Marketplace / Blueprint 16
LIVE EXAMPLEApplications / interfaces

Real-Time & Mobile Experiences

Use the same AI platform as a backend for live geospatial, charting and mobile experiences.

Review my build
Working vertical examples (AIS relay, WorldView, Atlas Charts, Journey Tracker) run in the census; the reusable blueprint abstracts them. The Expo mobile dev environment is intentionally offline by choice.

Interactive platform map

Architecture in context

The focused blueprint, its required foundation, and declared recommendations.

Core Selected Automatic Required path
Blueprint 16 / Applications

Real-Time & Mobile Experiences

Use the same AI platform as a backend for live geospatial, charting and mobile experiences.

2 vCPU4 GB RAM8 services
01 / Problem

What this replaces

AI capabilities are often trapped inside chat, while real business workflows need live data streams and purpose-built web/mobile interfaces.

02 / Outcome

What your team gains

Reusable platform APIs can power real-time visual applications and universal mobile clients without rebuilding identity, AI, knowledge or observability.

03 / Capability

What is inside the blueprint

Persistent WebSocket data ingestion
Normalized live APIs
3D/geospatial visualization
Trading/operational chart rendering
Timeline interfaces backed by graph context
Static web experiences via nginx
Expo universal Android/iOS/web development
Expo file-based routing and native SDK ecosystem
EAS Build/Submit/Update/Hosting/Workflows options
Internal distribution and app-store build pipelines
Shared Authentik/LiteLLM/AICORTEX backend APIs
04 / Architecture

How it fits the platform

Live feeds and platform APIs -> backend relay/services -> web/3D/chart/mobile frontends -> same identity, AI gateway, knowledge and operations layers.

Included services

ais-relay, worldview-dev (production hardening required), atlas-charts, journey-tracker, nginx, expo-dev (down by choice), Traefik, Authentik, platform APIs

Platform requirements
05 / Delivery

From prerequisites to operation

Prerequisites
  1. Authorized data feed or app use case
  2. Frontend/mobile codebase
  3. Production API/auth design
Deployment
  1. Normalize backend API
  2. Protect routes with platform identity
  3. Build web/mobile interface
  4. Use Expo/EAS or self-hosted build path
  5. Instrument telemetry
Configuration
  1. Feed credentials
  2. Refresh rates
  3. Client feature flags
  4. Auth flows
  5. API endpoints
  6. Build profiles
Operations
  1. Feed resiliency
  2. Frontend production hardening
  3. App release lifecycle
  4. API compatibility
  5. Client security
06 / Combinations

What this unlocks with other layers

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.

07 / Technology

Technology behind this capability

AuthentikRUNNING - server + worker + DB + RedisTraefikRUNNING - only ingress pathnginxRUNNING in frontend and static sitesExpo / React Nativeexpo-dev DOWN BY CHOICEais-relayAICORTEX nativeworldview-devAICORTEX nativeatlas-chartsAICORTEX nativejourney-trackerAICORTEX native