How It Works

AI That Never Leaves Your Building

Most AI tools send your data to external servers. Ours doesn't. Here's how.

The Hidden Cost of Cloud AI

Every time you use ChatGPT, Copilot, or Claude for work, your data travels to external servers. For most tasks, that's fine. For finance? It's a problem.

Board materials

Draft board packs containing strategy, M&A plans, and sensitive forecasts.

Financial models

Scenario planning, valuation models, and competitive intelligence.

Confidential data

Employee compensation, customer contracts, pre-announcement numbers.

This isn't paranoia. It's governance.

Private by Architecture, Not Just Policy

Your Data

Forecasts, board packs, models

Your Infrastructure

On-prem or private cloud

Local LLM

Llama, Mistral, Phi

Results

Commentary, reports, answers

Everything above stays inside your network

Local models

Open-source LLMs (Llama, Mistral) running on your servers. No API calls to OpenAI or Anthropic.

Your infrastructure

On-prem, private cloud, or Azure private endpoints. Your choice of deployment target.

Zero data egress

Nothing sent to OpenAI, Anthropic, or any third party. Complete data sovereignty.

In Practice

Your board pack drafts never touch external servers
Forecast models stay inside your firewall
M&A analysis doesn't become AI training data
You control data retention and deletion
Auditable — you can prove where data went

What We Deploy

Models

Llama 3, Mistral, Phi — matched to your needs and infrastructure. Not every problem needs GPT-4.

Deployment

Docker containers, Kubernetes, or direct VM installation. Whatever fits your existing stack.

Integration

API endpoints your existing tools can call. Works with Power Automate, Python, Excel add-ins, and more.

Management

Monitoring, updates, and support included. We don't deploy and disappear.

"We match the model to your infrastructure and use case. Not every problem needs GPT-4."

What Private AI Can't Do (Yet)

We believe in honesty. Private deployment has tradeoffs.

Private AI strengths

Data sovereignty — full control
Compliance and audit-ready
No per-call API costs at scale
Works offline — no internet dependency

Cloud AI strengths

Largest models (GPT-4, Claude)
Fastest iteration and updates
Zero infrastructure to manage
Broadest general capability

For most finance use cases — commentary generation, document Q&A, process automation — private models are more than capable. We'll tell you if they're not.