FlaskTrack Laboratory Operations & Data Platform

Core execution layer · protocols · workflows · batches · samples

Turn methods into work your team can actually run

Build versioned protocols with custom data collection forms, then arrange them into scheduled workflows. Every completed step connects the operator, sample, material lot, observation, and result.

This is the execution backbone of FlaskTrack: the place where people, materials, instruments, data, approvals, and scientific context come together while the work is happening.

See FlaskTrack in action Biological Catalogs ← Back

FlaskTrack in practice

From method to evidence

A technician opens the next scheduled step, records its required measurements and files, and completes it against a specific protocol version. The sample and batch retain that history for review.

The FlaskTrack operating model

A platform, not a collection of tabs

The same records move through design, preparation, execution, instrument capture, analysis, and review. That continuity is the product: fewer handoffs, less duplicated context, and a usable scientific history from the bench to the data layer.

DesignSequences, primers, assemblies, catalogs, and approved scientific entities. ExecuteVersioned protocols, workflows, schedules, batches, samples, and operator actions. SupplyInventory, lots, locations, reservations, consumption, suppliers, and procurement context. CaptureInstrument connectors, agents, result files, position mapping, review, and provenance. ComputeData Studio, SQL, reports, Python/R pipelines, APIs, exports, and analytical storage. GovernRoles, approvals, electronic signatures, audit history, validation support, and controlled records.

Turn protocols into operational execution

FlaskTrack helps labs move beyond static procedures and spreadsheet trackers. Protocols become scheduled step runs, workflow history, sample events, batch records, compliance context, and reviewable operational evidence.

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Structured Protocols Define steps, timing windows, rest periods, required data capture, materials, tools, environmental notes, and expected outcomes.

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Composable Workflows Combine protocols into ordered workflows that reflect real biological processes across multiple execution stages.

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Batches & Samples Track batch-level execution, individual sample state, lineage, outcomes, notes, files, and operational events.

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Scheduled Step Runs Monitor upcoming, due, overdue, blocked, completed, and failed work across batch and sample execution.

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Files, Notes & Measurements Link execution records to files, structured data, observations, measurements, materials, tools, and decisions.

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Audit-Ready History Preserve who performed work, when it happened, what changed, and which records were affected.

Designed for hands-on lab execution

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Structured Step Completion Require data forms, notes, measurements, files, and event details when critical workflow steps are completed.

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Operational State Tracking Follow samples and batches through active, completed, failed, contaminated, archived, and custom operational states.

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Execution Timing Awareness Use scheduled offsets, timing windows, rest periods, due work, overdue work, and alert windows to coordinate execution.

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QR-Ready Bench Workflows Use QR codes to open records, identify samples, and advance workflow steps from logged-in bench devices.

Connected to the rest of your operation

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Catalog-Linked Execution Connect workflows to species, strains, plasmids, ingredients, tools, suppliers, concentrations, units, and files.

Execution-Connected Inventory Check material readiness and record consumption against the batch, sample, and step where materials were used.

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Compliance Context Derive compliance context from the materials, entities, protocols, samples, and actions involved in execution.

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Reports & Exports Feed dashboards, SQL exploration, CSV exports, compliance packets, data lake records, and external analysis.

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Audit Integrity Preserve user and API actions with tamper-evident, hash-linked operational audit history.

AI-assisted workflow import

FlaskTrack can help reduce manual data entry by extracting useful workflow structure and components from uploaded research papers, methods, SOPs, and technical documents. Generated records remain reviewable drafts for scientific validation.

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Research Paper Import Upload external papers and methods so AI can identify protocols, steps, materials, timing, and execution structure.

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Draft Protocol Generation Generate draft workflows, protocols, protocol steps, ingredients, tools, concentrations, units, and metadata.

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Human Review Required Keep AI assistance transparent by reviewing, correcting, and approving records before operational use.

Built for specialized biological workflows

✔ Plant tissue culture, propagation, rooting, acclimation, and contamination workflows
✔ Agrobacterium transformation, plasmid, strain, and selection workflows
✔ Mycology, fungal culture, spawn, substrate, and fruiting operations
✔ Synthetic biology, genetic engineering, and experimental production workflows
✔ Batch execution, sample lineage, state transitions, files, measurements, and notes
✔ Workflow history that feeds compliance, audit trails, reporting, dashboards, and exports

Molecular Designs in Execution Connect approved plasmids and released sequence versions to cloning, transformation, screening, and experimental workflows.

Buyer evaluation

Digitize the procedure your team can actually execute

A workflow should be structured enough to guide work and preserve evidence without turning every scientific exception into a software problem.

Procedure design

Select the steps, timing, materials, expected results, required fields, and approval points that must be consistent.

Exception paths

Define how operators document deviations, failed steps, contamination, holds, skipped work, and corrective actions.

Change control

Agree on who may draft, review, approve, supersede, and execute protocol and workflow versions.

Make execution the backbone of the laboratory platform

FlaskTrack turns procedures into execution systems. Teams can reuse methods, coordinate bench work, preserve sample history, monitor progress, generate reports, and maintain reviewable evidence without rebuilding records after the fact.

See Plans & Pricing Compliance Automation Reporting & API