AI Train2024
Pretrained foundation model for zero-shot point and quantile forecasting on unseen time series, no per-dataset training. Decoder-only, trained on 100B real-world time-points; v2.5 (200M params) handles up to 16k context and 1k-step horizons.
AI API2024
Build AI workflows once and run them across model providers — GoogleAI, OpenAI, Claude, Ollama — through one SDK. Composable primitives for RAG, tool use, and agents, plus a local dev UI for tracing and debugging, with SDKs in JS/TS, Go, and Python.
AI API2024
aisuite is a lightweight Python library that provides a unified API for working with multiple Generative AI providers. It supports models from OpenAI, Anthropic, Google, Hugging Face, AWS, Cohere, Mistral, Ollama, and others—abstracting away SDK differences, authentication details, and parameter variations. Modeled after OpenAI’s API style, it enables developers to build LLM-based or agentic applications across providers with minimal setup.
AI Deploy2024
Runs and optimizes ML and generative-AI models on-device across mobile, desktop, web, and IoT. Successor to TensorFlow Lite, it adds automated GPU/NPU accelerator selection and zero-copy buffer interop to cut latency without cloud round-trips.
AI Dataset2025
Provides professionally translated parallel corpora and a multilingual lexicon across 100+ low-resource languages for training and evaluating multilingual MT and NLP models. Includes SmolDoc, SmolSent, GATITOS, and factuality annotations; licensed CC-BY-4.0.
AI Agent2025
Scaffolds production-ready GenAI agents on Google Cloud from one CLI command, wrapping your agent logic in Terraform, CI/CD, observability, and evaluation. Ships ADK, LangGraph, and multimodal RAG templates for Cloud Run or Vertex AI Agent Engine.
AI Client2025
Runs open-source LLMs and multimodal models entirely on mobile devices for offline, private inference. Offers Agent Skills, Thinking Mode, Ask Image, audio scribe, model management and benchmarks, with Gemma 4 and Hugging Face integration.
AI Agent2025
Builds, evaluates, and deploys multi-agent systems in Python, code-first. A graph-based runtime handles routing, fan-out/fan-in, loops, retries, and human-in-the-loop; a Task API covers agent-to-agent delegation, plus a CLI and web UI.
AI Agent2025
Provides ready-to-use sample agents for Google’s Agent Development Kit across Python, TypeScript, Go, Java, Kotlin, and Android, from simple assistants to multi-agent workflows.
AI Deploy2025
Run large-language and multimodal models locally on edge devices (Android, iOS, desktop, web, Raspberry Pi) with hardware acceleration, function-calling, and multi-language SDKs—designed for low-latency, privacy-sensitive on-device inference.
AI Client2025
Brings Gemini models into the terminal as an agent that reads files, runs shell commands, and edits code in place. Includes Google Search grounding, MCP server support, and a free OAuth tier (60 req/min, 1,000 req/day) with a 1M-token context window.
AI Agent2025
Official reference code for building browser-controlling agents on Google's Gemini computer-use models. The model sees a screenshot, proposes a UI action, and the loop executes its clicks, typing and scrolling via local Playwright or cloud Browserbase.