Enterprise AI Infrastructure · On-Premise · NVIDIA DGX Spark


OpenGate deploys production-grade AI infrastructure directly inside your organization — purpose-built appliances running domain-specific models on NVIDIA DGX Spark silicon, fully air-gapped, with the strategy, implementation, and managed services to make it operational from day one.

30 → 4 min

contract review

Weeks

to production AI

Zero

data leaves your network

87%

of AI projects fail. Ours ship.

gatekeeper@dgx-spark ~ opengate-appliance

The Opportunity

AI is transforming every industry. Most businesses are locked out.

$0T

Global AI spend in 2026

Gartner

Trillions pouring into AI — yet most mid-market businesses can't access enterprise-grade models without shipping their data to the cloud.

0%

AI projects never reach production

Industry average

Fragmented tooling, compliance barriers, and the 'AI team' hiring problem block the path from prototype to operations.

0%

of apps will embed AI agents

Gartner 2026

Up from less than 5% in 2025. The businesses that operationalize AI first will compound their advantage. The window is closing.

0%

CIOs increasing AI budgets

Deloitte

The question isn't whether to invest — it's how to deploy safely, on-premise, without building an ML platform from scratch.

“We don't need another AI SaaS subscription. We need AI that runs on our hardware, behind our firewall, with models trained on our data.”

— Every CIO we've talked to

The Appliance

Hardware + software + services. One box.

OpenGate isn't a SaaS platform you log into. It's a physical appliance on your network — running domain-specific AI agents with full governance. Plug in, configure playbooks, go live.

Playbook-Driven AI Agents

Every workflow is a YAML playbook with explicit reasoning chains. Contract review, prior authorization, ticket triage — each with domain-specific LoRA adapters that hot-swap per request.

# playbooks/legal/contract_review.yml
id: contract-review
model: llama-3.1-8b
adapter: legal-general-v1    # LoRA rank 64
use_rag: true

steps:
  - extract_parties       # Identify all parties
  - key_terms             # Commercial terms
  - risk_analysis         # HIGH / MEDIUM / LOW
  - generate_memo         # Attorney-ready memo

Air-Gapped by Design

Zero external API calls. Zero cloud dependencies. JWT auth, AES-256 encryption at rest, immutable audit logs on every inference call. HIPAA and SOC 2 by architecture — not by checklist.

0

External calls

0 B

Data egress

AES-256

Encryption

Full Observability

OpenTelemetry traces on every inference. Prometheus metrics, Grafana dashboards, Loki log aggregation. Know exactly what your AI is doing, when, and at what cost.

P50 latencyToken/s$/queryAdapter perf

RAG Pipeline Built In

LlamaIndex orchestrates the full pipeline — 512-token chunks, 50-token overlap, nomic-embed-text embeddings (768-dim) into Qdrant vector storage. Your documents, your vectors, your building.

IngestChunkEmbedStoreRetrieve

Scale by Stacking DGX Sparks

Start with one DGX Spark: 128 GB unified memory, 1 PFLOP FP4, GB10 Grace Blackwell. Need more? Stack two via 200GbE ConnectX-7 for 256 GB combined — supporting models up to 405B parameters.

1× SPARK

128 GB

up to 200B params

2× STACKED

256 GB

up to 405B params

LINK

200 GbE

ConnectX-7

Services

Your AI partner from pilot to production

We don't just sell hardware. We partner with you to discover, build, deploy, and optimize AI workflows — then stand behind them.

Start Here

Paid Pilot

4-6 weeks · Prove the ROI

We deploy the appliance on your network with 1-2 use cases, load your documents into the RAG pipeline, and measure real results — time saved per workflow, output quality, and team adoption. Not a demo. A proof of value on your actual data.

Deploy on your network
50-100 customer documents loaded
Vertical-specific playbooks configured
Baseline metrics established

Full Appliance Deployment

Turnkey delivery + training

A pre-configured DGX Spark loaded with your playbooks, LoRA adapters trained on your domain data, and the full observability stack. Professional installation, admin training, and 30 days of onsite support included.

DGX Spark hardware + software
Custom LoRA adapter fine-tuning
4 pre-built Grafana dashboards
Staff training + 30-day support

Managed AI Operations

Ongoing partnership

We don't walk away after deployment. Continuous model monitoring, adapter retraining, playbook optimization, and quarterly business reviews with usage analytics. When you're ready to scale, we help you stack hardware and expand verticals.

