Curated for content, computing, data, information, and digital experience professionals

Day: June 16, 2025

Deepgram launches Voice Agent API

Deepgram, a voice AI platform for enterprise use cases, announced the general availability of its Voice Agent API, a single, unified voice-to-voice interface that gives developers full control to build context-aware voice agents that power natural, responsive conversations. Combining speech-to-text, text-to-speech, and large language model (LLM) orchestration with contextualized conversational logic into a unified architecture, the Voice Agent API gives developers the choice of using Deepgram’s fully integrated stack (leveraging Nova-3 STT and Aura-2 TTS models) or bringing their own LLM and TTS models. It delivers simplicity for developers and the controllability enterprises need to deploy voice agents.

Deepgram’s Voice Agent API provides a single, unified API that integrates speech-to-text, LLM reasoning, and text-to-speech with built-in support for real-time conversational dynamics. Capabilities such as barge-in handling and turn-taking prediction are model-driven and managed natively within the platform.

While the Voice Agent API streamlines development, it also gives teams control over performance, behavior, and scalability in production. Built on Deepgram’s Enterprise Runtime and model ownership across the voice AI stack, the platform enables model-level optimization at every layer of the interaction loop for precise tuning of latency, barge-in handling, turn-taking, and domain-specific behavior in ways not possible with disconnected components.

https://deepgram.com/learn/voice-agent-api-generally-available

Adobe announces LLM Optimizer

Adobe announced Adobe LLM Optimizer, an enterprise application that enables businesses to gain new relevance where consumers are embracing generative AI-powered interfaces to engage brands. With Adobe LLM Optimizer, teams can stay ahead of shifting consumer behaviors and remain top-of-mind in the AI era. A suite of features will enable businesses to monitor AI-driven traffic and benchmark brand visibility, while receiving recommendations that can be quickly deployed on their digital properties to improve discoverability, engagement and conversion.

LLM Optimizer will be able to identify owned content (details on a website for instance) that is being leveraged by AI-powered interfaces to deliver responses to user queries. This provides teams with a real-time pulse on how their brand is showing up across browsers and chat services.

A recommendation engine detects gaps in brand visibility and suggests improvements across both owned (web pages, FAQs) and external (Wikipedia, public forums) channels — based on attributes prioritized by LLMs including high-quality, informative content from authoritative sources.

LLM Optimizer is built to support existing workflows across SEO leads, content strategists, digital marketers and web publishers, and supports enterprise-ready frameworks such as Agent-to-Agent (A2A) and Model Context Protocol (MCP), to integrate LLM Optimizer with third-party solutions and partners.

https://news.adobe.com/news/2025/06/adobe-llm-optimizer-empowers-businesses-drive-brand-visibility

© 2025 The Gilbane Advisor

Theme by Anders NorenUp ↑