LDAS converts proprietary data formats from instruments, ELNs, and LIMS into standardized, AI-ready datasets using prebuilt parser library.

Each dataset is enriched with metadata from file attributes, sample tracking systems, or templates—ensuring completeness, traceability, and compliance readiness.

LDAS transforms raw data into structured, contextualized datasets, enabling faster insights through pattern recognition, assay optimizations and predictive analysis.

Captures antibody panels, gating strategies, operator info, and sample context as metadata to ensure traceable, reproducible datasets.

Integrates outputs from leading cytometry platforms into standardized, vendor-neutral FAIR formats for consistent analysis.

Streamline cytometer health checks and gating workflows with automated QC pipelines, by flagging only anomalies for manual review.

Structure large cytometry datasets into searchable data lakes, enabling machine learning models to drive faster, more reliable research conclusions.

Connects CDS systems to ELN/LIMS, automating real-time data capture and metadata linking to ensure accuracy and full traceability.

Each dataset is enriched with metadata like method versions, injection parameters, and operator details, extracted automatically from file attributes.

Real-time monitoring and data transfer ensure immediate availability of analytical results, reducing validation time and speeding interpretation.

LDAS converts fragmented CDS outputs into structured, machine-readable formats enriched with metadata—enabling AI/ML analysis.

LDAS automates sequencing pipelines, triggers alert, prevents manual errors, and ensures accurate, reproducible results

Scalable, version-controlled archival ensures secure backup, efficient retrieval, and long-term storage of large sequencing datasets.

LDAS integrates NGS pipelines with analysis tools and ELN/LIMS systems, enabling real-time monitoring, anomaly detection, and faster, more reliable results.

Results are transformed into structured, metadata-rich formats—FAIR-compliant and optimized for AI/ML-driven insights.

Enables standardized and contextualized capture of CDS data into ELNs/LIMS, ensuring harmonized, structured data that support advanced analytics and AI-readiness.

Enables fast, iterative method development by capturing CDS data in real time, allowing scientists to assess results and adjust methods without delays or data loss.

Centralized chromatographic data improves collaboration, reduces rework, and streamlines tech transfer across development sites

Ensures AI-ready, traceable chromatography data with e-signatures, login tracking, and ALCOA+ compliance for regulatory and IP needs.

Maintains consistent experimental lineage with metadata-rich records and version control across methods and conditions.

Standardizes data from LC/MS, GC/MS, NMR, and spectroscopy into FAIR formats for seamless data sharing across R&D teams.

Capture time-stamped, version-controlled data with electronic signatures to meet regulatory expectations and ensure traceability.

Creates structured, searchable data lakes that support ML models for trend detection, method optimization, and molecule progression.

Automates the entire PCR assay lifecycle — from request and result capture to integration with analytical/processing software and ELN/LIMS — eliminating manual errors and enabling high-throughput, scalable data processing.

Enriches datasets with structured metadata, that ensures traceability, reproducibility, integrity, and consistent assay comparisons across proprietary experimental designs.

LDAS enforces ALCOA+ and 21 CFR Part 11 standards with audit trails and e-signatures, ensuring inspection-ready datasets and IP protection.

Transforms raw PCR data into standardized, metadata-rich formats, enabling AI-driven insights for trend detection and predictive assay refinement.

Automates data capture from bioreactors and at-line instruments using connectors and file watchers, eliminating manual handling and streamlining lab workflows.

Standardizes raw data using ontologies like Allotrope and AnIML, enriching it with metadata for contextual insights.

Auto-aligns sample and run data with enriched metadata and link them to experiments and assays in ELN/LIMS.

Structures bioprocess data into AI-ready formats, flags anomalies, and enables faster, exception-based decisions for scale-up optimization.

Connects directly to bioreactors and associated inline, at-line, and offline instruments, capturing real-time data and mapping it to sample IDs and assay results

Standardized metadata enables comparisons across bioreactors and runs, supporting robust reproducibility and process refinement.

Ensures ALCOA+ and 21 CFR Part 11 compliance, enabling audit-ready, traceable data for regulatory and IP filings.

Transforms raw bioreactor data into structured, metadata-rich formats for AI/ML-driven insights—accelerating decisions and future-proofing scale-up.

LDAS integrates CDMO data from instruments, ELNs, and LIMS into a standardized, vendor-neutral format using pre-built parser library, eliminating silos and manual rework.

Datasets retain lineage with metadata, aligning FAIR and ALCOA+ standards for traceability and scientific defensibility.

LDAS enforces 21 CFR Part 11 and ALCOA+ with secure, error-free data capture and immutable audit trails, reducing compliance risks.

Structured, AI-ready data enables predictive analysis and method optimization.

LDAS captures instrument data in real time via protocols like serial and OPC, enriches it with metadata, and ensures contemporaneous, complete, and compliant records—ready for AI-driven insights.

Automated anomaly detection enables review-by-exception workflows, reducing manual errors and allowing QA/QC teams to focus on critical deviations.

LDAS logs user actions, timestamps, and system events, ensuring transparent, inspection-ready traceability aligned with ALCOA+ and 21 CFR Part 11.

Establishes a centralized data backbone, enabling real-time visibility, anomaly detection, and proactive compliance management.

Captures instrument raw data with e-signatures and audit trails, ensuring ALCOA+ and 21 CFR Part 11 compliance.

Eliminates manual errors and broken traceability for complete, compliant records.

Bridges legacy and modern instruments via RS232, OPC, and proprietary protocols, enabling SOP-aligned, AI-ready workflows.

Enables SOP-aligned, AI-ready workflows with full traceability and secure data retention.

LDAS breaks down data silos, enabling real-time access to chromatographic data, reducing manual effort, and supporting faster, compliant batch release.

Secure, automated data transfer from CDS to ELN/LIMS ensures AI-compatible formats, eliminating transcription errors and speeding decision-making.

LDAS detects anomalies and out-of-spec values in real time, enabling QA teams to focus on critical exceptions.

Time-stamped records, version-controlled chromatograms, and e-signatures ensure ALCOA+ compliance and enable AI-driven audit readiness.

LDAS ingests raw data from varied instruments via serial, OPC, and proprietary protocols, converting it into standardized, metadata-rich data sets.

Time-stamped, version-controlled entries with e-signatures ensure ALCOA+ and 21 CFR Part 11 compliance across workflows.

Automated anomaly detection enables review-by-exception workflows, reducing manual errors and allowing QA/QC teams to focus on critical deviations.

Establishes a centralized data backbone, enabling real-time visibility into assay results and trends.

LDAS ingests batch, QC, and stability data in any format, converting it into structured, vendor-neutral datasets enriched with traceable metadata for regulatory submissions.

Electronic signatures and audit trails, ensure ALCOA+ and 21 CFR Part 11 compliance for inspection-ready records.

LDAS flags anomalies and OOS values in real time, enabling faster, exception-based quality decisions.

Contextualized datasets empower AI to detect trends, predict deviations, and support real-time batch release strategies.