On-Premise AI Stack Targets Regulated Industries
AI knowledge management vendor Docsie has released a fully on-premise platform that runs entirely on customer-owned hardware and customer-controlled language models. The company says it is responding to a growing unwillingness among regulated enterprises to route sensitive data through third-party cloud infrastructure.
The platform - branded as a Bring-Your-Own-Model (BYOM) stack - connects existing large language model (LLM) endpoints, including Llama, Qwen, DeepSeek, Mistral, and any OpenAI-compatible model, to document management and compliance workflows. Docsie says no data leaves the customer’s network at any point.
The timing reflects a widening gap between AI investment and AI deployment. According to Info-Tech Research Group’s AI Trends 2026 report. 72% of global IT leaders now list data sovereignty and regulatory compliance as their top AI-related challenge - up from 49% the previous year.
A separate Nutanix 2026 Enterprise Cloud Index survey found 80% of respondents consider data sovereignty a high priority when making infrastructure decisions.
The platform targets organisations in financial services, healthcare, manufacturing, defence contracting, and ERP implementation - sectors where regulatory frameworks routinely prohibit sensitive data from transiting external networks.
“The enterprise AI problem isn’t capability - it’s control,” said Philippe Trounev, CEO of Docsie.
“These organisations have bought GPUs, they’re running models internally, they have vLLM or Bedrock deployed - but they have no way to connect that inference capacity to their actual knowledge management workflows.”
A content compliance scanning module analyses video, audio, and text against personally identifiable information (PII), brand, and custom policy frameworks. Docsie says an interactive timeline viewer allows compliance officers to click flagged violations and jump to the corresponding moment in training video - including content visible on screen for less than a second.
An air-gapped documentation delivery function packages complete offline documentation sets deployable to disconnected networks, factory floor terminals, or field equipment with no internet dependency. The package ships as a Docker container for any Kubernetes cluster.
A multi-agent orchestration layer allows organisations to build domain-specific AI agents - described in release materials as compliance reviewers, standard operating procedure (SOP) generators, and training content converters - that connect to enterprise systems including Jira, Salesforce, and ServiceNow. Docsie says no code is required to configure these agents.
The platform includes a multi-tenant enterprise portal with single sign-on (SSO), per-organisation vector indexes, and session-level audit trails with remote revocation - features relevant to organisations managing access governance across multiple business units or client environments.
Docsie is an AI-powered knowledge orchestration platform that converts training videos, PDFs, and existing content into structured knowledge bases, then delivers them as branded portals with AI chat, compliance scanning, and learning management.