AI that doesn't leak your data.
Real agent capability without your customer data, contracts, IP, or PHI ever leaving your environment. Open-source models running in your VPC. Frontier models via your own cloud account. Fully air-gapped where you need it.
The default question
Where does your data go when it talks to AI?
SaaS AI products send every prompt to the provider's servers. Fine for consumer use; a non-starter for PHI, FERPA records, financial detail, manuscripts, contracts, or anything you've promised customers won't leave your environment.
Quantilus only deploys in environments that meet your data policy. Can't leave your VPC? Neither do our agents. Need air-gapped? We ship air-gapped.
Three ways
AI inside your perimeter, three ways.
Pick the deployment model that matches your data-handling policy and your model-quality needs. We've shipped all three.
Open-weight models (LLaMA, Mistral, Qwen, Gemma) inside your VPC or on-prem. No external API calls. No telemetry.
Best for: highly regulated, full data control.
Claude via AWS Bedrock, GPT via Azure OpenAI, Gemini via Vertex. Your contract with the hyperscaler. Data stays in your cloud account.
Best for: frontier quality without direct model-provider exposure.
No internet egress. No model-provider relationship. Open-weight models on your hardware, your network only.
Best for: defense, classified, fully isolated workloads.
You can also mix: high-volume / low-sensitivity workloads on a hyperscaler-hosted frontier model, sensitive workloads on a self-hosted open-weight model. The agent picks the right one per request, transparently.
Compliance
Built for the standards your regulators care about.
Every private-AI deployment ships with the trust layer your industry expects.
Healthcare
HIPAA-aligned. BAAs available. PHI handling, redaction, full audit trail.
Education
FERPA-aware. Records scoped to the institution. Disclosure controls logged.
EU & Global
GDPR. Data-subject rights. EU residency. Processor agreements available.
Enterprise
SOC 2 Type 2. Customer-side KMS, BYOK, HSM integration.
Government
FedRAMP-aligned. GovCloud regions. Air-gapped configurations.
Audit & Review
Full audit trail. Every prompt, tool call, decision logged with reasoning.
What we handle
From model selection through monthly operations.
You don't need an in-house ML platform team. We bring the model layer.
- Model selection & deployment. Open-source or hosted; VPC / on-prem / GovCloud / air-gapped
- Inference infrastructure. GPU sizing, autoscaling, request queueing, fallback routing
- Monitoring. Uptime, latency, cost, output quality, drift detection
- Security ops. Access control, secret rotation, audit retention, vulnerability response
- Compliance evidence. The artifacts auditors and customers will ask for
Adversarial threats
An agent that acts on your systems is a target.
Private deployment protects where your data lives. These controls protect the agent itself from being manipulated into doing the wrong thing.
A malicious instruction hidden inside otherwise normal content (an email, a document, a web page the agent reads) that tries to hijack what the agent does next.
How we defend it: input validation and sanitization, least-privilege tool permissions so the agent can't exceed its scope, human approval gates on high-stakes actions, and an eval harness that tests known injection patterns on every change.
Corrupted or planted data in the agent's knowledge sources or training set, designed to skew its answers or behavior over time.
How we defend it: vetted and access-controlled knowledge sources, provenance and change tracking on ingested data, grounding with citations so every claim traces to a source, and drift monitoring that flags behavior changes early.
Every action the agent takes is logged with its reasoning, so an attempted manipulation is visible and reviewable. Defense is built into the agent from day one, alongside the deployment model you choose above.
Who this is for
Industries where this isn't optional.
If any of these describe your business, the SaaS-AI default isn't an option for you. Private deployment is the only deployment.
Healthcare
PHI must stay in HIPAA-aligned environments, patient records, clinical notes, prior authorization.
Financial Services
Customer records, contracts, KYC documents, material non-public information stays in the bank's environment.
Government & Defense
Classified, CUI, or sensitive-but-unclassified workloads. Often requires GovCloud or air-gapped deployment.
Publishing & Legal
Manuscripts, contracts, royalty data, privileged communications, M&A diligence. IP and client work that stays private.
Any audited company
SOC 2, ISO 27001, customer data agreements, if you've contractually committed to keeping data scoped, you can't send it to a SaaS LLM.
Also deployed across Education (FERPA), Pharma & Life Sciences, and Critical Infrastructure (energy / utilities / telecom). See industries →
One firm, one approach
Same agents. Private deployment.
Private AI isn't a separate product, it's how we deploy for clients who need it. Every service engagement can be delivered inside your environment, on the model layer that fits your data-handling policy.