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LIVEAI Experience / intelligence

Private AI Workspace

One private workspace for models, knowledge, tools, search, voice and collaborative AI.

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Live workload cutawayArchitecture in context
Private AI Workspace
FoundationAICORTEX Core PlatformConnectedUniversal AI GatewayConnectedKnowledge Hub & RAGConnectedPersistent AI Memory
Signal path active8 deployment units

What this replaces

Users bounce between separate AI subscriptions for chat, search, files, coding, images, voice and prompts, fragmenting data and governance.

What your team gains

A single authenticated AI workspace that can talk to multiple models and attach organizational knowledge, tools and controlled external services.

What is inside the blueprint

Multi-model and side-by-side chat
Files and image uploads
Web search with source retrieval
Browser/Python code execution options
Cross-conversation memory
Voice input/output and voice/video workflows
Image generation/edit integrations
Automations and recurring prompts
Structured task management
Knowledge bases with vector or full-context modes
Hybrid BM25 + vector retrieval with reranking
Agentic document retrieval
Model presets with instructions, tools and knowledge
Notes and AI-assisted editing
Shared channels with model tagging
MCP, OpenAPI, Python tools, pipelines, skills and prompts
RBAC, groups, per-resource permissions, SSO/OIDC/LDAP, SCIM and API keys
Usage analytics, model evaluation/A-B testing, banners and webhooks
OpenTelemetry and horizontal scaling options

How it fits the platform

Authentication -> chat UI -> AI gateway/local model endpoints + web search + knowledge/vector store + MCP/OpenAPI tools + speech/image services.

Included services

Chat UI, AI Gateway, Authentication, Web search, Relational database, Vector store, Speech model, Hosted speech service

Platform requirements
  • AICORTEX Core PlatformThe workspace's containers, routing, database and boot protection are provided by the Core substrate.

From prerequisites to operation

Prerequisites
  1. AICORTEX Core
  2. At least one configured model endpoint/provider
  3. User identity strategy
  4. Optional knowledge collections and tool servers
Deployment
  1. Deploy the chat UI against the relational database and vector store
  2. Connect the AI gateway and local model endpoints
  3. Integrate authentication
  4. Configure web search and speech
  5. Register tools/MCP/OpenAPI endpoints
  6. Define roles/groups and workspace defaults
Configuration
  1. Available models and model presets
  2. Knowledge and retrieval defaults
  3. Web search policies
  4. Voice/image providers
  5. Role/group access
  6. API keys and automation permissions
  7. Analytics and evaluation settings
Operations
  1. User lifecycle
  2. Database backup
  3. Provider health
  4. Extension compatibility
  5. Usage/cost monitoring
  6. Permission review

What this unlocks with other layers

Private AI Workspace + Universal AI Gateway

Private AI + Model Freedom

Users get one interface while builders can change providers underneath it without changing the experience.

Private AI Workspace + Voice & Multimodal Experience + Real-Time & Mobile Experiences

Multi-Channel Intelligence

The intelligence layer is reusable across interfaces rather than tied to one chat surface.

Technology behind this capability

Chat UIAI GatewayWeb searchSpeech modelHosted speech serviceVector storeAuthentication
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AI Control Plane

Universal AI Gateway

One governed API in front of cloud and local AI providers.

AI Control Plane
Knowledge

Knowledge Hub & RAG

Turn private documents and structured data into grounded, searchable AI context.

Knowledge
Knowledge

Persistent AI Memory

Let agents recall relevant history across sessions instead of starting over.

Knowledge
Agents

MCP Agent Hub

Give AI modular tools and data connectors without rebuilding the model layer.

Agents