Your LLM works locally. In production, it needs to work differently.
We deploy production infrastructure for AI products in 2–7 days: LLM deployment, RAG pipelines, GPU orchestration, model monitoring. You focus on the product — we make it work in production.
Trusted by AI startups, SaaS teams, and research groups
The model works in Jupyter. Production is a different story.
You trained the model, built the RAG, launched the chatbot. But infrastructure is blocking your users.
Every day without proper AI infrastructure is money wasted and a business risk.
Production Infra Box — Infrastructure, Done Right
One package. Fixed timeline. Everything you need to launch with confidence.
LLM & AI Service Deployment
vLLM, Ollama, TGI — deployed with auto-scaling, load balancing, and GPU cost optimization.
RAG Pipelines, End-to-End
Vector DB (Qdrant / Weaviate), embedding service, retrieval API — configured and production-ready.
Model Quality Monitoring
Latency, token/s, error rate, degradation — you see model health in real time. Prometheus + Grafana + custom dashboards.
CI/CD for ML Pipelines
Every model or prompt update is automatically tested and deployed. No manual steps.
AI System Security
Rate limiting, API key management, network policies, RBAC — protection from abuse and leaks.
Backups & Disaster Recovery
Automated backups of vector DB and models. Losing the index is not a disaster.
What You Get
How It Works
5 steps from MVP to production in 2–7 days
Infrastructure Review
We review your stack, cloud, code, and requirements. We define the optimal architecture.
Environment Setup
We deploy the Kubernetes cluster, configure staging and production environments.
CI/CD Automation
We set up automated testing and deployment pipelines. Every commit goes to production without stress.
Monitoring & Security
We connect monitoring, alerts, secrets management, and network policies.
Production Launch & Handoff
We launch in production, hand off documentation and code to your team.
Who This Is For
AI startups with LLM products
You're building a chatbot, RAG system, or AI assistant. The model is ready — you need infrastructure that handles real users.
Research teams with GPU clusters
You need to train and run models on GPU, manage spot instances, and not waste budget.
SaaS teams adding AI features
You're adding embedding, inference API, or generation to an existing product and want to do it reliably without overpaying for cloud.
Founders before demo or launch
Deadline in a week, investors waiting for a demo, client wants production. No time to figure out Kubernetes and Terraform.
Why Not Hire a DevOps Engineer?
Compare your options honestly
Hire a DevOps Engineer
- —$8,000–15,000/month
- —3–6 weeks to onboard
- —Needs to learn your stack
- —Risk of leaving
- —Full-time not needed at early stage
Freelancer
- —$2,000–5,000 per project
- —Unpredictable timeline
- —No quality guarantees
- —No support after delivery
- —Documentation often missing
Production Infra Box
- from $500
- 2–7 days
- Proven stack, fixed scope
- Documentation and code handoff
- Optional 24/7 support after
Transparent Pricing
Fixed price. No surprises.
Essentials
For simple apps and MVP launches
- Kubernetes cluster (staging + production)
- Basic CI/CD (GitHub Actions / GitLab CI)
- Monitoring (Prometheus + Grafana)
- SSL certificates + domain setup
- Basic security and secrets management
Standard
For SaaS products and startups
- Everything in Essentials
- Multi-node Kubernetes with HA
- Full CI/CD with staging and production
- Advanced monitoring and alerts
- Secrets management (Vault)
- Infrastructure as Code (Terraform)
Advanced
For complex systems and high loads
- Everything in Standard
- Multi-region architecture
- Distributed tracing (Jaeger)
- Compliance-ready logging
- Performance optimization
- Extended documentation and SLOs
Enterprise
For enterprise requirements and custom needs
- Everything in Advanced
- Custom architecture for your requirements
- Integration with enterprise systems
- Team training
- Dedicated engineer for the project
- SLA and post-launch support
The Team Behind It
Infoscale is built by DevOps engineers who have designed and operated production infrastructure for startups and SaaS products.
Frequently Asked Questions
Ready to get production-ready infrastructure?
Tell us about your project — we'll respond within 24 hours and propose the optimal plan.