Connect
Applications, agents, internal systems, and knowledge sources connect through one enterprise AI gateway.
EntAIFab
Enterprise AI Fabric
A secure AI orchestration layer for connecting enterprise applications, AI models, knowledge, and agents under one governed platform.
Executive Summary
EntAIFab helps organizations move from scattered AI usage to managed AI operations.
The platform sits between enterprise systems and AI providers. Instead of every application connecting directly to a different model, EntAIFab provides a shared layer for access, routing, masking, governance, audit, and cost visibility.
Why It Matters
Common enterprise AI risks
As AI adoption grows, business units can quickly create disconnected tools, duplicated integrations, and unmanaged data exposure.
- Different teams using different AI providers without a single policy layer
- Sensitive business data entering AI tools without consistent masking
- API keys, prompts, and model usage becoming hard to control
- AI spend spread across providers, teams, and projects
- Compliance teams lacking a reliable audit trail for AI activity
- Applications being tied too tightly to one AI vendor
How It Works
Four operating layers
EntAIFab can be understood as a practical operating model for enterprise AI: connect the work, protect the data, route the models, and observe the activity.
Protect
Sensitive data can be detected, masked, and governed before a request is sent to an AI model.
Route
Requests can be directed across providers such as OpenAI, Azure OpenAI, Gemini, Claude, Ollama, DeepSeek, and future models.
Observe
Usage, audit history, and cost signals are centralized so leaders can review AI activity with context.
Where It Fits
Use cases for enterprise teams
Enterprise AI gateway
Create one controlled access point for AI requests across business applications and internal tools.
Governed AI adoption
Let teams experiment and build with approved providers while IT keeps policies consistent.
Secure data handling
Reduce the risk of confidential data, credentials, or personal information being sent to external models.
Cost and usage visibility
Understand which teams, apps, providers, and models are driving AI consumption.
Business Outcome
AI adoption with more control and less vendor dependency
By standardizing AI access through EntAIFab, organizations can reduce exposed keys, improve governance, mask sensitive data, monitor costs, and keep the freedom to use multiple AI providers as needs change.