Skip to content

Our Delivery Process

A structured pathway from initial objectives to reproducible deliverables—minimizing ambiguity and maximizing scientific utility.

Stages

  1. 1

    Discovery & Alignment

    Clarify data readiness, biological questions, constraints, success metrics.

    • Checklist-based data intake
    • Risk & assumption log
    • Outcome framing (figures, tables, KPIs)
  2. 2

    Scoped Proposal

    Milestones, timeline ranges, pricing model, dependencies.

    • Defined deliverables
    • Sample size / complexity notes
    • Approval checkpoint
  3. 3

    Execution & Iteration

    Reproducible analysis or pipeline implementation with interim previews.

    • Version-controlled workflow
    • Containerized environments
    • Interim QC & validation snapshots
  4. 4

    Delivery & Knowledge Transfer

    Hand-off plus optional ongoing advisory or maintenance.

    • Reports & publication-ready figures
    • Pipeline manifest + parameters
    • Follow-up support window

Reproducibility & Quality

Version Control

Git-based branching & tagged releases.

Environment Capture

Container or environment lockfiles for determinism.

Parameter Traceability

Structured config manifests & logs.

Data Handling

Scoped least-privilege access & encrypted transit.

Validation

QC checkpoints & summary metrics.

Documentation

README bundles & usage notes.

Security & Data Handling

Data is processed under controlled locations with optional encrypted object storage. Sensitive identifiers can be hashed or excluded on request. Long-term retention only by agreement.

Want to walk through an upcoming dataset?

We can assess readiness and outline a draft workflow.

Book Discovery Call Pricing Models Overview