AI Infrastructure That Doesn't Break in Production
We help companies deploy, scale, and operate AI systems reliably. From model serving to monitoring — production-grade AI infrastructure by engineers who've run systems at enterprise scale.
What We Do
End-to-end AI infrastructure — from Jupyter notebook to production Kubernetes cluster
AI/ML Deployment & Infrastructure
We set up model serving infrastructure with GPU optimization, auto-scaling, and CI/CD pipelines for ML models. Cloud-native AI deployment on Kubernetes.
- Model Serving & GPU Optimization
- CI/CD Pipelines for ML Models
- Cloud-native AI (AWS, GCP, Azure)
- Kubernetes ML Workload Orchestration
MLOps & AI Reliability
We set up monitoring for your models, detection for drift, and alerts for when things break. Automated retraining pipelines with SLA-driven reliability.
- ML Model Monitoring & Observability
- Data Drift Detection & Alerting
- Automated Model Retraining Pipelines
- SLA-driven AI System Reliability
Custom AI Agents & Tooling
AI-powered SRE agents for incident detection and auto-remediation. RAG-based knowledge systems, LLM integrations, and AI cost optimization.
- AI-powered SRE Agents
- RAG-based Internal Knowledge Systems
- Custom LLM Integrations & Fine-tuning
- AI Cost Optimization Tooling
Not Sure Where to Start?
Book a free 30-minute AI infrastructure audit. We'll assess your current setup and identify the biggest reliability gaps.
Why Resilio Tech
We combine deep infrastructure expertise with modern AI/ML knowledge
Built by SREs Who've Operated at Fortune 500 Scale
Our team has managed mission-critical production systems handling millions of requests daily — the kind of systems where downtime isn't an option.
6+ Years of Production Infrastructure Experience
We don't just build demos — we build systems that survive Friday deploys. Real production battle scars.
End-to-End: Jupyter Notebook to Production K8s
From model training to production deployment, monitoring, and continuous improvement. No handoff gaps.
We Ship, Not Slide
We'd rather show you a working Kubernetes manifest than a slide deck. Direct, specific, no fluff.
How We Work
Simple, transparent process. No surprises.
Audit
We assess your current AI infrastructure and identify reliability gaps. Free 30-minute call — no commitment, just clarity.
Architect
We design a production-grade AI infrastructure tailored to your scale, stack, and budget. No over-engineering, no under-building.
Implement & Operate
We build, deploy, monitor, and continuously improve. You ship AI features — we make sure the infrastructure holds.
Frequently Asked Questions
Everything you need to know about working with us
We primarily work with Series A–C startups scaling AI features. If you have an ML team building models but struggling with production deployment, we're a good fit.
Three models: 2-week focused sprints for specific problems, monthly retainers for ongoing infrastructure support, or project-based engagements for building complete ML pipelines.
We focus on infrastructure, deployment, and reliability — not model training. We work alongside your data science team to make their models production-ready.
That's actually our sweet spot. We'll design and build your AI infrastructure from scratch — properly, the first time.
We combine deep SRE expertise with specialized AI/ML infrastructure knowledge. Most SREs don't understand ML pipelines; most ML engineers don't understand production reliability. We bridge that gap.
A 30-minute call where we review your current AI stack, identify the top 3 reliability risks, and provide a concrete action plan — regardless of whether you work with us.
Technologies We Work With
Battle-tested tools for production AI infrastructure
Learn With Us
We share everything we learn — real use cases, real production lessons
YouTube Channel
Coming SoonTechnical deep-dives on MLOps, AI infrastructure, and production reliability.
- ▸ Deploying LLMs to K8s
- ▸ GPU Cost Optimization in Practice
Technical Blog
In-depth articles on AI reliability, deployment patterns, and infrastructure automation.
- ▸ Why Your ML Models Fail in Production
- ▸ Building an MLOps Pipeline on Kubernetes
- ▸ How We Cut GPU Costs by 40%
Follow our building-in-public journey and weekly AI infra insights.
- ▸ Weekly AI Infra insights
- ▸ Behind-the-scenes updates
Ready to Make Your AI Production-Ready?
Book a free 30-minute AI infrastructure audit. We'll assess your current setup, identify reliability gaps, and give you a concrete action plan.