What we build for biotech
Sample management and tracking
Sample lifecycle, end to end.
From sample receipt through processing, storage, retrieval, and disposal: full lifecycle tracking with chain of custody, audit trails, and storage location management. Barcode and RFID integration. Freezer and storage inventory with location hierarchy down to the rack and box level. Sample state transitions tied to protocols and approvals.
We build sample management as a real system, not as a tab inside a generic LIMS. Researchers find samples. Managers see throughput. Auditors get the trail.
Lab automation and workflow orchestration
Software that runs the routine work.
Protocol orchestration across instruments, robots, and human-in-the-loop steps. Schedule-driven automation that runs overnight runs reliably. Multi-step workflows where data flows from instrument to analysis to storage without human intervention. Error handling, retry logic, and clear escalation paths when something goes wrong.
The automation isn't the goal. The reliability of the automation is. We build lab software that keeps running when the operator goes home.
Instrument and system integrations
Connect the things that don't natively talk to each other.
Real-time data ingestion from lab instruments via direct API, SDK, file watchers, or middleware. LIMS, ELN, MES, ERP, and inventory system integrations. Standards-based interfaces where they exist and custom integrations where they don't.
We've integrated with major lab platforms (Roche Navify for clinical lab operations, Zorgmail for downstream communications) and with proprietary instrument software where the vendor never built a real API. If the instrument produces data, we connect to it.
Regulated environments and GxP compliance
Built for the auditor on day one.
Validated systems with full change control, electronic signatures, audit trails on every record, role-based access at the field level, and reproducible deployments. Documented training records and access reviews built into the platform.
We architect for regulated environments from the first commit. Validation isn't something we tack on at the end. It's the foundation the architecture is built on.
Data pipelines and analysis infrastructure
From instrument output to research insight.
ETL pipelines for raw instrument data. Standardised data models that survive the next instrument upgrade. Analysis pipelines built in Python, R, or your existing toolchain. Reproducible notebooks integrated into the platform. Data lakes and warehouses for cross-experiment analysis.
The data is the asset. We build the pipelines that turn raw output into structured, queryable, scientifically useful data.