LiquidText
The infinite workspace for deep document analysis and multi-source synthesis.
Transform fragmented company data into an intelligent, context-aware AI workforce.
Kodi.ai is a sophisticated Retrieval-Augmented Generation (RAG) platform designed to bridge the gap between static enterprise data and conversational intelligence. By 2026, Kodi has evolved into a central nervous system for organizational knowledge, allowing businesses to ingest data from disparate sources such as Notion, Google Drive, and internal PDFs into a unified vector-indexed repository. The technical architecture leverages state-of-the-art LLMs (including GPT-4o and Claude 3.5 variants) while maintaining strict data boundaries to prevent hallucinations. Its market position is defined by its ability to provide 'source-grounded' answers, ensuring every response is backed by a verifiable internal document citation. This makes it an essential tool for high-compliance industries where accuracy is non-negotiable. Kodi's infrastructure handles the complex heavy lifting of embedding generation, chunking strategies, and vector database management, providing a seamless no-code interface for non-technical administrators to deploy production-ready AI agents across web widgets, Slack, and internal portals with sub-second latency.
Every AI response includes clickable links or references to the exact document chunk used for generation.
The infinite workspace for deep document analysis and multi-source synthesis.
Empower your teams to learn, practice, and perform with AI-driven sales enablement and microlearning.
Transform fragmented datasets into navigable, high-fidelity neural knowledge graphs for RAG orchestration.
The minimalist's gateway to focused reading and intelligent content archival.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Real-time syncing with Notion, Google Drive, and URLs via automated crawlers.
Ability to inject form fields into the conversation flow based on user intent triggers.
Uses a second-pass re-ranking algorithm to ensure the most relevant context is prioritized for the LLM prompt.
Technical implementation of session-based memory that persists across multiple turns without inflating token costs.
Full CSS/JS control over the widget interface with no 'Powered by' badges.
The system can route simple queries to smaller models (GPT-4o mini) and complex ones to larger models to optimize performance.
Support teams are overwhelmed by repetitive FAQs regarding product specs.
Registry Updated:2/7/2026
New hires spend hours searching for benefits information and company policies.
Developers struggle to find specific API endpoints in massive documentation sets.