The Founder

Ranganath Eunny.
Platform engineering
built at scale.
In production.

FalconIO is not a product designed by a product manager describing what platform engineers need. It is built by Ranganath Eunny — an engineering leader who has directed the design and delivery of Kubernetes-native platforms across AI/ML, quantum computing, IoT edge, and enterprise infrastructure — on three continents, under real production pressure.

"The tools existed. The integrated, opinionated control plane that made them work as a system — that is what was missing. That is what we built."

Engineering leadership
at the moments that mattered.

These are not job descriptions. They are the moments where scope was ambitious, stakes were real, and the outcome was a production system that held — or a platform that enabled something that had not existed before.

Achievement 01
AI Platform Engineering · US Enterprise Production
Reduced infrastructure provisioning time by 70% across an enterprise AI platform.
Directed the design and delivery of a Kubernetes-native Internal Developer Platform for a US enterprise that collapsed multi-day provisioning cycles to minutes — through Crossplane-based self-service abstractions and OPA policy enforcement applied at the workflow, not the document. Simultaneously architected and delivered AI inference infrastructure — LLM services, document extraction pipelines, risk-adjusted pricing models — as first-class production workloads on Kubernetes with full GitOps delivery and observability. Real SLAs. Real AWS infrastructure. Not a proof of concept.
70% provisioning time reduction US enterprise production IDP + AI infra simultaneously
Achievement 02
Quantum Computing Infrastructure · Novel Compute Class
Led the MLOps platform build for India's first quantum computer — with no prior playbook.
Led a large engineering team building and operating the AI/MLOps platform for hybrid classical-quantum compute environments — a compute class that had no established Kubernetes operational model when the programme began. The work was: architect the IDP for AI and quantum workload provisioning, build Go-based Kubernetes operators for quantum job scheduling, establish the full observability stack, and operate across GCP and on-premises clusters — all while the hardware itself was being commissioned for the first time. Leading a large engineering team through infrastructure design for a compute class with no prior art is a different kind of engineering leadership.
Large engineering team led Novel compute class, no playbook IDP + MLOps + Quantum orchestration
Achievement 03
IoT · AI Edge · Blockchain · Global Brand · US Operations
Architected IoT edge control plane + AI inference + blockchain simultaneously, at fleet scale.
Architected the full-spectrum platform for a global consumer brand's autonomous vending fleet initiative — converging IoT edge fleet management, AI inference at the edge, and blockchain-backed supply chain audit into a single, unified architecture. Designed edge-to-cloud Kubernetes control planes managing deployment and configuration reconciliation across thousands of IoT-class edge nodes via FluxCD GitOps. Integrated Hyperledger Fabric for tamper-proof supply chain audit trails. Delivered Go microservices coordinating real-time AI inference on GPU-accelerated edge hardware. Three infrastructure disciplines running simultaneously, at fleet scale, for a production US operation. This programme is the direct ancestor of FalconIO's IoT feature.
Fleet-scale IoT Edge AI + Blockchain simultaneously US production fleet
Achievement 04
Enterprise Platform Engineering · 50+ Clusters · Portfolio Scale
Operated 50+ production Kubernetes clusters, standardising platform engineering across an enterprise portfolio.
Led platform engineering for enterprise-scale Kubernetes transformation engagements — migrating clients from VM-based infrastructure to resilient, container-native deployments across a portfolio of 50+ Rancher-managed production clusters. Standardised GitOps delivery pipelines across the portfolio, replaced ad-hoc provisioning scripts with tested Pulumi Go automation, and built Go microservices extending ERP capabilities with high-throughput gRPC interfaces and integrated observability. The operational discipline of managing 50+ heterogeneous clusters across enterprise environments is precisely what informed FalconIO's approach to multi-cluster topology management and drift detection.
50+ production clusters Enterprise portfolio scale GitOps + IaC standardisation
Achievement 05
Financial Risk Systems · Global Financial Institutions · Zero Tolerance for Failure
Built trading and risk infrastructure where state errors are denominated in market exposure.

Early career: built and operated quantitative trading strategy platforms and financial risk technology for investment banks and NBFCs — C++ systems, statistical arbitrage strategies, Bloomberg API integration, and risk model infrastructure operated under the strictest correctness requirements in any engineering domain. The lesson from this period is the one that runs through every FalconIO design decision: in systems where the cost of failure is immediate and measurable, correctness is not a feature — it is the foundation. That standard, applied to platform engineering, is what BC/DR as code and topology-aware incident management look like in practice.

Production trading systems Global financial institutions Zero tolerance for state errors
The financial risk engineering background is not a footnote. It is the origin of the conviction that infrastructure correctness — not just availability — is the standard FalconIO is built to meet.

The gap was not in
individual tools.
It was in the integrated
operating model.

Every engineer who has operated Kubernetes at scale knows the components — Crossplane, Pulumi, FluxCD, OTel, VictoriaMetrics, ClickHouse, Cilium, KEDA, Karpenter. The tooling is excellent.

What does not exist is the opinionated, integrated platform that makes them operate as a system — where infra state, observability telemetry, resilience declarations, and incident context share a topology graph and a common operating model.

That integration — with a point of view, built for enterprises where downtime has a real cost — is FalconIO. It exists because the gaps were encountered in production, repeatedly, at scale, and the founder had enough accumulated experience across enough different infrastructure classes to know exactly what the integrated version should look like.

FalconIO is in early build. We are in active conversations with platform and SRE teams at operationally critical enterprises in the United States and Europe. If you recognise the problems on this site, we want to speak with you.
Connect With the Founder →
22+
Years of infrastructure engineering leadership
50+
Kubernetes clusters in production experience
3
Continents — US, Europe, India — platforms operated
4
Infrastructure disciplines: Cloud · AI/ML · IoT · Risk Systems
FalconIO.AI
Chennai, India · Serving US & European enterprise markets