Model updates + new playbooks
Priority support (4-hour SLA)
Quarterly business reviews
Scaling consultation

Professional Services

À la carte expertise for specialized needs

Custom LoRA fine-tuning

Train domain adapters on your data

Custom playbook development

New workflows for your processes

Integration services

Connect to your existing systems

AI strategy consulting

Identify highest-ROI automation targets

Architecture

Three nodes. One appliance. Zero cloud.

A purpose-built 3-node architecture connected over your local LAN. Control plane, GPU inference, and observability — each containerized with a clear role.

$ docker compose up -d
Creating gatekeeper-control-plane ... done
Creating gatekeeper-gpu-inference ... done
Creating gatekeeper-observability ... done

No Kubernetes. No cloud accounts. No DevOps team.

Governance & Security

HIPAA/SOC 2 compliant · zero external API calls

JWT AuthAudit LoggingAES-256 EncryptionAir-Gap Mode

Agent Playbook Engine

Legal, healthcare, and IT ops verticals with domain adapters

YAML PlaybooksStep ChainingLoRA Hot-SwapGuardrails

RAG & Knowledge Layer

Document ingestion, vector embeddings, semantic retrieval

LlamaIndexQdrant (cosine)nomic-embed-text512t chunks

Control PlaneCore

Orchestrates all inference, RAG, and agent workflows

FastAPI GatewayPostgreSQL 16Agent EngineCost Tracking

Observability Stack

Full-stack monitoring, traces, metrics, and logs

OpenTelemetryPrometheusGrafanaLoki

GPU Inference — NVIDIA DGX Spark

Stackable to 256 GB via 200GbE ConnectX-7 for 405B models

GB10 BlackwellTensorRT-LLM128GB LPDDR5x1 PFLOP FP4

How We Work

From discovery to production AI — with you at every step

01

Discovery

We learn your workflows

Our AI engineers spend time with your team — mapping the operational workflows that consume the most time. Contract review backlogs. Prior auth denials. Ticket response SLAs. We find the highest-ROI automation targets.

Workflow mappingROI analysisData auditCompliance review
02

Configure

Playbooks + adapters

We build YAML playbooks tailored to your workflows and fine-tune LoRA adapters on your domain data. Each playbook defines explicit step-by-step reasoning chains — not prompt engineering, but structured AI workflows.

# Built for your firm
adapter: your-domain-v1
steps: extract → analyze → classify → output
03

Deploy

Rack, plug, go live

We ship a pre-configured DGX Spark appliance loaded with your playbooks, adapters, and document pipeline. Your team racks it, connects to the LAN, and runs docker compose up. Production AI in hours, not months.

$ docker compose up -d
Creating gatekeeper-control-plane ... done
Creating gatekeeper-gpu-inference ... done
Live on 192.168.x.x | P50: 340ms
04

Ingest

Your documents, your vectors

Feed your contracts, policies, runbooks, or clinical records into the RAG pipeline. LlamaIndex chunks at 512 tokens, nomic-embed-text generates 768-dim vectors, Qdrant indexes everything locally. Nothing leaves the building.

DocsChunkEmbedQdrant
05

Optimize

Continuous improvement

We don't walk away after deployment. Ongoing monitoring, adapter retraining, playbook tuning, and scaling consultation. When you're ready, stack a second DGX Spark for 256 GB and 405B parameter models.

1× Spark
128 GB · 200B
2× Stacked
256 GB · 405B

The result: production AI on your network, governed by your policies, powered by NVIDIA silicon, supported by our team.

Verticals

8 production playbooks. 3 verticals.

Each vertical ships with YAML playbooks, a fine-tuned LoRA adapter, and pre-built RAG pipelines. Every playbook defines explicit reasoning chains — not prompt engineering, but structured AI workflows.

