100% Data Residency
GDPR · HIPAA · SOC 2 · ISO 27001 · EU AI Act ready
Prompts, documents, embeddings, and model outputs never leave your network. The full stack — inference, retrieval, orchestration — runs inside your perimeter.
Run Frontier Models On-Prem
H100 / H200 / B200 · AMD MI300X · Apple Silicon
Run 70B-class models on a single server. Pick the hardware tier and inference engine that fits your latency, throughput, and budget targets.
AI that thinks on your data — without leaving your network.
Contract review, technical-doc RAG, clinical summarization, financial research, support deflection, internal Q&A — all running on infrastructure you control.
Document & Knowledge Intelligence
Ground every answer in your private corpus. Extract structured fields, summarize, classify, and reason — with citations back to the source document. No data ever leaves your network.
- Contract & policy review with clause-level citations
- Technical, clinical, and financial document RAG
- Multi-language OCR and structured-field extraction
- Internal knowledge Q&A grounded in your sources
- Compliance copilots: KYC, AML, model risk
Multilingual & Domain-Tuned
Open-weight models fine-tuned to your terminology and language mix. 100+ languages. Domain adaptation on your private data.
Smart Workflow Automation
Auto-fill forms, extract structured fields, route exceptions to humans, and write back to your systems of record.
Production-grade AI
that runs on your hardware.
A complete reference stack — frontier open-weights, production inference engines, and private RAG — engineered, deployed, and operated for you.
Llama / Qwen / Mistral
Open-weight LLMs
vLLM / SGLang
Production inference
Qdrant / pgvector
Self-hosted vector store
LangGraph
Multi-agent orchestration
Ollama
Pilot & dev tier
Air-Gapped
Zero external dependency
Built for regulated, data-sensitive industries.
Wherever data residency, IP, or PII makes the public cloud a non-starter.
Legal
Contract review, due diligence, and e-discovery on privileged data — without sending a single document to a third-party API.
Healthcare
Clinical-note summarization, radiology, and prior auth — HIPAA-aligned by design with no PHI leaving your perimeter.
Financial Services
KYC/AML narratives, sanctions screening, equity research, and model-risk-managed assistants on MNPI-grade data.
Insurance
Claims triage, underwriting copilots, fraud detection, and policy issuance grounded in your historical book.
Manufacturing
Technical-document RAG, predictive maintenance, and IP-sensitive design assistance — air-gapped where required.
Government & Defense
Classified workloads, FOIA processing, and citizen services with full audit trails and zero external dependency.
Energy & Utilities
Asset intelligence, operations Q&A on operating manuals, and predictive maintenance on operational telemetry.
Retail & E-commerce
Catalog enrichment, agentic customer support, and fraud triage on customer PII and transaction history.
Compliance you can audit.
Engineered for the frameworks your security and legal teams already use.
GDPR & UK GDPR
EU and UK data residency by construction. Lawful basis for AI training and inference is straightforward when the data never leaves your network.
HIPAA Ready
PHI handling for US healthcare. On-premise inference is the cleanest structural path to HIPAA-compliant LLM deployments.
SOC 2 Type II
Procurement table-stakes for B2B. Extends your existing SOC 2 program to AI controls in 3–6 months.
ISO 27001 / 42001
InfoSec plus the first AI-management standard. ISO 42001 maps directly to EU AI Act conformity assessment and NIST AI RMF.
EU AI Act Aligned
Risk-tiered governance, GPAI obligations, and conformity-assessment readiness — fines up to 7% of global revenue make this non-optional.
Air-Gapped Audit Trails
Tamper-evident logs, role-based access, and forensic-grade observability — with no external SaaS dependency in the audit path.
Reference Architecture
A reference stack for sovereign enterprise AI.
Three layers, modular components, your data perimeter. Frontier open-weight models, production inference, and private RAG — engineered, deployed, and operated end-to-end on infrastructure you own.
Inference Layer
Open-Weight LLMs on Your GPUs
Llama 4, Qwen 3.5, Mistral, and DeepSeek served via vLLM or SGLang on H100 / H200 / B200 — or AMD MI300X. Sub-100ms tokens at production throughput. Apache 2.0 and MIT licensing means no vendor lock-in.
Orchestration Layer
Multi-Agent Routing & Tool Use
LangGraph orchestrates retrieval, reasoning, tool-use, and human-in-the-loop checkpoints. Specialist agents per domain — research, compliance, document intake — coordinated through a typed graph with full observability.
Knowledge Layer
Private RAG on Your Corpus
Hybrid search and re-ranking over Qdrant or pgvector. Encrypted at rest, role-based access, and citation-grounded answers. Ingest contracts, manuals, clinical notes, or trade records — all isolated to your network.
Capabilities
Contract & document review with clause-level citations
Multi-language OCR and structured-field extraction
Knowledge Q&A grounded in your internal documentation
Workflow automation with human-in-the-loop checkpoints
Compliance copilots: KYC, AML, model risk, EU AI Act
Domain fine-tuning on your data, on your infrastructure
Audit logs and role-based access on every interaction
Offline / air-gapped operation when required
Hardware Tiers
Pilot — Mac Studio M3 Ultra
Up to 512GB unified memory · Apple Silicon
7B–32B open-weight models · per-team deployments
From $25,000
Production — Single H100 / H200 Server
141GB HBM3e · NVLink · NVMe RAID
70B-class models · sub-100ms tokens
From $90,000
Enterprise — 8× H200 / B200 Cluster
Full NVLink fabric · tensor parallel · redundant
Frontier MoE 400B+ · sovereign-scale workloads
From $250,000
Ready to bring AI inside your perimeter?
From discovery to production in weeks, not quarters. We engineer, deploy, and operate the stack — you keep ownership of the data, the models, and the outcomes.
Schedule Your Demo
See Private AI in action for your specific workflows and compliance requirements
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Frequently Asked Questions
Common questions about Private AI for the enterprise
Cloud APIs send your data to a third-party provider for inference. Private AI runs the entire stack — model, vector store, orchestration, observability — inside your perimeter. Your prompts, documents, and embeddings never leave your network, and you keep ownership of every byte.
Any industry where data residency, intellectual property, or PII makes shared cloud risky: legal, healthcare, financial services, insurance, manufacturing, energy, government, and retail. The deeper the regulatory or competitive moat, the stronger the case.
For most enterprise workloads, yes. Qwen 3.5 leads GPQA Diamond at 88.4%, Llama 4 Maverick reaches 85.5% on MMLU, and GLM-5 hits 77.8% on SWE-bench. With domain fine-tuning, open models routinely outperform frontier APIs on customer-specific tasks because they've seen your data.
GDPR, HIPAA, SOC 2 Type II, ISO 27001 / 42001, the EU AI Act, NIST AI RMF, PCI-DSS, and FedRAMP. On-premise deployment is the cleanest structural path to all of them — and ISO 42001 maps directly to EU AI Act conformity assessment, so you can implement once and satisfy multiple regulators.
Tiers range from Mac Studio M3 Ultra for pilots (7B–32B models), through single-server H100/H200 for production (70B-class models, sub-100ms tokens), to 8-GPU H200/B200 clusters for frontier MoE workloads. Typical production deployment takes 4–8 weeks end-to-end — including data discovery, hardware procurement, model fine-tuning, and operator training.
Yes. We operate the inference, retrieval, evaluation, and observability stack — model upgrades, eval pipelines, and infrastructure are ours; data and outcomes stay yours. Open weights plus Apache/MIT licensing means there is no vendor lock-in: swapping a model is a config change, not a re-platform.