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Tech Radar

The Tech Radar workflow automates the management and intelligent querying of enterprise technology radar data by integrating various technologies. It transforms data from Google Sheets into structured text and stores it in vector and relational databases, supporting multidimensional queries. Equipped with an intelligent AI agent, it can accurately respond to user inquiries, enhancing information retrieval efficiency. Additionally, scheduled synchronization updates ensure data timeliness, lowering the information access barrier for non-technical personnel and facilitating technology decision-making and internal communication.

Workflow Diagram
Tech Radar Workflow diagram

Workflow Name

Tech Radar

Key Features and Highlights

The Tech Radar workflow is designed to automate the management of technology radar data and enable intelligent Q&A capabilities. Its key highlights include:

  • Automatically converting technology radar data from Google Sheets into structured text and generating Google Docs documents for easy downstream processing.
  • Employing dual storage solutions with a vector database (Pinecone) and a relational database (MySQL) to support multi-dimensional querying of technical data.
  • Equipped with intelligent AI agents that automatically determine the type of user query and invoke either a vector search-based RAG agent or an SQL query-based database agent to provide precise answers to technology-related questions.
  • Supporting scheduled synchronization and updates to ensure data timeliness and accuracy.
  • Offering a chat Q&A API via Webhook interface for seamless integration into frontend applications.

Core Problems Addressed

  • Resolves the fragmentation and inconsistent formatting of enterprise technology radar data by achieving data structuring and multi-channel storage.
  • Addresses difficulties in querying technology radar data and low information retrieval efficiency by implementing AI-driven intelligent routing for accurate Q&A.
  • Lowers the barrier for non-technical personnel to access technology decision information, enhancing internal communication efficiency.
  • Automates the synchronization and updating of technology radar data, eliminating repetitive manual maintenance tasks.

Application Scenarios

  • Dynamic monitoring and analysis of internal technology stacks, platforms, and tools by enterprise technology management departments.
  • Quick lookup of technology adoption status, strategic directions, and related descriptions by technical team members.
  • Decision support for enterprise executives formulating technology strategies based on the latest data.
  • Internal knowledge base Q&A systems to assist employees in understanding the company’s technology roadmap.
  • Integration of technology radar query functionality into third-party systems via API.

Main Process Steps

  1. Read technology radar data from Google Sheets.
  2. Convert spreadsheet data into paragraph text via code nodes and update Google Docs documents.
  3. Monitor document updates in a specified Google Drive folder and download the latest documents.
  4. Load document content using LangChain and perform recursive character splitting.
  5. Generate Google Gemini text embeddings and store them in the Pinecone vector database.
  6. Periodically synchronize Google Sheets data to the MySQL database.
  7. Receive user queries via Webhook and use LLM to decide whether to invoke the RAG agent or SQL agent.
  8. The respective agent performs retrieval from the data source and generates answers.
  9. AI output guardrails ensure the response is accurate and compliant with policy requirements.
  10. Return the final answer to the calling client.

Involved Systems and Services

  • Google Sheets (technology radar data source)
  • Google Docs (document formatting and storage)
  • Google Drive (document update monitoring and downloading)
  • MySQL (structured database storage)
  • Pinecone (vector database for embeddings storage)
  • LangChain (text loading, splitting, and embedding processing)
  • Google Gemini (PaLM) API (text embeddings and language modeling)
  • Groq AI (backup or auxiliary language model)
  • n8n Webhook (external API interface)
  • AI Agents (RAG agent and SQL agent for intelligent Q&A)

Target Users and Value Proposition

  • Enterprise technology managers: achieve efficient management and intelligent analysis of technology radar data.
  • Technology decision-makers: quickly obtain technology status and strategic direction information through intelligent Q&A to support informed decision-making.
  • Internal employees: reduce the difficulty of understanding technology radar data and improve technology sharing efficiency.
  • Automation and data engineers: leverage workflow automation to reduce maintenance workload and enhance data consistency.
  • Product and project managers: gain real-time insights into technology trends to optimize product roadmap planning.

Summary:
The Tech Radar workflow integrates Google Workspace, structured databases, and advanced AI technologies to automate the collection, intelligent storage, and multi-dimensional intelligent Q&A of technology radar data. It significantly enhances enterprise technology management efficiency and decision quality, serving as a vital assistant for modern enterprise technology strategy management.