Thinking out
loud.
Engineering notes, product decisions, and AI insights from the ThinkMindLabs team. We write about what we build and why we build it.
Why we built OpenVoce.ai — and why it deploys in under 5 minutes
Most AI chatbot builders take weeks to configure and months to tune. We believed that was wrong. Here is how we engineered OpenVoce to be live in under 5 minutes without compromising on quality.
Building sovereign AI: why your enterprise data must never leave your infrastructure
As AI adoption accelerates, data sovereignty is becoming the defining enterprise concern. We explain our architecture and why Pravakta.ai was designed from day one to run entirely on customer-owned infrastructure.
Pravakta.ai: how we trained 100+ voice agents before launch
Pre-trained agents are our moat. Before Pravakta.ai shipped, we trained over 100 domain-specific voice agents across healthcare, retail, banking and customer service. This is how.
The future of retail is conversational — TalkBuy and the end of the search bar
E-commerce search is broken. Customers know what they want but can't always describe it in keywords. Conversational AI changes this entirely. The TalkBuy thesis.
WebRTC vs SIP for AI voice agents: what we learned building Pravakta
We support both WebRTC and SIP in Pravakta.ai. Each has tradeoffs for enterprise deployments. After months of production data, here is what we recommend and why.
AgentForDoc.ai: building a clinical AI agent that listens like a human coordinator
Clinical documentation is one of the most expensive and error-prone processes in healthcare. We built an AI agent that listens, infers and summarises — in real time, inside your HIS.
Build with AI, Build for AI, Build to integrate — the ThinkMindLabs mantra
Our three-word engineering philosophy sounds simple. But it shapes every product decision we make — from architecture to UX to pricing. Here is what it actually means in practice.
How we use AI Workers to ship products as a team of 5
We are 5 humans. But we operate like a team of 100+. Our AI Workers handle code generation, testing, content, QA and deployment pipelines. This is our actual workflow.
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