Our Delivery Process
A structured pathway from initial objectives to reproducible deliverables — minimizing ambiguity and maximizing scientific utility.
Four Stages, Full Transparency
Every engagement follows the same structured pathway — so you always know what's happening, what's next, and what you'll receive.
Discovery & Alignment
We start by understanding your data, your biological questions, and what success looks like. This is a conversation — not a form.
- Checklist-based data intake & readiness review
- Risk & assumption log
- Outcome framing — figures, tables, KPIs you need
- Timeline and resource assessment
Scoped Proposal
You receive a clear, written proposal with defined deliverables, milestones, and pricing — no ambiguity.
- Defined deliverables & acceptance criteria
- Milestone-based timeline with ranges
- Transparent pricing model (fixed, milestone, or hourly)
- Approval checkpoint before work begins
Execution & Iteration
Analysis and pipeline work proceed in a version-controlled, containerized environment. You see interim results — not a black box.
- Git-managed, containerized workflows
- Interim QC snapshots & validation checkpoints
- Regular check-ins on progress and emerging findings
- Scope adjustments handled transparently
Delivery & Knowledge Transfer
Final outputs are delivered with full documentation, and we stay available to make sure you can use them.
- Reports, publication-ready figures & tables
- Pipeline manifest with parameters & environment
- README documentation & usage guide
- Follow-up support window included
What You'll Receive
- Written proposal with clear scope & pricing
- Interim progress updates & QC snapshots
- Final report with publication-ready figures
- Versioned pipeline & environment manifest
- Documentation bundle & usage notes
- Post-delivery support window
Typical Timelines
- Pilot / single analysis: 1–3 weeks
- Multi-sample study: 3–6 weeks
- Pipeline development: 4–8 weeks
- Custom software: scoped individually
Reproducible by Design, Secure by Default
Every workflow is version-controlled, containerized, and documented. Data is handled with the same care you'd expect from a regulated environment.
Every analysis is Git-managed with branching, tagged releases, and full commit history.
Docker and Singularity containers with lockfiles ensure deterministic execution across any system.
Structured config manifests, parameter logs, and audit trails for every run.
Encrypted transit, least-privilege access, and optional encrypted object storage. Sensitive identifiers hashed on request.
QC gates at each stage with summary metrics — problems caught early, not at delivery.
README bundles, usage guides, and interpretation notes included with every deliverable.
Want to walk through an upcoming dataset?
We can assess data readiness and outline a draft workflow — response typically within one business day.