Gemini in Looker deep dive

Announced at Next 25, the Looker Conversational Analytics API serves as the agentic backend for Looker AI. It answers questions using a reasoning agent that uses multiple tools to answer analytical questions. It also uses conversation history to answer multi-turn questions and enable more efficient Looker queries, including the ability to open them in the Explore UI.

Looker’s AI architecture is designed for accuracy and quality, taking a multi-pronged approach to gen AI quality:

1. Agentic reasoning

2. A semantic layer foundation

3. A dynamic knowledge graph that provides context for Retrieval Augmented Generation (RAG)

4. Fine-tuned models for SQL and Python generation

This robust architecture enables Looker to move beyond simply answering “What?” questions to addressing more complex queries like “How does this compare?” “Why?” “What will happen?” and ultimately, “What should we do?”

Looker’s AI and BI roadmap

With Looker, we’re committed to converging AI and BI, and are working on a number of new offerings including:

• Code Interpreter for Conversational Analytics makes advanced analytics easy, enabling business users to perform complex tasks like forecasting and anomaly detection using natural language, without needing in-depth Python expertise. You can learn more about this new capability and sign up here for the Preview.

• The Conversational Analytics API lets developers integrate Conversational Analytics across multiple experiences, including customer applications, chat apps, Agentspace, and BigQuery. Sign up here for preview access to the Conversational Analytics API.

• Centralize and share your Looker agents with Agentspace, which offers centralized access, faster deployment, enhanced team collaboration, and secure governance.

• Automated semantic model generation with Gemini helps democratize LookML creation, boost developer productivity, and unlock data insights with multi-modal inputs. Gemini leverages diverse input types like natural language descriptions, SQL queries, and database schemas.

Embracing BI’s AI-powered future

Gemini in Looker is a significant milestone in the AI/BI revolution. By integrating the power of Google’s Gemini models with Looker’s robust data modeling and analytics capabilities, organizations can empower their analysts, enhance the productivity of their business users, and unlock deeper, more actionable insights from their data. Gemini in Looker is transforming how we understand and leverage data to make smarter, more informed decisions. The journey from asking “What?” to confidently determining “What next?” is now within reach, powered by Gemini in Looker. Learn more at https://cloud.google.com/looker, or click here to learn more about Gemini in Looker and how to enable it for your Looker deployment. You can also choose to enable Trusted Tester features to gain access to early features in development.