Co-Founder · Adaptive AI Data Intelligence
NeuroNova: adaptive AI data intelligence.
NeuroNova is an Adaptive AI Data Intelligence startup building toward a persistent AI data analyst that progressively understands each company's unique data language, context, and analytical workflows. As Co-Founder, I work across product and AI architecture while helping refine the MVP through real-world validation.
The problem
Data is abundant. Reliable understanding still takes work.
Companies have enormous amounts of data, but turning that data into reliable understanding and decisions still requires significant manual work.
The product
A conversational analytics workflow.
The platform is being designed to make this workflow conversational and intelligent. Companies connect their structured data; NeuroNova profiles and understands the underlying schema; users ask questions in natural language; and the system generates and validates SQL, performs analysis, creates visualizations, and surfaces insights.
Company Intelligence
Beyond NL2SQL or another database chat interface.
Every organization has its own data language: terminology, business definitions, relationships, rules, analytical patterns, historical queries, and institutional knowledge.
NeuroNova is being built to progressively understand that company-specific context and develop Company Intelligence on top of general AI and domain intelligence.
Long-term vision
A persistent, company-aware analytical layer.
The long-term vision is a persistent AI data analyst and organizational intelligence layer that becomes more useful through validated feedback, corrections, recurring workflows, and accumulated company context.
Company-specific intelligence is intended to remain isolated and private.
My role
Co-Founder across product and AI architecture.
As Co-Founder, I contribute across product and AI architecture, helping shape how NeuroNova understands company-specific context, memory, domain intelligence, and feedback.
I also contribute to refining the MVP and the core analytics workflow based on real-world use.
Current MVP
An iterative approach to the intelligence layers that matter.
The current MVP focuses on the core analytics workflow while the team validates what intelligence layers and workflows actually matter.
The approach is deliberately iterative rather than assuming the long-term architecture is already solved.
Current validation
Learning from the people and companies closest to the work.
- Conversations with 50+ data analysts.
- Discussions with experienced data professionals.
- Selected for the Sarvam Startup Program.
- MVP validation with data-rich MSMEs, MSBs, and lower-mid-market companies.
Validation approach
A path for proving the right use cases.
Free pilots → validated use cases → paid SaaS → enterprise expansion