Google Research details an agentic RAG framework in Gemini Enterprise Agent Platform. A Sufficient Context Agent re-searches until multi-hop, multi-source queries have enough grounding to answer. The framework raises factuality accuracy up to 34% versus standard RAG.
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We look at Gemini-SQL2, the text-to-SQL capability Google Research announced on June 12, 2026. Powered by Gemini 3.1 Pro, it posted 80.04% execution accuracy on the BIRD single-model leaderboard. We explain what the score measures, how the leaderboard stacks up, and what Google has not yet disclosed. We also cover use cases and a schema-grounded implementation pattern.
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Antigravity 2.0, launched at Google IO on Tuesday, is the second iteration of Google’s agent-first development platform, and comes with a new desktop app, Antigravity CLI, expanded SDK capabilities, and deeper integration with the Gemini Enterprise Agent Platform. But along with its announcement came the news that Google is beginning to consolidate its existing tools under the Antigravity umbrella.
“Listening to your feedback made one thing clear: we can serve you best by pouring our energy into a single product built for today’s multi-agent reality,” the company wrote in a blog post. To do so, it said, “we’re unifying our efforts into Google Antigravity, our premier agent-first development platform, which includes a powerful server-side harness and a brand-new terminal experience: Antigravity CLI.”
Cleanup of overlapping tools could simplify procurement
While that transition doesn’t mean that Google is immediately shutting down Gemini CLI or Gemini Code Assist for paying enterprise c
turbovec brings Google Research's TurboQuant algorithm to vector search, offering 16x compression and zero codebook training for RAG pipelines.
The post Meet Turbovec: A Rust Vector Index with Python Bindings, and Built on Google’s TurboQuant Algorithm appeared first on MarkTechPost.
Google has launched Gemini 3.5 Flash, a new AI model designed to support agentic workflows across its products and enterprise platforms, as the company looks to move generative AI beyond chatbot-style interactions and deeper into business operations.
The model, announced at the annual Google I/O developer conference, is available through the Gemini app, AI Mode in Google Search, Google Antigravity, the Gemini API in Google AI Studio and Android Studio, Gemini Enterprise Agent Platform, and Gemini Enterprise.
In a blog post, Google said Gemini 3.5 Flash is built for tasks including software development, financial document preparation, customer onboarding, OCR, tax workflows, and data diagnostics.
Google also sought to position the model as a faster alternative to larger flagship systems. It described Gemini 3.5 Flash as its strongest model yet for agentic and coding tasks, claiming it outperforms Gemini 3.1 Pro on benchmarks including Terminal-Bench 2.1, GDPval-AA, and MCP Atlas.
The co
Two weeks ago at Google Cloud Next ’26 in Las Vegas, Google did something the enterprise AI industry has been dancing around for the better part of two years: it made agentic AI governance a native product feature, not an afterthought. The centrepiece announcement was the Gemini Enterprise Agent Platform, pitched as the successor to Vertex AI […]
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