Skip to main content

🏗️ CompanyDNA Architecture Overview

CompanyDNA is designed as a comprehensive system that securely integrates, preprocesses, stores, and transforms raw business data into real-time AI-powered insights and recommendations.

🔌 Integration Layer​

  • Connects with over 100 third-party applications including QuickBooks, Stripe, ZohoBooks, Slack, Jira, GitHub, Notion, and more.
  • Uses OAuth-based secure authorization with precise data scopes for each app to ensure safe and uninterrupted data retrieval.

🔄 Data Preprocessing & Structuring​

  • Raw data is processed through automated cleaning, normalization, and enrichment pipelines.
  • The structured data is transformed into vector indexes optimized for LLMs (Large Language Models). This includes format transformation (e.g., JSON, CSV, documents) and efficient indexing.
  • To support vector-based search and RAG (Retrieval-Augmented Generation) processes, dedicated worker nodes and queue systems like Amazon SQS are used to build indexes quickly and reliably.

💾 Storage & Security Layer​

  • All processed data is securely stored in the organization’s own cloud infrastructure (e.g., AWS S3, with future support for Google Drive, Dropbox, etc.).
  • Data is encrypted in transit and at rest, leveraging technologies like AWS KMS.
  • Data processing is distributed across physically isolated worker servers, enabling parallel execution and high availability.

🧠 AI & Machine Learning Layer​

  • CompanyDNA powers intelligent agents such as “The Chief” and department-specific AI Manager Avatars to deliver real-time analysis, strategic suggestions, and auto-generated reports.
  • Pre-trained LLMs are fine-tuned with company-specific data, allowing domain- or team-level personalization and context-aware decision support.
  • Thanks to advanced RAG capabilities, CompanyDNA’s AI models merge internal company knowledge with external sources to produce more relevant and comprehensive answers.

⚙️ Operational & Management Layer​

  • The platform is built for scalability, supported by CI/CD pipelines for continuous deployment and seamless new app integrations.
  • A token-based pricing system calculates usage based on AI model computations, offering a flexible, scalable billing structure.
  • Real-time analytics and data flow are handled via Node.js & Python-based APIs, supported by WebSockets and asynchronous task processing patterns.

✅ Summary​

The architecture of CompanyDNA enables it to:

  • Integrate with various data sources
  • Preprocess and structure raw inputs
  • Store them securely
  • Extract actionable AI-driven insights

All of this happens in a highly modular and scalable environment — making CompanyDNA a powerful operating layer for modern, data-driven organizations.