ThinkerWave
Product · flagship
AI for your hardest problems: high-stakes decisions where being wrong is expensive. It works a problem from every angle and argues against its own answer, then shows its work. Runs locally, available by invitation.
Founder, Thinkerwave AITech · Sovereign AI · AI Agents
Vikas Goel
Founder of Thinkerwave AITech, building autonomous, self-evolving AI agents. 30 years turning AI into measurable business results at enterprise scale.
$20M+
Annual recurring revenue at blackNgreen
5 → 160+
Enterprise customers grown over 13 years
290M+
End-users reached, across 4 continents
50+
Engineers across direct reporting structure
I'm the founder of Thinkerwave AITech Private Limited, an Indian AI company building ThinkerWave (self-evolving AI agents, patent pending), Torbi (AI-powered B2B prospecting), and a creator-intelligence platform.
Before founding Thinkerwave, I spent 30 years in production engineering. As CTO of blackNgreen (2013–2026) I owned far more than the tech: the product, the go-to-market, and the P&L. That's the founder's lens I build with now. AI is only worth building if it moves the business.
Thinkerwave AITech · current work
What I'm building right now
Torbi
Commercial · AI prospecting
AI-powered B2B prospecting. It reads buying signals across the web and matches them against a seller's entire catalog, then drafts the outreach.
Creator Intelligence
Commercial · in build
An influencer-intelligence platform: pricing, fit, and audience signals for the creator economy. AI applied to the messy problem of matching the right creator to the right brand.
Track record
Former · 30 years
Ex-CTO at blackNgreen (290M+ users, $20M+ ARR, 5→160+ customers) and Nexiva (AI voice agents). Led MagicCall to 14M+ downloads. Three Indian patents.
Areas of expertise
30 years shipping production AI at scale
- · Enterprise voice AI, in production at scale
- · AI agents & agentic architecture
- · Self-evolving AI agent research
- · Taking AI from pilot to production
- · AI that drives revenue: recommendation & upsell
- · Build-vs-buy & AI strategy for enterprises
Latest writing
From the blog
6 min read
What an AI Agent Actually Costs in Tokens: A Reproducible Teardown
Most teams blame the model's price for a runaway agent bill. The real driver is re-sent context, and it grows quadratically with the number of steps. Here's a reproducible cost model you can run on your own numbers, and the changes that cut a 10-step agent's input tokens by about 65% without touching the model.
- Token Optimization
- AI Agents
- LLM Cost
6 min read
India's GCCs Have the Agentic-AI Mandate. Most Will Still Miss It.
India's 2,100+ Global Capability Centers finally have the board mandate to lead on agentic AI. 83% are scaling GenAI and 58% are piloting agents. But a GCC is structurally optimized for delivery and cost arbitrage, and agentic AI rewards almost the opposite muscle: owning outcomes, buying instead of building, and running eval and governance in production. This is the operating-model climb from cost center to AI-first, and the gap most GCCs fall into on the way up.
- GCC
- Agentic AI
- India AI
5 min read
Voice AI Agents Hallucinate. In a Regulated Call, That's a Compliance Incident.
A voice AI agent that hallucinates a balance, a policy limit, or a payoff amount hasn't made a cute mistake. In banking, insurance, or healthcare it has created a spoken, recorded, actionable liability. You don't fix that with a better model or a sterner prompt. You fix it with an architecture: retrieve the authoritative record, verify it against policy, then speak or refuse. This is how reliability gets engineered into a regulated voice agent.
- Voice AI
- Conversational AI
- Enterprise AI
Working on something at the AI frontier?
I'm always open to conversations about Voice AI, agent architectures, and enterprise AI deployment. Reach out on LinkedIn or via email.