Find the root causes
We trace the processes that let waste pile up, so the savings don't creep back.
FinOps · AI Cost Optimization · AI Adoption
Cut your cloud & AI bill 15–30%.
Then put the savings to work.
We're senior engineers who find and remove the waste in your cloud, observability, CI/CD, and LLM spend, and make sure it stays gone. Then we help you build AI that ships to production, funded by what we saved you.
The problem
Most companies overpay for the cloud by 20–30%.
Not because anyone is careless. Waste builds up quietly: the test environment nobody shut down, the instance sized "just in case," logs kept forever, and resources nobody remembers creating. Now AI features add a new, fast-growing line item that almost no one is managing.
Cloud
Oversized compute, idle clusters, untiered storage, surprise egress.
Observability
Log volume, metric cardinality, and retention that grow faster than your product.
CI/CD
Oversized runners, cold caches, and build minutes burned on every push.
AI & LLM
Frontier models on simple tasks, no caching, idle GPUs, and unknown cost per customer.
How we cut costs
We fix the causes of waste, not just this month's bill.
Right-size to real need
Sizing based on actual usage, beyond autoscaling defaults. Kubernetes requests, bin-packing, spot, and commitments done right.
Tune storage & data
Tiering, retention, snapshot sprawl, warehouse queries, and data transfer: often the biggest hidden costs.
Tame observability
Cut log, metric, and trace volume without going blind, and renegotiate vendor contracts from a position of knowledge.
Clean up safely
We show you exactly which resources can be removed without putting production at risk, then remove them.
Make ownership clear
Every resource gets an owner, a budget, and an alert, so cost stays managed after we leave.
AWS · Azure · GCP · Kubernetes · Datadog · Terraform · GitHub Actions · and the tools you already run
AI Cost Optimization
Your AI features should earn more than they cost.
We've run cost and performance optimization for a production AI agent platform: mapping cost of goods sold, cutting the cloud bill, and tuning model usage, all without hurting quality. Few teams have done both infrastructure FinOps and production AI. We have.
- Unit economics. Know your cost per conversation, task, and customer.
- Model routing. The right model for each job, chosen with evals rather than guesswork.
- Caching & batching. Prompt caching, response reuse, and batch APIs where latency allows.
- Token efficiency. Leaner prompts and context without losing quality.
- GPU utilization. Right-sized inference fleets with no idle accelerators.
Estimate your savings
What's 15–30% worth to you?
Add up your monthly spend on cloud, observability, CI/CD, and AI/LLM providers.
$10k$500k+
Estimated annual savings
$144k – $288k
Based on an annual spend of $960k. This is an estimate, not a quote; the free consult gives you a real number.
Get a real numberHow it works
Low-risk to start. Aligned all the way through.
- 1
Free consult
30 minutes. We look at your spend profile and where it's likely leaking.
- 2
Cost assessment
2–3 weeks. A sized, prioritized savings plan with a dollar value on every item. The fee is credited toward the next phase.
- 3
Cost reduction
We implement the changes with your team. Part of our fee is tied to 12 months of realized savings.
- 4
Guardrails
Ownership, budgets, and anomaly alerts so the savings last.
Then, AI adoption
Build what's next with house money.
Once the savings are flowing, your next AI project has already paid for itself. Our team has built AI agents that run inside real products, not demos, and we know what it takes to make them reliable, fast, and affordable.
Talk about AI adoptionAgents in your product
Customer-facing agents with evals, guardrails, and cost controls from day one.
Internal automation
Replace manual, expensive processes with agents and workflows your team trusts.
Engineering enablement
Get your engineers productive with AI tooling, and running it safely.
Production readiness
Deploy, observe, and scale agents with the same rigor as the rest of your stack.
Who we are
Senior engineers, not slide decks.
Joey Stevens
Founder
12 years building and running infrastructure at startups, from bare-metal hypervisors to AWS, Azure, and GCP. Joey has scaled applications to millions of users, led SRE for an AI agent platform, and cut a ~$1M/yr cloud bill by 26%.
Steve Wieland
Partner
Steve spent over a decade single-handedly digitizing and automating the operations of a large government institution. He then joined an AI agent platform, where he mapped cost of goods sold, cut cloud costs, and tuned AI usage for both cost and performance.
Backed by a bench of senior engineers
We work with a network of engineers who have built and run production AI agents. We staff your engagement with the people who've done the work, and scale up when you need more.
Free 30-minute consult
Find out what you're overpaying.
Tell us a bit about your stack and spend. We'll get back to you within one business day to schedule a call, with no obligation and no sales pitch.
Prefer email? hello@revelations.consulting