Austin – April 7, 2026 – Docsie, the AI-powered knowledge orchestration platform, today announced general availability of its on-premise deployment and Bring-Your-Own-Model (BYOM) stack — a complete AI documentation infrastructure that runs entirely on customer-owned infrastructure using customer-controlled language models.
The release addresses a structural problem in enterprise AI adoption. 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 year prior. The bottleneck isn’t model capability. Only 11% of agentic AI use cases have reached production, and the gap is primarily a trust problem: the unwillingness of security-conscious organizations to route sensitive operational data through third-party cloud infrastructure they don’t control.
The organizations most affected are the ones with the most to gain: ERP implementation partners managing SAP, Workday, and Oracle deployments; manufacturing quality teams maintaining ISO-compliant SOPs across global facilities; financial services compliance departments producing regulatory documentation under audit; healthcare organizations generating training materials containing protected health information; and defense contractors operating in ITAR-controlled environments where external network communication is prohibited.
“The enterprise AI problem isn’t capability — it’s control,” said Philippe Trounev, CEO of Docsie. “These organizations 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. They’ve got a Ferrari engine sitting in the garage with no car around it. We built the car.”
The On-Premise AI Orchestration Stack
Docsie’s on-premise deployment provisions a complete AI knowledge platform on customer infrastructure through an automated process, with full feature parity with the cloud version:
Bring-Your-Own-Model Architecture — Organizations connect their own LLM endpoints running Llama, Qwen, DeepSeek, Mistral, or any OpenAI-compatible model on vLLM, Ollama, or Amazon Bedrock. A setup wizard auto-discovers available models and assigns them to 11 distinct AI actions: chat, document OCR, vector embeddings, transcription, image generation, and more. No data leaves the customer’s network at any point.
Autonomous AI Agent Orchestration — A multi-agent system where organizations build domain-specific agents — compliance reviewers, SOP generators, training content converters — that call enterprise APIs (Jira, Salesforce, ServiceNow), reference internal documentation as knowledge sources, and route conversations between specialized agents automatically. No code required.
Content Compliance Scanning — AI-powered analysis of video, audio, and text content against HIPAA, PII, brand, and custom policy frameworks. An interactive timeline viewer lets compliance officers click any flagged violation and jump to that exact moment in a training video — surfacing exposures human review misses, such as a patient name visible on-screen for less than a second.
Air-Gapped Documentation Delivery — Complete offline documentation packages deployable to disconnected networks, factory floor terminals, or field equipment with zero internet dependency. Client-side search runs entirely in the browser. Ships as a Docker container for any Kubernetes cluster.
Enterprise Portal with Full Tenant Isolation — White-labeled, multi-tenant portals with SSO, per-organization vector indexes, and session-level audit trails with remote revocation.
Why This Matters Now
For the majority of IT decision-makers surveyed in Nutanix’s 2026 Enterprise Cloud Index — 80% — data sovereignty is a high priority or a must-include when making infrastructure decisions. A Harvard Business Review Analytic Services study found that mission-critical data often remains in on-premise environments due to sovereignty, security, and compliance requirements — creating a persistent gap between AI ambition and deployment reality.
Docsie’s BYOM architecture ensures all inference runs within the customer’s own infrastructure — no data transits external networks, no model outputs are logged by third parties, and no proprietary content is exposed to vendor AI systems. Most large enterprises already adopt a hybrid model, buying platform components such as foundation models and vector databases then building domain-specific layers internally. Docsie’s on-premise stack is designed to slot into that architecture: bring your models, bring your infrastructure, bring your compliance requirements.
Availability
Docsie’s on-premise deployment with BYOM is available now for enterprise customers. The platform deploys on any Kubernetes cluster via Helm charts. Air-gapped offline documentation packages are available for disconnected environments.
Enterprise deployment consultations: docsie.io/demo
About Docsie
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. Trusted by ERP implementation consultancies, enterprise training teams, and regulated industry organizations worldwide.
Media Contact
Company Name: Docsie Inc.
Contact Person: Philippe Trounev
Email: Send Email
Phone: 4169028771
Address:140 Yonge Street Suite 200
City: Toronto
State: ON
Country: Canada
Website: https://www.docsie.io