Data Management
Automated life science laboratory

Making life science data AI-ready

AI Starts with Trusted Data

Data Management uses AI to understand laboratory data and structure it. Scientists then confirm the results, ensuring every dataset and report can be traced back to the original evidence.

WHY TRUSTED DATA IS HARD

Laboratories have no shortage of data. What they lack is trustworthy data.

Results are scattered across instrument exports, shared drives, LIMS, ELN and automation systems. Teams spend substantial time locating, cross-checking and re-running experiments, and AI cannot safely use data stripped of context.

01

Data sources are fragmented

Diverse formats and scattered locations make unified discovery and access difficult.

02

Experimental context is lost

Results lack linkage to experiments, samples, methodologies and operational records.

03

Verification costs are high

Manual duplication, cross-checking and data sorting consume high-value scientific time.

04

Data reuse remains low

Data without permissions, version control and lineage cannot reliably support analytics and AI workflows.

TRUSTED DATA WORKFLOW

Four steps from source data to trusted application.

Data Management Agent collects data from connected sources, structures it automatically, and turns it into trusted data through human confirmation—ready for downstream systems, AI models, analytics and reports.

Galatek Ecosystem

Lab InformaticsLab Informatics
OrchestrationLab Automation

External Sources

InstrumentsInstrument Data & Files
Third-Party SystemsLaboratory & Business Systems

Connection methods vary by source: files, APIs or RPA.

Data
ManagementAgent
Trusted Data

Source traceable

Human confirmed

Galatek GeraAI-Assisted Experiment Planning
Third-Party Systems
AI Models
Analytics &Visualization Tools
Reports
01

Data Collection

Collect data from instruments, files, third-party systems, APIs and RPA.

02

Agent Structuring

Data Management Agent automatically interprets and structures unstructured data.

03

Human Confirmation

Scientists confirm each data type once, enabling subsequent confirmations to be completed automatically while maintaining data trustworthiness.

04

Data Application

Apply data to systems, AI models, analytics tools and reports.

HOW DATA MANAGEMENT WORKS

Data Management delivers capabilities for every data scenario, from collection to application.

Data Management provides laboratories with integrated capabilities spanning experimental data collection, structuring, management, analysis and reporting.

01

Lab Terminal

Lab Terminal collects instrument files within the authorized Data Access Scope.

Lab Terminal
02

Data Management Agent

Data Management Agent helps scientists structure data.

Data Management Agent
03

Incoming Data

Review and confirm data before trusted data is formally stored.

Incoming Data
04

Data Library

Use AI to enrich stored data assets with relevant business information.

Data Library
05

Analysis Datasets

Organize trusted data into reusable Analysis Datasets.

Analysis Datasets
06

Reports

Use prepared data with AI for analysis, reporting and third-party applications.

Reports

THE VALUE OF DATA MANAGEMENT

Continuously create high-quality data assets for scientific R&D.

Data Management helps organizations continuously build data assets, improve collaboration, reduce compliance effort and accelerate scientific R&D decisions.

01

BUILD THE AI DATA FOUNDATION

Continuously accumulate enterprise data assets

Turn the data generated by every experiment into reusable enterprise data assets.

02

BREAK DOWN DATA SILOS

Improve data collaboration efficiency

Enable instruments, systems and research teams to collaborate using consistent data.

03

ESTABLISH COMPLIANCE

Reduce compliance and audit effort

Keep experimental data sources, change history and critical actions clear and reviewable, reducing compliance preparation work.

04

DRIVE SCIENTIFIC R&D

Accelerate scientific R&D decisions

Help teams understand experimental results, uncover data connections and advance the next research step faster.

CONNECTED LAB USE CASES

Support laboratory scenarios of varying complexity.

Data Management provides four independently deployable data solutions for different laboratory environments, covering scenarios of varying complexity—from instrument data integration to informatics, automation and AI collaboration.

01

Bring Instrument Data into Systems

Solve the challenge of instrument data being scattered across local files and difficult to connect to laboratory business systems.

02

Enable Data Sharing Across Laboratory Systems

Solve the challenge of disconnected information systems that prevent data from linking and flowing freely.

03

Connect Informatics to Automation Equipment

Solve the data gap between laboratory informatics systems and automation equipment.

04

Unify Informatics, Automation & AI

Solve the challenge of connecting and using data consistently across information systems, automation equipment and AI applications.

PLANS & DEPLOYMENT

Choose the Data Management edition that fits your data environment.

Start free, upgrade your Data Management SaaS capacity with Pro, or deploy on-premises and in your private cloud.

Free

SaaS Basic

Start using Data Management for free.

  • 1 AI Agent
  • 1M credits / month
  • 10 GB storage
PRO

SaaS Pro

Scale with more AI Agents, capacity and storage.

  • 5 AI Agents
  • 10M credits / month
  • 100 GB storage
PRIVATE DEPLOYMENT

On-Premises & Private Cloud

Deploy Data Management on your organization's local infrastructure or private cloud.

  • Bring Your Own Model Integration
  • Third-Party System Integration
  • Instrument & Equipment Integration
  • Custom Parsing for Specialized File Formats