— ALL AI STACK REPORTS
Stacks using Arize Phoenix
Community-built AI stacks that include Arize Phoenix.
AI Algorithmic Trading System with Real-Time Analysis
Scalable stack for building AI-powered trading agents that analyze market data in real-time, execute trades, and adapt strategies using LLMs with low-latency inference and persistent memory.
AI Anomaly Detection for APM & Alerting
Real-time anomaly detection system for application performance monitoring with ML-powered alerting. Combines observability collection, time-series analysis, and intelligent alerting for startup-scale deployments.
AI HR Onboarding Assistant
Automates employee onboarding workflows with multi-agent orchestration, document processing, and task automation for startups scaling from 10 to 1000+ employees.
AI Mental Health Chatbot & Triage Platform
Scalable conversational AI system for patient intake, symptom assessment, and therapy session support with safety guardrails and observability.
AI Search & Autocomplete Stack for SaaS
Production-ready vector search with embeddings, semantic retrieval, and real-time autocomplete for SaaS products. Scales from startup to enterprise with managed infrastructure.
AI-Powered Restaurant with Intelligent Waiters
Полный стек для создания ресторана с ИИ-официантами: голосовые агенты для приёма заказов, управление рабочими процессами, интеграция с системами и мониторинг.
AI Video Content Moderation at Scale
End-to-end video moderation pipeline detecting harmful content with scalable inference, async processing, and observability for startup operations.
AI Infrastructure Cost Optimization Stack
Monitor LLM usage patterns, auto-scale compute resources, and optimize costs through intelligent workload distribution and serverless inference.
AI Essay Grading & Feedback System
Automated essay evaluation with LLM-powered feedback, evaluation metrics, and scalable document processing for educational institutions.
Context Retention & Drift Detection Agent
Multi-agent system that maintains accurate context streams, detects context drift, and alerts users when conversation topics diverge to prevent inaccurate results.