About Sanctum AI

Tools, not toys.

Sanctum AI delivers locally-deployed AI agents that run entirely on client infrastructure — on a single workstation for an individual, or on a shared on-site machine accessed by an entire team. Same agentic workflows that everyone's talking about. None of the data leaves the building.

The idea, in one breath

The giant cloud AI models powering today's agentic systems are remarkable. They're also overkill for most jobs. The AI agent your accounting department uses to generate monthly reports doesn't need to know how to bake a good cherry pie — and you definitely don't need to pipe your financials through a third-party cloud to get the job done.

We replace those giant cloud models with smaller, focused models that run on local hardware. They get the job done without the cloud, and without the fluctuating API costs that make AI line-items impossible to budget.

“Tools, not toys. Every Sanctum product delivers measurable operational value. No novelty. No gimmicks. AI that earns its place in your stack.”

How a Sanctum deployment works

Two ways to deploy. Zero data leaving the building.

Shared on-site deployment

One capable on-prem machine hosts the model. Multiple employees access it from their own workstations over the local network. Ideal for teams of 5–50 with consistent workflows.

Single-machine deployment

For privacy-sensitive individuals or roles, the entire stack runs on one workstation. No network, no shared service — just an agent that lives on the device.

Product roadmap

Starting where the value is clearest.

We're shipping the agents customers ask for first, then growing into adjacent capabilities as the platform matures.

Phase 1 — Now

Knowledge & documents

Document intelligence, retrieval-augmented knowledge agents, and task automation built on focused open-weight models.

Phase 2 — 2026–2027

Image & audio

On-device image manipulation and audio processing workflows for media-heavy teams that can't upload source assets.

Phase 3 — 2027–2028

Coding & expanded library

Local AI coding assistant and an expanded library of purpose-built models for additional verticals.

The competitive picture

The gap no current solution fills.

Cloud AI is convenient but exposes data. Enterprise on-prem is air-tight but requires an ML team. DIY open-source is flexible but unfinished. Sanctum sits in the middle.

	Cloud AI (OpenAI, Anthropic, Gemini)	Enterprise on-prem (IBM, SAP, Oracle)	DIY open-source (LLaMA, Ollama)	Sanctum AI
Data stays on-premises	No	Yes	Yes	Yes
No ML expertise needed	Yes	No	No	Yes
SME-accessible pricing	Yes	No	Yes	Yes
Production-ready tooling	Yes	Yes	No	Yes
Predictable fixed cost	No	No	Yes	Yes
RAG + custom tooling	Limited	Complex	DIY	Built-in

The team

Operator experience, applied to a new category.

Michael Chase, Founder & CEO. Early employee at Digioh, where he helped scale the company from a 3-person startup to a recognized player in the martech space, growing to 2,000+ DTC brand clients including Death Wish Coffee and Dollar Shave Club. Extensive hands-on experience in SaaS product development, go-to-market strategy, and B2B customer growth.

Sanctum AI is currently seeking a senior ML engineer / infrastructure lead with local-LLM deployment experience.

Get in touch