GLUE

Scispot GLUE is an AI-powered lab data integration platform designed to serve as the data backbone for modern life science laboratories. It connects instruments, ELNs, LIMS, LIS, legacy systems, and cloud platforms into a single, unified environment — standardizing data models, automating pipelines, and making scientific data ready for machine learning and large language models. GLUE is trusted by regulated and research teams across biopharma, molecular diagnostics, CROs, pathology labs, biotech startups, and academic institutions.

Built for both GxP and non-GxP workflows, GLUE supports over 200 lab instruments and integrates via API, SFTP, ASTM, HL7, and REST protocols. It eliminates manual data transfers, ensures regulatory compliance, and provides real-time access to harmonized, analysis-ready data — all while maintaining end-to-end data lineage.

Core Capabilities

• Lab interoperability: Connect instruments, ELNs, LIMS, LIS, data lakes, and third-party applications. Monitor status across all connections from a single dashboard and resolve issues quickly.
• Data readiness for analysis: Convert raw instrument files into tidy, consistent tables. Align units, timestamps, methods, and identifiers to ensure data is immediately usable.
• ML and LLM readiness: Store data relationships in a knowledge graph and index text and tables in a vector database, making scientific data fully prepared for AI-driven workflows.
• Insight extraction via Scibot: Use the built-in AI lab assistant, Scibot, to search, summarize, and chart lab data, generate reports, trigger runs, and build dashboards using plain English queries.

Data Integration and Processing

• Pull data from instruments, ELNs, LIMS, LIS, and legacy tools; push to databases, data lakes, and applications via API, SFTP, ASTM, and HL7.
• Agent-based support for air-gapped and offline machines ensures even instruments without internet access can be integrated.
• Automate ETL pipelines from source to destination, running transformations as new data arrives and preserving full data lineage end-to-end.
• Reduce processing time from hours to minutes through automated workflows.
• Stream data in real time to S3, Snowflake, Databricks, or the GLUE Lakehouse.
• Supports structured data formats including CSV, XML, and ALCOA.
• Connects to thousands of third-party applications via Zapier, including Slack notifications and Google Sheets synchronization; custom integrations can be built on request.

Real-World Use Cases

• Instrument ETL to lake and LIMS: Stream data from LCMS, HPLC, or plate readers on Windows PCs to S3 or ELN/LIMS, with automatic file parsing, metadata mapping, and lineage preservation.
• Clinical de-identification and EDC sync: De-identify sensitive clinical datasets, standardize formats, and synchronize with EDC platforms through secure, audit-ready pipelines.
• Bioprocess signal harmonization: Harmonize upstream and downstream signals and convert raw readings into features such as VCD, HETP, and yield for advanced bioprocess analysis.
• Knowledge graph and RAG: Link batch, run, sample, and assay data in a graph structure; use retrieval-augmented generation (RAG) for fast, cited answers drawn from SOPs and records.

Scibot: AI Lab Assistant

• Enables researchers to talk directly to their scientific data using natural language.
• Generates reports, triggers experimental runs, and delivers outputs with context and citations.
• Works in conjunction with existing connections and notebooks to plan steps and call tools automatically.
• Built-in guardrails ensure that AI-driven actions remain safe and controlled.

Compliance and Security

• Compliant with FDA CFR Part 11, SOC 2, HIPAA, and GxP standards.
• Features role-based access controls (RBAC), electronic signatures, comprehensive audit trails, and end-to-end encryption at rest and in transit.
• Hourly backups protect against data loss.
• Automates QC checks, flags deviations from reference values, and sends instant team notifications to reduce compliance risk.
• Maintains a complete chain of custody, linking every data transformation back to the originating experiment.

Developer and Enterprise Features

• API-first architecture supports Python, notebooks, and Postman-based API calls for developer-friendly integration.
• Hundreds of pre-built connections across instruments and applications using proven lab data integration patterns.
• White-glove onboarding includes configuration of templates, connections, and dashboards in collaboration with the customer's team.
• Highly scalable infrastructure suitable for high-throughput experiments, multi-sample testing, and clinical trials.

Scispot GLUE is available as a cloud-based platform with support for regulated production environments and flexible R&D workflows. It is deployed by labs in biopharma, molecular diagnostics, pathology, biobanking, industrial biotech, pharma QC, and clinical QC settings, with offices in Kitchener, Seattle, London, San Francisco, and Montreal.