Ryght is an AI platform for life sciences organizations — including pharmaceutical, biotech, and medical device companies — that enables researchers and commercial teams to query complex biomedical datasets, clinical documents, and scientific literature using natural language. Rather than requiring researchers to use specialized query languages or navigate complex data systems, Ryght allows users to ask questions in plain language and receive synthesized, grounded answers from the relevant data. The platform targets mid-market and enterprise life sciences organizations and supports on-premise deployment for companies with proprietary data they cannot send to a third-party cloud. It differentiates through its focus on the life sciences domain — handling the data types, terminology, and regulatory context relevant to pharma and biotech — rather than positioning as a generic enterprise AI search tool.
Ryght
Natural language AI for biomedical data and life sciences research.
Compliance
SOC 2
Key Features
- Natural language biomedical data querying: Allows researchers to ask questions of complex clinical and scientific datasets in plain language, without needing to write SQL, use BI tools, or engage data engineering teams for every query.
- Multi-document synthesis: Processes and synthesizes information across large corpora of scientific literature, clinical trial documents, regulatory filings, and internal research data to answer multi-part research questions.
- Life sciences domain specialization: Built for the specific document types, data structures, and terminology of pharmaceutical and biotech work — including clinical trial protocols, regulatory submissions, and biomedical literature.
- On-premise deployment: Supports on-premise deployment for organizations that need to query proprietary compound data, clinical trial results, or other sensitive research assets without exposing them to a cloud environment.
- Multi-model architecture: Uses multiple underlying LLM providers, allowing the platform to apply different models for different query types within the life sciences workflow.
Use Cases
- For pharmaceutical research teams querying clinical trial data: A clinical development team at a pharma company uses Ryght to query structured and unstructured data from their clinical trial program, getting rapid answers to analytical questions without waiting for data engineering support.
- For life sciences commercial teams accessing market and medical data: A medical affairs or market access team uses Ryght to search and synthesize internal reports, published literature, and real-world evidence relevant to their product’s therapeutic area, accelerating the research that supports commercial decisions.
Pricing MODELS
Enterprise
Pricing Summary
Ryght uses a custom enterprise pricing model. No self-serve tiers or publicly listed prices are available — organizations contact the company directly for pricing.
Company Size Fit
Enterprise Mid-market
Technical Snapshot
API Available
Yes
LLM Provider
Multi-model
Open Source
No
Deployment Options
Cloud Saas, On-premise
Notable Customers
Undisclosed