AI Agents & Conversational Interfaces

AgentFloor visualizes Claude Code agents as pixel RPG characters executing tasks in a real-time office dashboard, solving the problem of monitoring multi-agent workflows at a glance. Built with Flask SSE streaming, vanilla Canvas rendering, and Python stdlib hooks that intercept agent lifecycle events, it displays live terminal output and agent state without external dependencies. Deployed on a VPS and wired to Claude Code via hook scripts, the system currently tracks concurrent agent activity with sub-second latency updates.

BarPhoneAgent automates B2B sales outreach for bar owners by scraping Yelp leads, qualifying them against competitor databases, and sending personalized SMS via Twilio with Claude-powered reply handling. Built with Python, SQLite, and multi-API orchestration (Yelp, SerpAPI, Twilio, Anthropic), it processes location-based lead batches with built-in rate limiting and dry-run safety. Successfully deployed with live SMS campaigns reaching 50+ qualified leads per location.

Jarvis is a screen-aware voice AI assistant for macOS that combines real-time speech-to-text (Deepgram), Claude vision/conversation models, and 18 desktop control tools into a unified Pipecat pipeline. It monitors the active screen, filters sensitive data (passwords, 2FA), and responds conversationally while executing system tasks-deployed as a persistent LaunchAgent with wake-word detection and self-modifying capabilities. Built with Python 3.13, Anthropic APIs, and ElevenLabs TTS; runs continuously at login with comprehensive logging.

MayaSA routes SMS and iMessage queries to Claude, which delivers hyperlocal San Antonio business recommendations enriched with real-time weather, event calendars, and persistent user memory. Built on FastAPI with Supabase persistence, it includes a loyalty system, business-owner portal, and automated weekly outreach-deployed on a VPS with live production traffic. The architecture prioritizes low-latency responses and conversation continuity across multiple messaging channels.

ResearchAgent decomposes complex research queries into atomic sub-questions, searches 8+ sources in parallel (Exa, Tavily, Brave, arXiv, Reddit, YouTube, etc.), and synthesizes credibility-scored reports using Claude with extended thinking. Handles business intelligence, academic research, and social sentiment at scale via async orchestration-outputs structured JSON reports with gap analysis and timelines.

Thirstistant automates mail and email triage for a solo user by extracting structured data via dual-LLM orchestration (Gemini Flash → Claude Sonnet), then routing extracted facts through iMessage approval gates to Paperless-ngx and calendar systems. The security model enforces strict separation: untrusted content stays quarantined in the reader LLM, credentials never reach any AI, and auto-login runs sandboxed behind biometric gates-eliminating the trust debt of most personal AI agents. Deployed self-hosted with rate-limiting and approval fatigue mitigations.