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Research Agent with Gemini 2.5 Pro and LlamaIndex  |  Gemini API  |  Google AI for Developers

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Type: Web Article Original Link: https://ai.google.dev/gemini-api/docs/llama-index Publication Date: 2025-09-04


Summary
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WHAT - This article discusses how to build research agents using Gemini 2.5 Pro and LlamaIndex, a framework for creating knowledge agents that use large language models (LLM) connected to corporate data.

WHY - It is relevant for AI business because it allows for the automation of research and report generation, improving operational efficiency and the quality of the information collected.

WHO - The main players are Google (with Gemini API) and the developer community using LlamaIndex. Competitors include other AI platforms such as Microsoft and Amazon.

WHERE - It positions itself in the market for AI solutions for automating research and data analysis processes, integrating with the Google AI ecosystem.

WHEN - The content is current and reflects the latest integrations between Gemini and LlamaIndex, indicating a trend of increasing maturity and adoption of these technologies.

BUSINESS IMPACT:

  • Opportunities: Implement automated research agents to improve information collection and analysis, reducing operational time and costs.
  • Risks: Dependence on third-party technologies (Google, LlamaIndex) and the need for continuous updates to maintain competitiveness.
  • Integration: Possible integration with the existing stack of AI tools, leveraging Google APIs and LlamaIndex frameworks.

TECHNICAL SUMMARY:

  • Core technology stack: Python, Google GenAI, LlamaIndex, Gemini API.
  • Scalability: High scalability thanks to the use of cloud-based APIs and modular frameworks.
  • Technical differentiators: Advanced integration with Google Search, state management between agents, and flexibility in defining custom workflows.

NOTE: This article is a practical example of how to use Gemini and LlamaIndex, so it is not a tool or a library in itself, but a practical guide for developers.


Use Cases
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  • Private AI Stack: Integration into proprietary pipelines
  • Client Solutions: Implementation for client projects
  • Development Acceleration: Reduction of project time-to-market
  • Strategic Intelligence: Input for technological roadmap
  • Competitive Analysis: Monitoring AI ecosystem

Resources
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Original Links #


Article recommended and selected by the Human Technology eXcellence team, processed through artificial intelligence (in this case with LLM HTX-EU-Mistral3.1Small) on 2025-09-04 19:40 Original source: https://ai.google.dev/gemini-api/docs/llama-index

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