We design, deploy, and operate production Kubernetes β classical workloads or GPU-powered AI β and staff the engineering teams who keep it all running. Built for founders and platform leads who need to ship, not just strategize.
From cluster architecture to day-two operations, we deliver the pieces most teams don't have the bandwidth to build themselves.
Production clusters with sensible defaults β Helm, service mesh, observability, autoscaling, and cost controls baked in. Multi-region ready when you need it.
Delivery pipelines that ship safely and often. GitHub Actions, ArgoCD, progressive rollouts, and the policy guardrails to sleep through a 3am deploy.
Vetted SRE, DevOps, and platform engineers β hired, onboarded, and managed by us. You get capacity without the 90-day hiring cycle.
Lift-and-shift, replatforming, or greenfield builds on AWS, GCP, or Azure β with the IaC, IAM, and FinOps foundations that won't bite back later.
We operate the unsexy part of AI β the GPU clusters, the RAG pipelines, the eval harnesses, and the on-call runbooks that keep models answering correctly at 3am.
Self-hosted and hybrid LLM deployments with autoscaling, request shaping, quantization, and full observability β vLLM, TGI, or Triton under the hood.
Production retrieval systems with vector DBs, re-ranking, caching, and evals. We wire it in, instrument it, and leave you with a system you can actually improve.
Kubernetes GPU clusters that schedule well, share fairly, and don't melt your budget. A100/H100, spot, MIG partitioning, and the operator work no one wants to do.
Model monitoring, fallback chains, prompt regression tests, red-team hooks, and a human-readable runbook. On-call coverage when the model starts misbehaving.
Representative engagements across fintech, healthcare SaaS, and AI startups. Names omitted under NDA.
Re-architected a monolithic ECS workload onto EKS with spot-backed node pools and right-sized requests β cutting monthly cloud spend by ~$48k while doubling request throughput.
Stood up a HIPAA-aligned GitOps platform from scratch β cluster, delivery pipeline, observability, and runbooks β in fourteen working days. First production deploy in week three.
Scaled a GPU inference platform from a single-region prototype to three regions with autoscaling on demand β tripling usable capacity without increasing baseline cost.
Pick an entry point that matches where you are. Every engagement comes with a fixed scope and a named engineering lead.
A two-week deep-dive into your current stack with a written remediation plan and a prioritized roadmap.
We run your Kubernetes or GPU platform end to end β clusters, pipelines, observability, on-call. You ship code.
Vetted DevOps, SRE, and backend engineers embedded in your team. Flexible scope, no long lock-ins.
We've run production Kubernetes at companies from pre-seed to public. Every recommendation comes with a PR, not a slide.
No open-ended T&M contracts. You know what you're paying for, when it ships, and what "done" looks like.
We don't dump architecture diagrams and walk away. We stay on-call through rollout and own day-two until your team is ready.
Our international engineering network gives you senior capacity at rates that work β without the usual staff-aug mess.
Cronexa Ventures, LLC is a Tennessee-based infrastructure consultancy. We help growing companies ship reliable software β and AI β without the overhead of a full in-house platform team.
We work best with founders, platform leads, and engineering managers who want a partner that ships β someone who will write the Terraform, run the postmortem, and keep the Grafana dashboard green.
Short, practical pieces on Kubernetes, AI infrastructure, and scaling engineering teams. No listicles.
Resource requests, pod disruption budgets, probe timeouts, and topology spread. A short walkthrough of why the out-of-the-box values bite in production.
Read the postHigh GPU utilization isn't the same as doing useful work. A practical take on the metrics that matter when you're running LLM inference at scale.
Read the postWhy most external engineering engagements stall β and the three small process changes that make embedded contractors actually feel like teammates.
Read the postShare where you are today β a Slack screenshot works as well as a brief. We'll come back within one business day with a plan of action.