LabABLE is an AI-native open platform that provides laboratories with a core operational foundation—including sample tracking, audit logging, data parsing, workflow automation, and reporting—and extends into shared tools, AI agents, and collaborative workflows.
Funding
Funding not disclosed
Founders
Product
Problem
Laboratories often rely on fragmented legacy LIMS and manual processes, leading to inefficient sample tracking, poor data traceability, and limited ability to automate workflows. This hampers compliance, slows throughput, and makes it difficult to share protocols or integrate new instruments without costly system overhauls.
Solution
LabABLE offers an AI-native open platform that provides a core operational foundation for labs, including sample registration, audit logging, data parsing, workflow automation, and reporting. The platform can be deployed as a plugin overlay on existing LIMS, allowing labs to retain their current systems while gradually adopting unified data schemas and no‑code automation. Built-in integration connectors enable seamless linking of instruments, ELNs, databases, and external APIs without replacing legacy infrastructure. An extensible open layer lets users publish templates, share workflows, and deploy AI agents that assist with routine tasks, moving laboratories toward more autonomous scientific execution. All actions are versioned and auditable, supporting reproducibility and regulatory compliance.
Target Audience
Primary customers are mid‑size to large research and clinical laboratories seeking to modernize operations, improve data traceability, and enable automation without replacing their existing LIMS.
Features
- Sample tracking with barcode generation, location history, and immutable records
- Comprehensive audit logging for actions, approvals, and workflow events
- Data ingestion and validation for CSV, Excel, and JSON files with QC thresholds and alerts
- Drag‑and‑drop no‑code workflow builder with templating and automated reporting outputs
- Integration layer supporting instruments, ELNs, CRMs, REST endpoints, file drops, and existing LIMS
- Configurable schema translators to unify data structures across heterogeneous lab systems
- Version control for workflows, protocols, dashboards, and outputs to ensure provenance and reproducibility
- Open platform for sharing tools, templates, and AI agents that enhance collaborative and autonomous lab operations