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Docs · OGN platform

GPU-native genomics operating system

From raw reads to GIAB-validated variant calls in a continuous GPU pipeline. This is the control surface for the engine: CLI, pipelines, benchmarks, and deployment runbooks.

CUDA 12+Hopper · AmpereGIAB-validated flowsSchemas stable

Snapshot Report offer

The Snapshot Report is a fixed-scope engagement designed to answer a single question: should you adopt OGN for GPU-accelerated variant calling on your data?

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

  • Fixed Snapshot Report fee + compute pass-through (scoped to a fixed number of runs / iterations).
  • 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.
Paid pilot offer | OGN documentation | Omnis Genomics