Gemini 3.8 Live Integrations

Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.

Google AI Studio is a unified development platform that helps teams explore, build, and deploy applications using Google’s most advanced AI models, including Gemini 3.5. It brings text, image, audio, and video models together in one interactive playground. With vibe coding, developers can use natural language to quickly turn ideas into working AI applications. The platform reduces friction by generating functional apps that are ready for deployment with minimal setup. Built-in integrations like Google Search enhance real-world use cases. Google AI Studio also centralizes API key management, usage monitoring, and billing. It offers a fast, intuitive path from prompt to production powered by vibe coding workflows.

Gemini is Google’s advanced AI assistant designed to help users think, create, learn, and complete tasks with a new level of intelligence. Powered by Google’s most capable models, including Gemini 3, it enables users to ask complex questions, generate content, analyze information, and explore ideas through natural conversation. Gemini can create images, videos, summaries, study plans, and first drafts while also providing feedback on uploaded files and written work. The platform is grounded in Google Search, allowing it to deliver accurate, up-to-date information and support deep follow-up questions. Gemini connects seamlessly with Google apps like Gmail, Docs, Calendar, Maps, YouTube, and Photos to help users complete tasks without switching tools. Features such as Gemini Live, Deep Research, and Gems enhance brainstorming, research, and personalized workflows. Available through flexible free and paid plans, Gemini supports everyday users, students, and professionals across devices.

Vercel is an AI-powered cloud platform that helps developers build, deploy, and scale high-performance web experiences with speed and security. It provides a unified set of tools, templates, and infrastructure designed to streamline development workflows from idea to global deployment. With support for modern frameworks like Next.js, Svelte, Vite, and Nuxt, teams can ship fast, responsive applications without managing complex backend operations. Vercel’s AI Cloud includes an AI Gateway, SDKs, workflow automation tools, and fluid compute, enabling developers to integrate large language models and advanced AI features effortlessly. The platform emphasizes instant global distribution, enabling deployments to become available worldwide immediately after a git push. Backed by strong security and performance optimizations, Vercel helps companies deliver personalized, reliable digital experiences at massive scale.

LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability.

LiveKit is a real-time platform that enables developers to build video, voice, and data capabilities into their applications. Building on WebRTC, it supports a broad range of frontend and backend platforms. LiveKit's network is optimized for ultra-low latency, extreme resiliency, and massive scale. Our team is distributed across the world, and our infrastructure delivers billions of minutes of audio and video every month. LiveKit provides SDK support across all major platforms, allowing you to code your application with a LiveKit client natively designed for your platform of choice. You can self-host LiveKit for free without changing a line of code, as the entire ecosystem of tools and services is Apache 2.0 open source. LiveKit offers a feature-rich platform, including SSO and RBAC for teams, enterprise-grade security with end-to-end encryption, noise and echo cancellation, session recording, stream ingestion, and moderation tools.

Google Stitch is an AI-powered design tool that enables users to create mobile and web app interfaces from simple text prompts or images. It generates complete UI layouts along with front-end code, making the design process faster and more accessible. The platform allows users to quickly turn ideas into visual designs without requiring advanced design or coding skills. It also supports exporting designs to tools like Figma for further refinement and collaboration. By combining AI-driven generation with rapid prototyping, Stitch helps streamline the transition from concept to development.

Gemini Enterprise app is an advanced AI-powered platform that brings Google’s AI capabilities to every employee, enabling organizations to automate workflows, analyze data, and create high-quality content across multiple business functions. It securely connects to tools like Microsoft 365, Google Workspace, HubSpot, and Jira, allowing users to search and interact with their business data using natural language. The platform supports prebuilt agents such as NotebookLM and Deep Research, helping teams quickly extract insights and streamline tasks. It also allows users to build custom no-code agents to automate multi-step workflows across different applications. With centralized management, organizations can deploy and monitor all agents from a single interface. Built-in security and governance features ensure data privacy and compliance with enterprise standards. Overall, Gemini Enterprise app enhances productivity by combining AI automation with secure data integration.

