Sparkling Neuronics Labs

Sparkling Neuronics Labs is a principal-led, vendor-independent advisory practice working across AI assessment, strategy, architecture, modernization, and technical due diligence. We help CTOs, founders, and investors make high-stakes technical decisions: whether to trust an architecture, modernize or replace a legacy estate, move a prototype to production, validate an AI claim, or back an acquisition target.

The practice is AI-native. We run assessments through purpose-built, AI-accelerated delivery flows rather than manual review or off-the-shelf scanners, so the work is faster and goes deeper: more of the codebase actually examined, risks and patterns surfaced that a sampled review would miss, and a decision in days rather than quarters. The principal does not just use these tools; he builds them (agent orchestration, RAG over vector and graph stores, MCP and A2A integration), which is what makes the analysis sharper.

This is AI on both sides. As a method, the AI-native approach assesses any software on any stack: architecture, technical debt, modernization risk, and code quality. As a subject, the same principal is an AI architect who evaluates AI systems specifically: AI architecture, claims validation, production readiness, and software built with Cursor, Claude Code, Copilot, Lovable, Bolt, or Replit.

The principal brings 25+ years in software, including 15+ years architecting enterprise transformations across global consulting and technology firms, most recently in a senior AI leadership role, much of it in regulated, high-compliance environments. Big-bang core rewrites, monolith decoupling, multi-system consolidation, and prototype-to-production are the day job, not theory.

Engagements are principal-led and fixed-scope, and produce decision-grade output: boundary maps, architecture decision records, target-state architecture, migration roadmaps, risk registers, confidence-banded cost, time and risk models, and recommendations a CTO, investor, or board can sign.