Scispot LabOS
The Operating System for the Lab of the Future, unifying ELN, LIMS, and data lake with AI-driven insights.
Executive Summary
Scispot LabOS unifies ELN, LIMS, and data lake functionalities, enabling fast, auditable, and automated lab operations. It is designed for R&D and clinical labs, connecting instruments, people, and data to provide clear visibility, guided workflows, and compliance automation. The platform's key value lies in streamlining lab processes, enhancing data integrity, and preparing data for AI/ML applications.
Use Cases
- Streamlining sample tracking and management from registration to reporting.
- Automating lab workflows for high-throughput screening and experimental execution.
- Ensuring compliance with regulatory standards like 21 CFR Part 11, GxP, and HIPAA.
- Centralizing and harmonizing scientific data from various instruments and sources.
- Enabling collaborative R&D with version-controlled protocols and experiments.
- Preparing R&D data for machine learning and AI model training.
Features
Visibility
- Real-time Dashboards: Provides instant overviews of inventory, equipment, activity logs, and experiment progress, with alerts for low stock or maintenance.
- Customizable Analytics: Allows users to create custom dashboards, graphs, and visualizations, and run SQL/non-SQL queries for in-depth data analysis.
- Full Sample Traceability: Automates end-to-end sample tracking, logging every sample, monitoring its journey, and ensuring instant retrievability with a clear audit trail.
- Workflow Diagrams: Visualizes experimental workflows, making it easy to track progress steps and understand the flow of work.
Intelligence
- AI Lab Assistant/Copilot: A built-in AI copilot helps users find information, query data in plain language, and trace sample lineage across the platform.
- AI-Powered Workflow Automation: Automates sample-centric workflows, including generating pick lists for liquid handlers and mapping data from instruments using AI.
- AI-Guided CSV Mapping: Reduces manual effort in data migration by using AI to guide CSV mapping and import with checks, ensuring clean data lineage.
- Automated Quality Checks: Sets up AI-powered quality checks for data integrity, reducing errors and ensuring reliable results.
Support
- API Documentation: Provides comprehensive API documentation for integrating third-party applications and instruments.
- Interactive Vendor Evaluation Tools: Offers tools like alt-LIMS, alt-ELN, and GLP Vendor Evaluation Tools to help labs assess their needs and Scispot's fit.
- Dedicated Team Support: A team is available to help with questions and provide assistance.
Technical Specifications
- Architecture
- Cloud-native SaaS, auto-scaling, multi-tenant with strict tenant isolation (dedicated database schema) across global cloud regions.
- Deployment
- Cloud/SaaS
- Authentication
- SSO, MFA, Role-Based Access Control (RBAC)
- API Available
- Yes
- MCP Server
- No
Infrastructure
- AWS
AI/ML Stack
- Generative AI
- Machine Learning
- NLP
- Python
Integrations
- Laboratory Equipment
- Automation Systems
- Zapier
Security & Compliance
Certifications: GDPR, HIPAA, 21 CFR Part 11, GxP, CLIA, CAP, ISO 15189
Encryption: AES-256 at rest, TLS 1.2+ in transit (implied by 'encrypted in transit and at rest')
Pricing
- Model
- Per user/month, with volume benefits and modular additions for integrations/instruments.
- Starting Price
- Contact sales (paid pilot available)
- Target Customer
- Startup, Scaleup, Enterprise Biotech, Molecular Diagnostics, Contract Testing labs
- Contract Type
- Annual (implied by pilot structure and enterprise focus)
- Free Trial
- Yes, Paid pilot with fixed scope and clear deliverables (duration not specified, but typically 1-3 months) (credit card required)
About Scispot
Scispot is a cloud platform that serves as the operating system for self-driving labs, unifying ELN, LIMS, and data lake with AI-driven insights. It connects experiments, instruments, data, and analysis into one intelligent system to streamline processes, improve data integrity, and enhance collaboration in biotech R&D.