On-Premise Enterprise AI

Your AI. Your Hardware. Completely Airtight.

Deploy secure, on-premise AI automations that execute inside your local network. Zero data leakage. Total compliance. The ultimate enterprise alternative to public cloud LLMs.

Enterprise-grade compliance: SOC 2 Ready · GDPR Compliant · HIPAA Aligned

Public cloud AI leaks. DIY AI is unmanaged.

  • Sending sensitive CRM, financial, and patient data to ChatGPT or Claude means surrendering control to third-party servers.
  • Stitching together raw Ollama or JeffyAI setups leaves you with no governance, no compliance, and no enterprise integration.

Solutions

A complete enterprise AI platform — inside your perimeter

On-Prem LLM Workbench

A secure chat and reasoning workspace for every employee, served by open and commercial models running entirely on your hardware.

Secure Automation Pipelines

Build and orchestrate multi-step AI workflows that act on internal systems — with human-in-the-loop approvals and full traceability.

Native Enterprise Connectors

First-class APIs and adapters for your CRM, ERP, data lake, ticketing, and identity systems — no data ever transits a third party.

Governance & Audit

Immutable, exportable audit logs of every prompt, action, and data access — the evidence your auditors and regulators expect.

RBAC & SSO

Granular role-based access control with SAML/OIDC single sign-on, integrating cleanly with your existing identity provider.

Centralized Model Management

Version, deploy, and retire models across nodes from one console — with signed artifacts and reproducible rollouts.

Killer feature

Secure External Enrichment Workflow

Standard offline chatbots can't touch the outside world. SafeLocal can — safely. Take a real example: automatically preparing a sales rep for a client meeting. SafeLocal gathers public intelligence anonymously, merges it with your most sensitive CRM data locally, and synthesizes the executive brief strictly on-premise. The external world informs your AI without ever seeing your data.

Outer Loop · 01

Anonymous Fetch

SafeLocal queries public web sources anonymously for external client data — news, filings, org charts, market signals. Requests carry no internal identity, no prompts, and no CRM data. Identity-stripped egress.

Inner Loop · 02

Private Cross-Referencing

Sanitized public data is piped one-way, securely, into your local infrastructure. It is staged behind your firewall where internal automations can reference it — but nothing flows back out. One-way secure ingestion.

Local Node · 03

On-Premise Synthesis

A local LLM merges the external data with confidential internal CRM records to produce a secure, deal-ready client brief — entirely on your hardware. 0% of internal data leaves the building.

The enterprise comparison

SafeLocal vs. Cloud SaaS AI vs. DIY Open-Source

A factual capability comparison for enterprise security and procurement teams evaluating on-premise AI against public cloud LLMs and unmanaged open-source stacks.

CapabilitySafeLocal EnterpriseCloud SaaS AI (ChatGPT Team / Claude)DIY Open-Source (JeffyAI / Ollama)
Data Privacy100% Isolated — never leaves your networkThird-Party Servers — processed by the vendorLocal but Unmanaged — no policy enforcement
Internal System AutomationNative Enterprise APIs — CRM, ERP, data lakeProhibited / Cloud-Restricted — no access to internal systemsLacking Management UI — manual scripting only
DeploymentOne-Click MSI / Server — corporate-ready installersCloud Only — no on-prem optionManual Terminal Config — CLI assembly required
Secure External EnrichmentYes — Dual-Loop (public data in, nothing out)No — your data goes to the vendorNo — not available
Compliance (SOC 2 / GDPR / HIPAA)Built-in & Auditable — evidence on demandShared-Responsibility — vendor-dependentYour Problem — no built-in controls
Access Control & AuditEnterprise RBAC + Logs — SSO / SAML / OIDCLimited Admin — vendor consoleNone — DIY only
Support & SLA24/7 Enterprise SLA — dedicated engineeringTiered Support — plan-dependentCommunity Forums — best-effort

Comparison reflects typical enterprise configurations. ChatGPT, Claude, JeffyAI, and Ollama are trademarks of their respective owners and are referenced for comparison only.

Pricing

Enterprise licensing, built around your deployment

Transparent, capacity-based licensing with no per-token surprises. Every tier runs entirely on your infrastructure.

Departmental

Custom/ annual

Single-node deployment for one team or business unit.

  • Single-node, on-prem or VPC
  • On-Prem LLM Workbench
  • RBAC + audit logging
  • Business-hours support

Sovereign / Air-Gapped

Custom/ annual

Fully isolated deployment for regulated and critical sectors.

  • Everything in Enterprise
  • Fully air-gapped operation
  • Dedicated solutions engineer
  • Custom compliance packages

Built for security teams that assume breach

SafeLocal inverts the cloud AI model: instead of sending your data to the model, we bring the model to your data. Every layer is designed around a default-deny posture, least privilege, and complete auditability — zero data egress by default, AES-256 at rest and TLS 1.3 in transit, an immutable audit trail of every prompt and action, and air-gap-ready operation with signed, verifiable installation bundles.

Answers for security & procurement

How does SafeLocal guarantee zero data leakage during web lookups?

SafeLocal uses a dual-loop architecture. The Outer Loop performs anonymized public web retrieval through an isolated egress proxy that carries no internal identifiers, prompts, or CRM data — only generic public lookups ever leave your perimeter. Retrieved public data is sanitized and piped one-way into the Inner Loop, where a local LLM running entirely on your hardware merges it with confidential internal data. No internal data, embeddings, or prompts are ever transmitted externally, and all outbound traffic is governed by default-deny egress policies with full audit logging.

What are the hardware requirements for local enterprise deployment?

SafeLocal scales from a single workstation to multi-node GPU clusters. A typical departmental deployment runs on one server with an NVIDIA A100/H100 (or 2× RTX 6000 Ada), 128 GB RAM, and 2 TB NVMe storage. For organization-wide rollouts we provide a reference architecture for Kubernetes-based GPU clusters. CPU-only inference is supported for smaller models in edge or constrained air-gapped scenarios.

Can SafeLocal integrate with air-gapped internal environments?

Yes. SafeLocal is designed for fully air-gapped operation. Models, dependencies, and updates are delivered through signed, offline installation bundles. In air-gapped mode the Outer Loop enrichment is disabled, and all inference, automation, and internal integration run entirely within your isolated network with no outbound connectivity required.

Is SafeLocal compliant with SOC 2, GDPR, and HIPAA?

SafeLocal is engineered to be SOC 2 ready, GDPR compliant, and HIPAA aligned. Because all processing occurs on infrastructure you control, data residency, retention, and access are fully governed by your own policies. SafeLocal ships with RBAC, immutable audit logs, encryption at rest and in transit, and exportable compliance evidence to accelerate your audits.

How is SafeLocal different from running Ollama or open-source models myself?

DIY open-source stacks such as raw Ollama or JeffyAI give you a model runtime but no enterprise layer. SafeLocal adds managed deployment (one-click corporate MSI/server installers), enterprise RBAC and SSO, native automation APIs to your internal systems, the Secure External Enrichment pipeline, centralized audit and governance, and a 24/7 enterprise SLA — turning an unmanaged experiment into a compliant production platform.