monthly Product Update series. We are moving beyond standard release notes to give you context on why we shipped these changes and how they impact your long-term value. This month, we prioritized the “Day 2” problems of operations: stabilizing real-time voice, smoothing out complex integrations, and improving the developer experience so you can ship reliable agents faster.
Evolving the AI Agent Builder Experience
As your team’s use of agents matures, the platform needs to match that velocity. We’ve updated the AI Agents interface to better support the engineering lifecycle, moving you from setup to value faster. This update focuses on context and flow:
- Context-Aware Navigation: We’ve simplified the hierarchy to surface configuration options exactly when you need them. This reduces the cognitive load of “hunting” for settings and keeps the focus on the build logic.
- Accelerated Onboarding: For new team members, the improved structure clarifies the relationship between agent definition and deployment, reducing the ramp-up time for new builders.
- Workflow Efficiency: For experienced users, we’ve optimized high-frequency tasks to require fewer steps, removing friction from your daily iterative cycles.
Embedded Usage Analytics
Optimizing an agent shouldn’t require context-switching to a different data tool. We have introduced native usage analytics directly within the agent dashboard. You can now measure value and performance alongside your configuration controls:
- Usage Volume: Visualize exactly how frequently specific agents are being utilized.
- Performance Optimization: Identify usage patterns to spot bottlenecks or successful flows immediately.
- Data-Driven Iteration: Use in-context data to inform your next logic update without exporting logs or leaving the workflow.
Response API & Streaming Support
We have updated the AI Agents API to support the modern Response API pattern. This moves integration architecture beyond simple text-in > text-out loops, enabling the structured data flows necessary for real-time applications.
Why the shift? Standard REST patterns work well for asynchronous chat, but they introduce friction in high-velocity environments like voice or complex orchestration. By adopting a Response-based architecture, we are solving for two specific engineering challenges:
- Structured Outputs vs. Text Blobs: Previously, extracting complex data from an agent often meant parsing a text string or relying on regex. The new compatibility supports structured events, ensuring your external systems receive clean, valid JSON objects. This minimizes the “glue code” required to sanitize agent outputs before passing them to downstream services.
- Streaming for Low Latency: For voice and synchronous chat, waiting for a full completion generates unacceptable latency. The new API supports streaming responses, allowing your application to begin processing (or voicing) the output the moment the first token is generated.
Figure 1: Old: Monolithic Response vs. New: Streaming Response
Source: OneReach.ai
A Native Runtime for Real-Time Voice
Voice requires a completely different approach to latency management, interruption handling, and audio stream orchestration compared to conventional chat. We have introduced a dedicated Real-Time Voice Runtime designed to handle the specific constraints of synchronous audio. This isn’t a wrapper around a chat bot; it is a re-engineered pipeline focused on minimizing the “latency budget” between user input and agent response.
Optimized for Real-Time Voice
This architectural update is specifically designed to support the requirements of conversational voice and IVR:
- Reduced TTFB (Time to First Byte): Streaming significantly cuts the delay between user input and agent voice activity.
- Interruption Handling: The response structure allows for cleaner handling of barge-ins and state changes mid-stream.
Modular Audio Pipeline
We know that the “best” model changes weekly. We’ve architected the voice stack to be agnostic and modular, allowing you to plug in low-latency providers based on your specific use case requirements:
- STT (Speech-to-Text): Deepgram, etc.
- TTS (Text-to-Speech): ElevenLabs, Cartesia, etc.
This allows you to balance cost vs. quality vs. speed without rewriting your integration logic.
Native VAD (Voice Activity Detection)
The hardest part of voice UI is “barge-in” — handling users who interrupt the agent. We have implemented built-in VAD at the platform level. The system now listens for interruption signals on a separate thread, allowing for natural, bi-directional turn-taking without requiring you to build complex logic trees to handle silence or over-talking.
Actionable Voice via MCP
A voice agent that can only talk is limited. We’ve added Model Context Protocol (MCP) support to the voice runtime. This allows your voice agent to securely access tools, trigger database lookups, or execute OneReach.ai workflows during the conversation, turning voice from a passive interface into an active control plane.
Building Stronger Foundations for Scale
This release marks an important step in how we think about agentic AI: not as isolated demos or single-channel experiments, but as operational systems embedded into real business workflows. Across UX, integrations, and voice, the focus is consistent: reducing friction, increasing visibility, and ensuring stability at scale.
Whether you are expanding an existing deployment or scoping a new project, if you are evaluating how these new voice runtimes or streaming APIs fit into your stack, we are happy to skip the slide deck and go straight to the architecture. Reach out to your account team directly to schedule a whiteboard session focused on your integration logic and latency requirements. If you don’t have a representative yet, you can Request a Technical Deep Dive here.
Stay tuned for more updates next month.