THE ARCHITECTURE LAB

AI Systems.
Proven in production.

Six real systems. Real calls answered. Real workflows automated. Real compliance enforced. All currently running at enterprise scale.

Built with OpenAI, Anthropic Claude, Google Gemini, and the Model Context Protocol. Designed to survive security review.

Voice
PropTech leasing + US logistics

Can an AI voice agent really answer business phone calls?

+

Yes. Modern real-time speech models hold natural conversations with sub-second latency and are already qualifying leads, booking appointments, and logging every interaction 24/7.

Knowledge
One of the largest US PropTech platforms

How do RAG chatbots actually reduce enterprise support volume?

+

A grounded RAG system answers routine questions instantly across every audience role, deflects tickets, and only escalates the complex ones — with sentiment detection and perfect handoff.

Agents
Enterprise PropTech + logistics operators

What real business workflows can AI agents run end-to-end?

+

Agents with tool access and human-in-the-loop gates can execute complete revenue and operations flows across voice, chat, CRM, scheduling, and back-office systems.

Compliance
Licensed-professional platforms + ERP environments

How is AI used for continuous regulatory compliance monitoring?

+

AI scans operational data for risk patterns, scores exposure, simulates business impact of violations, and automates continuing-education tracking for licensed professionals.

Integration
Multiple enterprise and growth-stage companies

What is the Model Context Protocol and why does it matter for real AI automation?

+

MCP is the open standard that lets AI models securely read from and act on your actual business systems — CRMs, ERPs, telephony — instead of living in a chat window disconnected from reality.

Adoption
Startups and enterprise engineering organizations

How do serious engineering teams adopt AI coding agents without destroying quality or trust?

+

They pair the agents with AI-ready architecture, explicit review gates, and clear team workflows from day one. The result is measurable acceleration while keeping security and standards intact.

Frequently asked

What kind of AI work do you actually deliver?

End-to-end production systems: real-time voice agents, grounded RAG assistants, multi-agent orchestration, compliance & risk platforms, and Model Context Protocol (MCP) servers that give AI governed access to your real systems of record.

Do these systems pass enterprise security and audit?

Yes. Every deployment described above has gone through enterprise security review, includes human-in-the-loop controls where required, and generates the audit trails buyers demand.

How do you start an engagement?

With the metric you are trying to move — missed calls, ticket volume, compliance exposure, engineering velocity — not with a model. We scope a tight pilot, prove value on real traffic, then expand.

Which models and infrastructure?

OpenAI (GPT-4o, Realtime, Agents SDK), Anthropic Claude, Google Gemini (including Live), LangChain/LangGraph, Twilio/RingCentral, Cloudflare Workers, Azure, Vercel. MCP is our secret weapon for safe system integration.

What would you automate first?

Tell me the calls you’re missing or the workflow eating your team’s week. I’ll tell you the pattern that has already worked in production.