SteelRats
CLIENTS & CASE STUDIES ─── VERIFIED PRODUCTION WORK
Every metric below came out of a real Series B–D SaaS environment we were paged into. 71% MTTR reduction across 180+ stacks. 184 active clients. A 4-minute SLA we actually honor. These are the receipts — and the playbooks we used to get them.
── NAMED, APPROVED RECEIPTS ──
No invented logos. No fake customers. Only the references that survived our legal review and our own standards.
Eleven Winter 2023 Y Combinator graduates ship production on our platform today. Founders we onboarded inside their first 90 days, before they had a real platform team.
Engineers who cut their teeth on the most demanding production environments in fintech and observability came to us when they started their own companies. Same playbook, smaller org chart.
Not sponsored posts — independent reporting and editorial coverage of our incident-response practice and our 2023 retrospective on Kubernetes cost.
── TWO FLAGSHIPS ──
Each card shows the production stack we inherited, the 90-day MTTR delta, the incident volume we absorbed, and the business outcome the board saw.
A YC W23 graduate processing card volume for 600+ merchants came to us after a 47-minute customer-facing outage during their Q3 launch. Two senior SteelRats engineers embedded for 90 days.
A Datadog-alumni founder running a multi-region ingest pipeline on GKE + EKS came to us because their two SREs were burning out. We absorbed the pager, rebuilt the runbooks, and shipped a new incident-response model in 60 days.
── THE NO-FLUFF PROOF BEAT ──
── QUICK-HIT CASE ──
A Series B AI-inference platform serving 40+ model-serving tenants needed an on-call rotation that could speak GPU, NCCL and Kubernetes in the same sentence. Three of our engineers embedded; six weeks later the founding team was sleeping through the night again.
READ THE AI INFRA SNAPSHOT →── CREDENTIALS A SAVVY BUYER WILL GOOGLE ──
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