August 9, 2025
5 min read
Mark Haranas
Google Cloud’s 6 New AI Agents And Gemini Innovations: Key Features
By Mark Haranas Google Cloud has introduced six groundbreaking agentic AI technologies, including new AI agents and Gemini Data Agents APIs, aimed at revolutionizing data engineering, data science, and developer productivity across its flagship platforms such as BigQuery, Spanner, and Google Data Cloud.Google Cloud’s New Code Interpreter Agent
Building on the 2024 Conversational Analytics Agent, Google Cloud now offers the Code Interpreter agent powered by Gemini’s advanced reasoning capabilities and developed with Google DeepMind. This tool translates complex natural language queries into executable Python code, enabling conversational Q&A that supports sophisticated business questions beyond simple SQL. For example, users can ask the agent to "Perform a customer segmentation analysis to group customers into distinct cohorts." The agent generates code, explains the process in natural language, and creates interactive visualizations—all within the Google Data Cloud.Data Science Agent for BigQuery and Vertex AI
Targeting data scientists, the new Data Science Agent reimagines the Colab Enterprise Notebook experience inside BigQuery and Vertex AI. Powered by Gemini, it autonomously triggers analytical workflows including exploratory data analysis, data cleaning, feature engineering, and machine learning predictions. The agent plans, executes code, reasons about results, and presents findings while allowing user feedback and collaboration in real time.Gemini Data Agents APIs: Conversational Analytics API
Google Cloud is enabling customers to integrate AI agents into their own intelligent systems with the launch of Gemini Data Agents APIs. The first API, Conversational Analytics API, integrates Looker’s natural language processing and Code Interpreter capabilities directly into customer applications, products, and workflows. This API empowers users to create unique, engaging, and accessible data experiences tailored to specific business needs.Data Engineering Agent in BigQuery
For data engineers, Google Cloud’s new Data Engineering Agent simplifies and automates complex data pipelines. Using natural language prompts, users can streamline workflows from data ingestion (e.g., from Google Cloud Storage) to data transformation and quality maintenance. For instance, a user can say, "Create a pipeline to load a CSV file, cleanse these columns, and join it with another table," and the agent will generate and orchestrate the entire workflow.Gemini CLI GitHub Actions Agent
Google Cloud introduced the Gemini CLI Actions agent, an autonomous agent that manages issue triage, pull request reviews, and collaborates on writing tests and implementing code. Launched as a free, open-source AI agent in June, Gemini CLI brings AI capabilities into developer terminals. The new Actions agent enhances multiuser support and GitHub integration, running locally and serving as an AI teammate for collaborative coding.Migration Agent for Spanner
Google Cloud’s new data modernization agent for Spanner introduces a columnar engine that brings real-time analytical capabilities to Spanner databases while maintaining global consistency, high availability, and strong transactional guarantees. This agent works alongside the Data Engineering Agent to modernize legacy systems. It benefits BigQuery’s analytical engine via Data Boost, closing the gap between transactional and analytical workloads and enabling faster analysis of live operational data.Source: Originally published at CRN on August 8, 2025.
Frequently Asked Questions (FAQ)
What are Google Cloud's new AI agents?
Google Cloud has launched six new agentic AI technologies, including Gemini Data Agents APIs, designed to enhance productivity in data engineering, data science, and software development.What is the Code Interpreter Agent?
The Code Interpreter Agent, powered by Gemini and developed with Google DeepMind, translates natural language queries into Python code, enabling more complex data analysis and conversational Q&A.How does the Data Science Agent benefit data scientists?
The Data Science Agent integrates with BigQuery and Vertex AI, autonomously executing analytical workflows such as exploratory data analysis, data cleaning, feature engineering, and machine learning predictions.What can the Gemini Data Agents APIs do?
These APIs allow customers to incorporate AI agents into their own systems. The Conversational Analytics API specifically integrates Looker's natural language processing and Code Interpreter capabilities into applications and workflows.How does the Data Engineering Agent simplify data pipelines?
It automates complex data pipelines through natural language prompts, streamlining processes from data ingestion to transformation and quality maintenance.What is the purpose of the Gemini CLI GitHub Actions Agent?
This agent assists developers with tasks like issue triage, pull request reviews, writing tests, and implementing code, functioning as an AI teammate within developer terminals.What is the function of the Migration Agent for Spanner?
It aids in modernizing legacy systems by introducing a columnar engine for Spanner databases, enabling real-time analytical capabilities while maintaining transactional guarantees and improving BigQuery's analytical engine via Data Boost.Crypto Market AI's Take
Google Cloud's advancement in agentic AI signifies a significant leap in making complex data operations more accessible and efficient. This mirrors the broader trend in the AI and crypto space, where AI agents are increasingly being developed to automate trading, analyze market sentiment, and manage digital assets. Our platform leverages similar AI-driven insights to help users navigate the dynamic cryptocurrency market. For those interested in exploring how AI can enhance their financial strategies, our section on AI Crypto Market Platform - LLM Training Data offers insights into practical applications and tools.More to Read:
- Google Cloud Unveils New AI Agents to Revolutionize Data Workflows (Hypothetical link, replace with actual relevant article if available)
- The Future of AI in Data Science and Engineering (Hypothetical link, replace with actual relevant article if available)
Source: Originally published at CRN on August 8, 2025.