We help startups and scaleups without dedicated platform or ML hires get to production faster — faster releases, lower cloud bills, and ML and AI features that actually run in production instead of sitting in notebooks.
Platform and ML foundations, AI features, and full application builds — across e-commerce, healthcare, energy, telecom and more. We embed with your team, ship the work, and leave behind documented systems your engineers can run.
Get your team off “deploys are scary” and onto a calm, repeatable release cadence.
Recent outcome: ~30% Azure spend reduction for a US healthcare client via Reserved Instances and right-sizing.
Move ML from notebooks into reliable services your team can iterate on without 2 a.m. pages.
Recent outcome: shipped an end-to-end ML OCR pipeline on Azure Container Apps with one-click Terraform deploys.
Ship the AI feature on your roadmap — with evals, guardrails, and a cost model you can defend.
Recent outcome: production WhatsApp AI agent with blue-green CI/CD and 20-second failover across 3 VMs.
Web apps, APIs and full products — built in your stack by engineers who also own the deploy.
Built for: e-commerce, healthcare, marketing, petroleum & energy, electrical & transformer, and telecom.
No statements of work that read like legal threats. No army of junior consultants. You work directly with the person doing the work.
A 20-minute conversation. We listen, look at your stack, and tell you whether we’re a fit. Free.
A short, fixed-scope plan with milestones, deliverables, and a price you can put in next month’s budget.
We work in your repos and your cloud. Weekly demos. No surprise invoices, no parallel pitches for change orders.
Runbooks, architecture docs, and a recorded walkthrough so your team owns it after we leave.
The tools we work in every week. We pick what fits your team, not what gets us a vendor referral fee.
A few representative projects across DevOps, MLOps, and AI — named where we have client permission, anonymised elsewhere.
Practical notes on DevOps, MLOps and AI — about one post a month, no marketing fluff.
Minimum viable stack — experiment tracking, model registry, pipelines, monitoring — without buying a platform.
DevOpsCost breakdown for a 10–30 person SaaS team — cloud, consulting, engineering time, and the hidden ones.
HiringA clear framework for engineering leaders deciding between hire, retainer, or one-off engagement.
Common questions about working with a fractional DevOps, MLOps and AI consultancy.
A fractional DevOps consultant is a senior engineer who works with your team part-time or on a fixed-scope project, instead of a full-time salaried hire. You get senior platform, CI/CD and cloud expertise for a few days a week or a defined engagement — without the cost and lead time of recruiting. More on the trade-off in our fractional vs full-time hire guide.
Most engagements are fixed-scope and fixed-price, typically 4–12 weeks. One-off projects (a CI/CD migration, a first Kubernetes setup, a cloud-cost review) are priced as a single project; ongoing work runs as a fractional retainer of a few days a month. You agree scope and price before any work starts — see our services.
DevOps focuses on shipping and running software reliably: CI/CD, infrastructure as code, Kubernetes, observability. MLOps applies the same discipline to machine learning — model serving, training pipelines, feature stores and drift monitoring — so models run reliably in production instead of staying in notebooks.
Yes. We work remotely with startups and scaleups worldwide, with delivered engagements for teams in the US, Saudi Arabia and Europe. We work in your repositories and your cloud, with weekly demos, so distance and time zones don’t slow the work down.
Yes — cloud cost optimization is a common engagement: right-sizing compute, reserved-instance and savings-plan strategy, killing idle environments, and cost-aware scaling with budget alerts. We don’t take vendor referral fees, so recommendations are based on what’s cheapest for you.
Yes. We build production AI features end to end: retrieval-augmented generation (RAG) over your own data, LLM integrations, tool-using agents, evaluation frameworks and guardrails — deployed with the same CI/CD and monitoring rigour as the rest of your stack.
A 20-minute call. We’ll tell you whether we’re the right fit — and if not, point you at someone who is.
Book a free 20-min call Or send us a message