Platform, pipeline, and proof docs

Deliverables (what you get)

• A reproducible run on a representative dataset (yours or a public substitute you approve).
• A shareable proof bundle artifact folder you can forward internally:
  • vcf (+ optional index)
  • provenance.json (engine version, container digests, hashes)
  • metrics.json (runtime / throughput / cost hooks)
  • logs.ndjson (downloadable + streamable)
  • summary.md (human-readable recap + rerun commands)
• Runtime + cost comparison against your stated baseline (DRAGEN / Parabricks / Sentieon / GATK, etc.).
• Written acceptance criteria agreed up front (accuracy, runtime, cost, reproducibility).

Inputs (what we need)

• Dataset type + size (WGS / exome / panel, sample count, typical coverage).
• Baseline target (what you want us to beat, and the constraints you care about).
• Deployment shape (cloud/on‑prem, GPU model, storage).
• Any red lines (PHI handling, data residency, networking constraints).

Timeline (typical)

• Week 1: intake, baseline capture, environment constraints, acceptance criteria doc.
• Week 2: runs, proof bundle delivery, runtime + cost comparison, readout.

Pricing model

• Low-friction fixed Snapshot Report fee + compute pass-through (scoped to a fixed number of runs / iterations).
• Keep the first report small by default; expand only after the proof bundle shows value.
• Enterprise licensing is discussed only after the Snapshot Report produces a deterministic proof bundle.

Next steps

• Submit a request at /company/contact.
• If you want to talk first, include two meeting times (with timezone) and we’ll confirm quickly.