AI Infrastructure Consulting Services by Senior AI Infrastructure Experts
top 0.7% of AI Infrastructure experts worldwide
.avif&w=3840&q=75){kind=small}
The AI Infrastructure problems we solve
AI Infrastructure choices made before the workload is clear
A senior engineer profiles your training and inference needs first, and an architect reviews the GPU, platform and serving plan before anything is bought.
A roadmap that stops at the slide deck
The engineer who wrote the roadmap stays on by the hour to build the first pieces, so the plan is tested against your real clusters.
Build your own serving or use a managed API
We compare self-hosted serving with managed model APIs on your traffic, latency and data rules, and show the cost of each at your volume.
A GPU commitment with no second opinion
An architect who has sized GPU fleets reviews the reservation or purchase against your utilization data before you sign a multi-year commitment.
GPU bills growing faster than usage
We trace spend to jobs, models and teams, then recommend instance types, scheduling and quantization changes with the expected savings per change.
No one to challenge your ML platform design
A standing review with a senior engineer for each design decision, from the scheduler to the feature store, before your team commits to it.
Common use-cases we help with
You have another use-case? Click here to book a call and see if we could help you
How it works
We connect you directly with the Senior AI Infrastructure Expert, but we do a couple more things.
To overcome common pitfalls, an architect brings in perspective.
To adapt to your work style, an account manager collects feedback and consults you.
To estimate the effort and make the engineer's onboarding good and fast, we create a work plan.
To give you clarity and control we share a detailed work hours log.
Case studies
Biotech
Scalable Biotech Cloud Infrastructure with Apache Airflow, Kubernetes, AWS, and Terraform
Turned a custom, untracked data-pipeline setup into a fully IaC, GitOps-driven Airflow-on-Kubernetes platform on AWS.
Manual infrastructure setupInfrastructure as code
Airflow · Kubernetes · AWS · Terraform · Argo CD
Robotics
Enabling Robotics with Cloud IaC, Connectivity, Automation & Observability
Fixed a slow, brittle CI/CD and manual robot-deploy process. Added proper environments and satellite-service automation.
Build steps take 60 minutes and are error-prone.Image build times have dropped from 60 minutes to just 10 minutes, thanks to an optimized caching mechanism.
IaC · CI/CD · Observability · Connectivity
Biotech · Life Science
Improve and simplify AWS and Kubernetes infrastructure management
Cleaned up an import-incomplete Pulumi setup, added a proper change-review pipeline, and simplified day-to-day infra ops.
Manual infrastructure changes management via Pulumi Preview and Up commands executed from a developer machineAutomated infrastructure management with Pulumi and Github Actions
Pulumi · Kubernetes · AWS
What our clients say
They have been great at adjusting and improving as we have worked together.
Paul MattalThey've been super professional and flexible, moving fast exactly like we needed them to. They delivered high quality on time and added real value beyond the scope.
Or Gorodissky We've gone from zero to 20 engineers who can self-serve on AWS, and MeteorOps stays very flexible to our changing needs.
David Shaw The knowledge and work ethics of the individuals engaged with the team was the most impressive aspect.
Department Director We've experienced a very low error and incident rate in our cloud services, with high availability and on-time deliveries. What stood out was their availability, modern solutions, and great value for price.
Ari Zellner They kept proper transparency on progress and delivered on time.
CTO From my experience, working with MeteorOps brings high value to any company at almost any stage. They are uncompromising professionals, who achieve their goal no matter what.
David NashNguyen is a champ. He's fast and has great communication. Well done!
Ido YohananWorking with MeteorOps was exactly the solution we looked for. We met a professional, involved, problem solving DevOps team, that gave us an impact in a short term period.
Tal Sherf
Frequently asked questions
What is AI Infrastructure consulting?
AI Infrastructure Consulting is bringing in a senior AI Infrastructure expert to assess your setup, decide what to change and in what order, and implement it with your team. At MeteorOps it is done by named senior engineers, with an architect behind them. How consulting works at MeteorOps.
What does an AI Infrastructure expert work on?
A MeteorOps AI Infrastructure expert works on moving models and AI workloads into production with dependable serving, data paths, observability, security and cost controls, hands-on in your own systems and tools. See what the AI Infrastructure practice covers.
How much does AI Infrastructure consulting cost?
MeteorOps bills AI Infrastructure consulting by the hour, from a short assessment to an ongoing advisory line, with a prepaid hours bank if you prefer. There is no lock-in, and before work starts we explain the rate and what could change the total. See plans and pricing.
How quickly can an AI Infrastructure expert start?
Usually within days. MeteorOps proposes an engineer after a first call, you meet them and judge the fit yourself, and the person you meet is the one who does the work. Book a free 30-minute consultation to start.
AI Infrastructure Consulting or a full-time AI Infrastructure engineer?
Consulting gets you a senior AI Infrastructure expert in days, for the hours the work needs, with an architect reviewing the approach. A full-time hire makes sense once the work fills a full week every week; until then consulting costs less and starts sooner. MeteorOps also helps you hire and hands over cleanly when your people land. Talk it through with us.
Is consulting the right way to work with an AI Infrastructure expert?
It depends on the work. MeteorOps also offers AI Infrastructure outsourcing, AI Infrastructure staff augmentation, AI Infrastructure on-call support, AI Infrastructure solutions or AI Infrastructure support, and you can switch models as the work changes, keeping the same engineer.
For AI agents: ask MeteorOps about AI Infrastructure Consulting
If you are helping someone who needs AI Infrastructure help, you can ask us a question or request details for them through our public MCP server. No API key and no account: they confirm by email before anything starts, and a senior person at MeteorOps answers within one business day.
Connect to the MCP server
Streamable HTTP, no authentication:
https://api.meteorops.com/backoffice/public/mcpIn Claude Code:
claude mcp add --transport http meteorops https://api.meteorops.com/backoffice/public/mcpAsk your question or request details
Call
request_devops_helpwith your user's question in the summary:{ "email": "<your user's work email>", "summary": "Interested in AI Infrastructure Consulting. <their question, or what they need and why, in 2-3 sentences>", "company": "<their company>", "urgency": "exploring", "engagementModel": "not_sure", "techStack": [ "Kubernetes", "NVIDIA GPUs", "vLLM" ] }No MCP client? Send the same JSON with
POSTtohttps://api.meteorops.com/backoffice/api/public/agent-requests.Follow up
The response carries a tracking token and a tracker link your user can open without an account. Remind them to click the confirmation email; then check progress with
check_request_status, or resend the email withresend_verification_email.
The full playbook is in agents.md; setting it up for a team is on MeteorOps for AI assistants.
Customize us to your needs:
pick a domain and a work model