AI Companion App

Building the future of personalized AI companions with modular, scalable architecture

Web-based (PWA) Multi-Agent Pluggable
View Architecture → Infrastructure →

Implementation Tasks

Current phase: MVP Development

All Tasks Complete (100%)

1

🏗️ Architecture & Tech Stack

Define system architecture, select platform, LLM providers, and agent architecture.

  • Platform: Web-based (PWA)
  • LLM: Multi-provider (OpenAI primary)
  • Agents: Multi-agent system
  • Design: Plugin-based modular
✓ Completed
2

☁️ Infrastructure Setup

Configure cloud backend and deployment infrastructure.

  • AWS cloud configuration (Terraform)
  • Kubernetes orchestration (manifests)
  • CI/CD pipelines (GitHub Actions)
View Infrastructure → ✓ Completed
3

💬 Conversational Interface

Build chat UI with streaming and real-time features.

  • Chat UI with streaming
  • Typing indicators
  • Session management
Try Chat → ✓ Completed
4

🧠 Memory & Context

Implement memory system with vector database.

  • Short-term memory
  • Long-term memory (vector DB)
  • RAG pipeline
View Memory → ✓ Completed
5

🔧 Tool/Action System

Build extensible tool framework.

  • Function calling
  • Tool schema definition
  • Guardrails
View Tools → ✓ Completed
6

👤 User Profiling

Build user preference learning system.

  • Preference extraction
  • User model
  • Feedback collection
View Profile → ✓ Completed
7

📈 Feedback Loops

Implement continuous improvement system.

  • LLM-as-judge evaluation
  • RLHF pipeline
  • Optimization system
View Feedback → ✓ Completed
8

🛡️ Safety Guardrails

Add content policy and privacy enforcement.

  • Content filtering
  • PII detection
  • Action approvals
View Safety → ✓ Completed
9

🔐 Privacy Controls

Implement user privacy features.

  • Data retention
  • Export/deletion
  • E2E encryption
View Privacy → ✓ Completed
10

📱 Mobile Implementation

Build native/cross-platform mobile app.

  • React Native app
  • On-device inference
  • Voice pipeline
View Mobile App → ✓ Completed
11

🖼️ Multi-Modal Support

Add image, voice, and video capabilities.

  • Image understanding
  • Voice conversation
  • Video integration
View Multi-Modal → ✓ Completed
12

📊 Monitoring System

Implement observability and logging.

  • LLM observability (LangSmith, Arize, WhyLabs)
  • Token tracking & cost monitoring
  • Performance dashboards & alerts
View Dashboard → ✓ Completed
13

📉 Analytics

Build analytics pipeline for insights.

  • Engagement metrics
  • Quality monitoring
  • A/B testing
View Analytics → ✓ Completed

Implementation Timeline