About Us

Customer operations infrastructure for the age of real-time AI.

One system for lead capture, support, voice, chat, knowledge, and human handover. Designed for businesses where timing, context, and accuracy determine outcomes.

Our Thesis

The future belongs to systems that listen, reason, remember, and escalate in real time.

The old model was fragmented by default. One tool for chat, another for calls, another for documents. We think that approach is structurally weak. Modern customer operations need four capabilities working together.

Voice AI

WebRTC-based real-time voice with low-latency transport, natural turn-taking, and graceful human handoff.

AI Memory

Context that accumulates across interactions, detecting gaps, improving over time, and becoming business-faithful.

Engagement Intelligence

Recognizes buying intent from behavior signals and routes conversations while interest is still live.

Knowledgebase Indexing

Organizes, retrieves, and keeps business knowledge aligned with reality. Not static file storage.

Why we built this

Speed and context determine whether conversations convert or disappear.

Businesses have tools that capture leads, but those tools do not help them act at the moment of highest intent. Founders get notified too late, support sits in queues without context, and promising conversations get lost between automation and human follow-up.

What's different

Knowledge as a continuous learning loop, not a one-time upload.

Every meaningful interaction improves the system. Calls, chats, and support threads expose knowledge gaps, surface outdated information, and create raw material for stronger future responses. The system grows into the operating reality of the business over time.

Research Foundation

Always backed by state-of-the-art research.

Our systems are built on the latest advances in voice-to-voice AI pipelines, agentic memory architectures, and retrieval-augmented generation. Not demos. Production-grade implementations of frontier research.

Voice-to-Voice AI

Low-latency streaming pipelines with natural turn-taking, informed by research on end-to-end speech architectures and real-time voice agent design.

Agentic Memory

Persistent, structured memory that accumulates across interactions. Agents that detect knowledge gaps and improve with every conversation.

RAG Pipelines

Advanced retrieval-augmented generation with active retrieval, context compression, and evolving knowledge indices for accurate, grounded responses.

Built on  [1]  [2]  [3]  [4]  [5]  [6]  [7]

Human Handover

Built for human handover, not human replacement.

Zinc is designed for dynamic human takeover. The AI transfers at its scope boundary, customers can request a human directly, and agents join live conversations in real time. Never a dead-end.

Efficiency as Philosophy

Zero-waste discipline from day one.

Direct engineering ownership, tight feedback loops, and a bias toward systems that do more with less. Efficient systems force clarity about what actually matters. That philosophy shapes both our product and our architecture.

Looking Ahead

Infrastructure for company memory and customer operations.

Our long-term direction is broader than a chatbot or call tool. We see Zinc as a system that helps businesses capture knowledge, understand intent, coordinate responses, and continuously improve.

Unified data ingestion

Stronger business context from every source.

Interaction-driven learning

Richer knowledge from real conversations.

Companion workflows

Fast response on the go, anywhere.

Agentic capabilities

Backend tasks with investigation, context, and human approval.

Customer operations should get smarter with every interaction.

Real-time voice AI, evolving memory, engagement intelligence, and seamless human takeover. All inside one efficient system.