About
Product Engineering
Zeoxia is an intentionally small engineering studio building complex technology systems — from cloud platforms and data infrastructure to privacy-aware AI. The focus is simple: systems that scale reliably and meet real operational constraints.
We embed with founding teams and engineering leaders navigating hard technical transitions — first production deployments, legacy modernisation, core IP builds, or hardening a platform for its next phase.
Approach
How Zeoxia works
Two decades of systems engineering experience combined with AI-augmented development workflows — delivering depth traditionally requiring larger teams.
Engagements focus on solving real system challenges — architecture, platform design, and production reliability — not advisory decks.
Architecture before acceleration
Every engagement starts with understanding system boundaries, failure modes, and growth path. Moving fast on a weak foundation creates debt that compounds.
Production is the only proof
A system works when it runs in production, under real load, handling real edge cases, with real monitoring. Demos and POCs don't count.
Systems outlast engagements
Documented decisions, operational runbooks, clean handover. When the engagement ends, your team maintains and extends everything. No lock-in.
Infrastructure over hype
Whether it's AI, cloud migration, or platform engineering — the hard part is rarely the tool. It's the data pipeline, governance, deployment strategy, and what happens when things go wrong.
Founder
Krunal Sabnis — engineer and product builder with two decades of experience architecting and scaling complex systems. From enterprise platforms and cloud-native infrastructure to IoT systems handling millions of devices and AI-driven products.
Has led engineering across zero-to-one builds, high-growth scaling, acquisition integrations, and long-term platform operations. That range of experience shaped a simple belief: complex systems should be designed for real-world operation from day one.
Labs
Labs and products
Some work begins in the lab — exploring edge AI, local-first architectures, and production infrastructure patterns. When ideas mature, they evolve into solutions or products.
Neurelay
AI agent governance platform for MCP tool access control. Policy-driven management of which agents can use which tools, under whose authority. Born from production experience with AI systems that needed infrastructure, not just models.
neurelay.ai ↗ All labs →