Pipecat is an open source framework and ecosystem for building real-time voice and multimodal conversational AI agents. It gives developers everything they need to create, deploy, and scale AI applications that can see, hear, and speak, while orchestrating audio, video, AI services, transports, and conversation pipelines with ultra-low latency. The core Pipecat framework is a Python-based system for building voice and multimodal AI pipelines, helping teams connect components such as speech-to-text, LLMs, text-to-speech, vision, video, transports, and business logic without manually wiring every service from scratch. Pipecat is designed to be vendor-neutral and composable, supporting more than 100 AI services so developers can choose the models and providers that fit each use case. Its ecosystem includes Pipecat Subagents for coordinating specialized agents with handoff, task dispatch, and distributed deployment.

Vision Agents is an open source Python framework for building low-latency voice and video AI agents with any model. It lets developers plug in LLM, speech, and vision models from more than 25 providers and ship real-time agents for telehealth, voice support, live coaching, video analysis, interactive avatars, security monitoring, sports commentary, and other multimodal applications. It is designed to help teams build agents that can listen, speak, see, process media, call tools, and respond in real time while running on Stream’s global edge network with sub-500ms latency. Developers can build a first agent in minutes, using a small Python setup with Gemini Realtime, OpenAI, Deepgram, ElevenLabs, Stream, or other supported providers. Vision Agents supports both real-time speech-to-speech models and custom STT/LLM/TTS pipelines, giving teams either the fastest path to a working voice agent or full control over speech recognition, language reasoning, text-to-speech, etc.

The Real-Time Engagement Platform for meaningful human connections. People engage longer when they see, hear, and interact with each other. With Agora, you can embed vivid voice and video in any application, on any device, anywhere. Agora provides the SDKs and building blocks to enable a wide range of real-time engagement possibilities. Our network monitors activity in real time and automatically selects the most efficient routing path for sub-second latency globally across 200+ data centers. Compatible with all popular development platforms and mobile-device friendly with minimal battery consumption. Architected to withstand sudden spikes in traffic, gracefully scaling from one to millions of concurrent users as your business demands. Developers can create unique experiences with our extensive APIs, customizable UI and pre-integrated third-party extensions. Deliver the best quality real-time voice and video to your users with ultra-low latency and intelligent routing.

Fishjam is a real-time media platform for building video conferencing, interactive streaming, AI voice agents, and video compositing products. It works as a modular real-time media infrastructure, allowing teams to use one product or combine multiple products depending on what they need. Its Video Conferencing API lets developers add real-time group calls to an app with a few lines of code while Fishjam handles the WebRTC SFU infrastructure. Teams can create and manage rooms, invite participants, control access with tokens, send and receive audio, video, and screen-share tracks, manage quality on the fly, and use React, React Native, server-side SDKs, REST APIs, and data channels for chat, reactions, polls, or other real-time features. Fishjam’s Live Streaming API delivers live video from browsers, WHIP sources, or MoQ sources to viewers with sub-second latency, using WHEP or MoQ playback for experiences where delay damages the user experience, such as auctions, live events, Q&A, etc.

​The Gemini Live API is a preview feature that enables low-latency, bidirectional voice and video interactions with Gemini. It allows end users to experience natural, human-like voice conversations and provides the ability to interrupt the model's responses using voice commands. The model can process text, audio, and video input, and it can provide text and audio output. New capabilities include two new voices and 30 new languages with configurable output language, configurable image resolutions (66/256 tokens), configurable turn coverage (send all inputs all the time or only when the user is speaking), configurable interruption settings, configurable voice activity detection, new client events for end-of-turn signaling, token counts, a client event for signaling the end of stream, text streaming, configurable session resumption with session data stored on the server for 24 hours, and longer session support with a sliding context window.

Gemini 3.8 Flash is Google’s most intelligent Flash workhorse model, delivering significant improvements over 3.7 Flash across software engineering, agentic tasks, and critical multi-step reasoning in specialized domains. Built for long-horizon coding and autonomous agents, it can solve complex engineering problems end to end and delivers the dependability required for critical enterprise autonomy across specialized knowledge domains. The model shows stronger performance in quantitative and professional fields that require advanced analysis and reporting, as well as multi-step reasoning across STEM, humanities, and professional subjects. Its gains stem from a core design choice: Gemini 3.8 Flash works harder on complex tasks, executing additional reasoning steps and calling tools iteratively to maximize performance. At higher effort levels, it may use more tokens to pursue stronger results, while developers can select lower effort levels.