1. Home
  2. /
  3. Add-Ons
  4. /
  5. CoScientist & SmartSearch

Ai CoScientist & Smart search

Transform the way researchers access and leverage scientific information with an intelligent search solution combining advanced retrieval technologies and an AI CoScientist. The platform uses LLM-based embeddings and Retrieval-Augmented Generation (RAG) to deliver highly relevant, context-aware search results across scientific data sources. Rather than relying solely on keyword matching, it understands the semantic meaning of queries, enabling researchers to discover related experiments, samples, records, documents, and datasets even when exact terms are not used.

AI-Powered Scientific Search & Discovery

While Elasticsearch remains available as part of the technical architecture for indexing and search operations, the core value of the solution is now driven by AI-powered semantic search and RAG capabilities, providing a more intuitive and intelligent way to access knowledge.
The AI CoScientist connects directly to LIMS (LSM) and ELN platforms, allowing researchers to interact with their scientific data using natural language. It can analyze documents and experimental data, answer questions, provide summaries, generate visual insights, and support scientific reasoning by identifying patterns and suggesting potential hypotheses.

Key Capabilities

  • Semantic search powered by LLM embeddings
  • Context-aware retrieval using RAG technology
  • Unified access to data across LIMS, ELN, and scientific repositories
  • Natural language interaction with scientific records and documents
  • AI-assisted analysis of experiments, protocols, and datasets
  • Automated summaries and knowledge extraction
  • Generation of visual insights and data interpretation
  • Identification of trends, correlations, and research opportunities
  • Faster discovery of relevant information across multiple systems

Elasticsearch Integration

While Elasticsearch remains available as part of the technical architecture for indexing and search operations, the core value of the solution is now driven by AI-powered semantic search and RAG capabilities, providing a more intuitive and intelligent way to access knowledge.

  • Elasticsearch can be installed on the same server of LabCollector or on a dedicated server/VM or use an Elasticsearch cloud service (AWS, ElastiCloud…).
  • It takes in unstructured data from different locations, stores and indexes it, according to user-specified mapping (which can also be derived automatically from data) and makes it searchable.
  • Indexes are used to quickly locate data without having to search every row in a database table every time a database table is accessed.
  • LabCollector will handle all needed indexing of data and files to Elasticsearch engine.

Image Gallery