Haystack is designed to help developers easily create custom search solutions that leverage the latest advancements in machine learning. With its components like document stores, retrievers, and readers, Haystack can connect to various data sources and effectively process queries. Its modular architecture supports mixed search strategies, including semantic search and traditional keyword-based search, making it a versatile tool for enterprises looking to enhance their search capabilities.

Cognita offers a modular architecture for building RAG applications: ingest and index documents, select from OpenAI, TrueFoundry or third-party embeddings, and configure retrieval pipelines via YAML or Python DSL. Its integrated frontend UI lets you test queries, tune retrieval parameters, and visualize vector similarity. Once validated, Cognita provides deployment templates for Kubernetes and serverless environments, enabling you to scale knowledge-driven AI assistants in production with observability and security.

DocChat-Docling is an AI document chatbot framework that transforms static documents into an interactive knowledge base. By ingesting PDFs, text files, and other formats, it indexes content with vector embeddings and enables natural language Q&A. Users can ask follow-up questions, and the agent retains context for accurate dialogue. Built on Python and leading LLM APIs, it offers scalable document processing, customizable pipelines, and easy integration, empowering teams to self-serve information without manual searches or complex queries.