🛡️ Patent Pending | Backed by 28 USPTO Patent Filings & 2D Bounding-Box Grounding

Bypass the 17-Week Clinical Database Build Wall

Compile unstructured trial protocols into production-ready Medidata Rave ALS, Veeva Vault CDMS, and open CDISC architectures in under 24 hours. 100% vendor-agnostic portability with zero cloud data leaks.

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FDA 21 CFR Part 11 Compliant
Cryptographic audit trail & Part 11 e-signature gates
2026 FDA AI Guidance Ready
Deterministic PDF coordinate grounding, zero hallucinations
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Local-First On-Premise Appliance
Zero PHI cloud exposure; air-gapped local execution

The True Cost of Staying with the Status Quo

Every single day your database build team spends manually checking variable mappings against CDASH standards costs your pharmaceutical drug sponsors up to $8M in peak-sale patent commercial lifespan. Procurement departments are auditing timelines aggressively under the new 2026 FDA AI lifecycle mandates.

Verify Citations & Guidance References

Cost & Timelines: A landmark Tufts CSDD Study (sponsored by Veeva Systems and covered by FierceBiotech) reveals building a clinical database takes an average of 68 days. When databases are delayed beyond First Patient, First Visit (FPFV), it extends final database lock timelines by an average of 3 weeks.

COVID-19 Case Acceleration: In response to the pandemic, researchers found that the cycle time for a COVID-19 trial database build was compressed to 11 business days (an 83.9% reduction from standard timelines), proving rapid builds are possible under extreme operational overrides. Read the full analysis in Applied Clinical Trials and the associated Veristat Study.

Regulatory Mandates: The FDA Draft Guidance on Artificial Intelligence and Machine Learning in Drug Development (May 2026) outlines necessary validations and lifecycle tracking for AI-driven clinical workflow configurations.

Active Loss Under Manual Timelines
$8,000,000

Accumulating patent valuation leaks in real time.


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60-Second Database Friction Audit

Question 1 of 4

Q1: What is your typical Phase II/III clinical database build timeline?

Q2: What is the primary operational bottleneck stalling procurement?

Q3: Which EDC target engines does your organization require?

Q4: How many clinical study protocols does your organization initiate per year?

>>> INITIATING ALGORITHMIC ROUTING ENGINE...

G-Flow G-Flow Product Architecture Highlights

On-Premise Secure Stack

Self-contained hardware appliance serving continuous batching and PagedAttention loops with zero external API dependencies.

  • Dell Pro Max GB10 configuration
  • 128GB high-speed Blackwell memory
  • vLLM container orchestration
  • Speculative decoding via 2B Gemma 4
  • Outlines grammar-constraint engines
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Regulatory AI Compliance

Aligned with the May 2026 FDA AI Action Plan. Cryptographic auditing and strict verification rules built into the compilation flow.

  • Extractive Coordinate Grounding (character offset)
  • Consensus Gate™ (4-role approval)
  • Local 31B Parameter Judge audits
  • GitOps immutable change-control trail
  • Fully compliant with 21 CFR Part 11
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Universal Vendor Agnosticism

Build once in CDISC Intermediate Language (IL) and compile to any EDC target with zero vendor lock-in.

  • Native CDISC ODM-XML & CDASH standards
  • Multi-target compilation (Rave, Veeva, ODM-JSON)
  • Write-once, deploy-anywhere protocol IL
  • Zero SaaS platform lock-in or migration fees
  • Cross-EDC dataset & form portability

Oncology Validation Case

Real-world validation metrics on Cabozantinib vs. Belzutifan oncology trials containing complex visit branching.

  • Ingestion of NCT01631552 protocol (PDF)
  • SmolDocling Multimodal Parser
  • Tables translated without row failures
  • 10 pages of visit tables visual parsing
  • 24-hour Medidata Rave ALS Export
CORE PILLAR: UNRESTRICTED PORTABILITY

Build Once in Standard CDISC IL — Target Any EDC System

Legacy EDC vendors lock your clinical trial definitions inside proprietary SaaS silos. G-Flow breaks vendor lock-in: our semantic engine compiles protocol logic into standardized CDISC Intermediate Language (IL). Export verified database specifications to Medidata Rave ALS, Veeva Vault CDMS, Oracle Clinical One, or open CDISC ODM-XML in under 24 hours without rebuilding eCRFs from scratch.

✓ Medidata Rave ALS ✓ Veeva Vault CDMS ✓ CDISC ODM-XML v1.3.2 ✓ Zero Vendor Lock-in

Hardware Specification & TCO FAQ

What is the recommended hardware appliance?

We recommend the Dell Pro Max with NVIDIA GB10 micro-workstation (Makoto Tiger™). G-Flow is certified and pre-provisioned to run locally on this compact workstation to maintain 100% data sovereignty, air-gapped security, and zero cloud egress.

How much does the hardware cost?

The Dell Pro Max GB10 appliance is $7,000, purchased directly from us via our authorized Dell OEM partner site. To guarantee cryptographic firmware attestation, hardware execution halt bus integrity, and factory pre-imaging, all hardware must be procured through our Dell OEM channel. We do not support or license deployments on hardware purchased through third-party retail, consumer configurators, or other unauthorized avenues (Reserve via Dell OEM Partner Channel →).

How does G-Flow licensing and hardware delivery work?

We deliver a unified turn-key appliance solution. When you reserve your seat in one of our Sovereign Cohorts, your Dell Pro Max GB10 ($7,000) is drop-shipped directly to your facility through our Dell OEM partner channel, factory pre-loaded with the G-Flow Custom Factory Image (CFI). Your Grandfathered Software Activation Key activates the appliance on first boot with zero manual configuration required.

What are the hardware specifications?

The target appliance configuration includes:

  • CPU NVIDIA GB10 Grace CPU (20-core)
  • GPU NVIDIA GB10 Blackwell GPU
  • Memory 128GB LPDDR5X Unified Memory
  • Storage 4TB M.2 PCIe Gen4 NVMe SSD
  • OS NVIDIA DGX OS 7
  • Chassis Dell Pro Max GB10 L6 Chassis

What is the TCO compared to Cloud AI API solutions?

Deploying on-premise hardware eliminates recurring per-token cloud costs. For an organization processing 6+ protocols annually with active design iterations, G-Flow recovers the hardware investment ($7,000) within the first 14 days of operation, while preventing million-dollar IP leaks to external LLM providers.