Ryght is a generative AI platform designed to support biopharma and life sciences organizations in transforming unstructured scientific and clinical data into actionable knowledge. Built for data scientists, research teams, and decision-makers in pharmaceutical companies, Ryght helps users ingest, structure, and analyze large volumes of documents such as publications, trial results, regulatory filings, and internal research notes.

The platform leverages large language models (LLMs) and domain-specific knowledge graphs to accelerate research and development (R&D) processes, reduce time to insight, and increase confidence in data-driven decisions. Ryght is particularly valuable in early-stage drug discovery, competitive intelligence, and clinical development workflows.

What are the main features of Ryght?

Automated ingestion and structuring of scientific content

Ryght allows users to import and process scientific documents at scale, automatically converting unstructured content into structured, queryable data.

• Supports ingestion of PDFs, spreadsheets, proprietary formats, and web data.

• Extracts relevant biomedical entities such as genes, diseases, drugs, mechanisms, and trial phases.

• Converts scientific text into semantic data representations linked to ontologies.

This helps reduce manual curation efforts and ensures consistent, standardized information extraction across sources.

Generative AI question-answering engine

Using foundation models fine-tuned for the life sciences, Ryght provides conversational access to complex biomedical data.

• Users can ask natural language questions and receive context-aware, evidence-backed answers.

• Results are linked to primary sources with citations and confidence scores.

• Capable of summarizing research trends, comparing compounds, or identifying potential biomarkers.

This accelerates the research process while maintaining scientific rigor and traceability.

Customizable biomedical knowledge graph

Ryght creates and maintains a knowledge graph tailored to each organization’s needs, continuously updated with new information.

• Integrates internal and external data sources into a unified, semantically linked graph.

• Enables advanced search, filtering, and relationship exploration between biomedical concepts.

• Supports enrichment with proprietary taxonomies and domain-specific ontologies.

This structure provides a robust foundation for hypothesis generation and discovery across disciplines.

Collaboration and workflow integration

Ryght fits into biopharma R&D environments by enabling collaborative data analysis and integration with existing workflows.

• Supports multi-user access, project workspaces, and audit trails.

• Connects with data lakes, lab notebooks, and document management systems via APIs.

• Enables export of structured data to downstream tools or BI platforms.

This ensures that research teams can work together efficiently while retaining data provenance and governance.

Enterprise-grade customization and compliance

The platform is designed for biopharma-scale deployments, offering features that support data security, compliance, and customization.

• Configurable language models tailored to specific therapeutic areas.

• Support for deployment in private cloud or on-premises environments.

• Compliance with data standards such as GxP and FAIR principles.

This makes Ryght suitable for enterprise use cases with strict regulatory and operational requirements.

Why choose Ryght?

• Faster access to scientific insight: Accelerates literature review, data exploration, and knowledge synthesis using generative AI.

• Domain-specific precision: Tailored to biomedical language, minimizing hallucinations and improving output relevance.

• Reduced manual data handling: Automates extraction and structuring of complex scientific content at scale.

• Interoperable with existing systems: Integrates seamlessly with pharma data environments and analytical tools.

• Built for regulated industries: Supports compliance and traceability in clinical, research, and regulatory contexts.

Ryght stands out for its ability to combine LLM capabilities with biomedical structure and context, enabling more informed, efficient, and compliant decision-making in the life sciences sector.