Legal3× faster reviews

Legal AI

Three production playbooks for law firms: contract review with risk classification, e-discovery document screening with privilege analysis, and legal memo drafting in standard firm format. LoRA adapter trained on CUAD contract dataset.

contract_review.yml

Extract PartiesKey TermsRisk AnalysisGenerate Memo

discovery_assist.yml

Classify DocPrivilege ScreenKey FactsReview Log

legal_memo.yml

Identify IssuesResearchDraft Memo
legal-general-v1 · Llama 3.1 8B
Healthcare2.5× faster auth

Healthcare AI

Clinical chart summarization with ICD-10 coding and prior authorization narrative generation. Identifies missing documentation before payer submission. HIPAA-compliant by architecture — every token stays on-premise.

chart_summary.yml

DemographicsHistoryAssessmentSummary

prior_auth.yml

Request DetailsClinical JustificationCompletenessDraft
healthcare-chart-v1 · Llama 3.1 8B
IT Operations3× faster triage

IT Operations AI

Automated ticket triage with P1-P4 priority and team routing, guided runbook execution with step-by-step validation, and self-service knowledge base assistant. Trained on internal KB articles and runbooks via RAG.

ticket_triage.yml

ClassifyPrioritizeSuggest FixRoute

runbook_exec.yml

Identify RunbookValidateExecuteDocument

kb_assist.yml

Understand IssueSearch KBGuide ResolutionVerify
it-ops-triage-v1 · Nemotron Mini 4B

Built On

NVIDIA DGX SparkGB10 Grace BlackwellTensorRT-LLMConnectX-7 200GbELlamaIndexQdrantFastAPIPostgreSQL 16OpenTelemetryPrometheusGrafanaLokiDocker ComposeLoRA Adaptersnomic-embed-textstructlogNVIDIA DGX SparkGB10 Grace BlackwellTensorRT-LLMConnectX-7 200GbELlamaIndexQdrantFastAPIPostgreSQL 16OpenTelemetryPrometheusGrafanaLokiDocker ComposeLoRA Adaptersnomic-embed-textstructlog

The Flywheel

Every deployment compounds the next

OpenGate creates a virtuous cycle: each successful workflow automation drives expanded adoption. More adoption justifies deeper infrastructure investment. The partnership deepens with every deployment.

Start with one high-impact workflow → prove ROI

Success drives adoption across departments

More use cases justify stacking hardware

Deeper partnership → custom adapters, new verticals

OpenGatePartnership EngineWorkflowDiscoveryApplianceDeploymentAI AgentProductionOperationalImpactExpandedAdoptionDeeperPartnership

Why OpenGate

The AI partner that actually ships

We're not selling seats or API tokens. We're building, configuring, and deploying AI appliances tailored to your business — then standing behind them.

01

We're Your AI Team

No ML engineers on payroll? That's the point. OpenGate provides the AI infrastructure expertise — from workflow discovery through production deployment to ongoing optimization. We're the AI team you'd hire, delivered as a partnership.

02

Your Data Never Leaves

Air-gapped inference. Zero external API calls during operation. Every token stays on your LAN. JWT auth, AES-256 encryption at rest, immutable audit logs. HIPAA and SOC 2 compliant by architecture — not by checklist.

03

Domain-Specific, Not Generic

LoRA adapters fine-tuned for your industry. Contract review agents that know indemnification clauses. Prior auth agents that speak ICD-10. Ticket triage agents that map to your runbooks. Not a chatbot — a specialist.

04

NVIDIA DGX Spark Native

Purpose-built for the GB10 Grace Blackwell Superchip. 128 GB unified memory, 1 PFLOP FP4, TensorRT-LLM quantization, 6,144 CUDA cores. Stack two over 200GbE ConnectX-7 for 256 GB and 405B-parameter models.

05

Predictable Economics

No per-seat SaaS fees. No metered API pricing that scales with usage. One appliance, predictable costs. Real-time per-query cost tracking, budget caps per department, and total cost transparency from day one.

06

Production in Weeks, Not Quarters

From first conversation to live inference in weeks. Pre-configured hardware, pre-trained adapters, production-ready playbooks. We've compressed the 12-month enterprise AI deployment into a deliverable.

Our Belief

AI should work like electricity. You plug it in. It runs.

Fortune 500 companies spend tens of millions building AI platforms. A 50-person law firm shouldn't have to. A 200-bed hospital shouldn't have to. OpenGate closes that gap — same NVIDIA silicon, same model quality, delivered as an appliance with a partner standing behind it.

Discover

your highest-ROI workflows

Build

domain-specific AI agents

Deploy

on your network, air-gapped

Evolve

continuous optimization

We're building towards a future where every business — not just tech companies — runs AI as core infrastructure.

Get Started

Let's build your AI appliance.

Tell us your workflows — contract review, prior authorization, ticket triage, knowledge management — and we'll design an appliance with the right playbooks, adapters, and document pipelines. Delivered ready to deploy.

Turnkey deliveryAir-gapped deploymentOngoing support includedNVIDIA DGX Spark inside