Private & Self-Hosted AI
44% of enterprises cite data privacy as their number-one barrier to AI adoption. For healthcare, legal, financial services, and government, that is not a preference. It is a compliance requirement.
We build AI systems that run entirely within your infrastructure. No third-party data exposure. No API calls leaving your environment. Full audit trail. We have shipped in regulated environments that most AI agencies will not touch.
What We Build
Air-Gapped Deployments
- Complete AI systems with zero external API calls
- Local model inference via Ollama (Llama 3, Mistral, and others)
- On-premise vector stores for RAG without cloud exposure
- Isolated network configurations with no outbound AI data
Private Cloud Endpoints
- AWS Bedrock: Claude and other models within your AWS environment
- Azure OpenAI: GPT-4 within your Azure tenant, no Microsoft data access
- Custom VPC configurations with strict egress controls
Self-Hosted Automation
- n8n self-hosted on your infrastructure
- All workflow data processed and stored within your environment
- No Zapier, no Make, no third-party data handling
Industries Where This Is Required
Healthcare: HIPAA compliance requires that patient data does not leave controlled environments. We build AI systems for medical practices, billing operations, and clinical documentation that operate within those constraints.
Legal: Client privilege and bar association requirements around data handling. We have built AI tools for law firms where document ingestion and analysis happens entirely on-premise.
Financial services: SOC 2, PCI, and institutional data governance requirements. AI systems built for financial workflows where data sovereignty is non-negotiable.
Government and regulated enterprise: Compliance frameworks that prohibit cloud AI services. We scope and build for these environments specifically.
What This Means in Practice
Self-hosted AI is not slower or less capable than cloud AI. Modern open-source models running on properly sized hardware perform comparably to commercial APIs for most business use cases. For some tasks they outperform them when fine-tuned on domain-specific data.
We will give you an honest assessment of what self-hosted achieves versus what requires a private cloud endpoint, and where the compliance line actually is for your specific framework.
Stack
- Local Inference: Ollama (Llama 3.1, Mistral, Gemma, and others)
- Private Cloud: AWS Bedrock, Azure OpenAI
- Automation: n8n (self-hosted)
- Vector Stores: Weaviate, Chroma (self-hosted)
- Infra: On-premise hardware, private VPS, or isolated cloud VPC
- Security: Network isolation, audit logging, access controls