Releases are stressful
Deployment is manual and never on a Friday, a rollback turns into an emergency, and every release risks taking production down. So updates pile up and ship less often than the business needs.
Problem → solution
Build the infrastructure
The product is growing, but the infrastructure holds it back: releases are scary to ship, clients are the first to report failures, and the backup is first tested when it is already needed. We make deployment a boring operation, failures visible in advance and recovery a tested procedure.
For teams whose infrastructure gets in the way of growth: manual releases, an opaque production, resilience that rests on one person — or a need to deploy inside a closed perimeter and to security requirements.
What people come with
Production is a black box
Failures and degradation are discovered through client complaints, and the cause is hunted down by hand in the logs. No metrics, alerts or traces — so no early signal either.
Resilience hanging by a thread
Everything rests on one server and one person; backups are made but have never been restored, and there are simply no recovery-time requirements.
How we solve it
Infrastructure audit
We look at how build, deployment, monitoring and recovery work today, and find the places where everything rests on manual work and luck.
A plan by risk and impact
First what breaks most often or costs most when it fails. We do not redo everything at once or impose complexity you will not be able to maintain.
Roll out in iterations
Containerisation, a deployment pipeline, observability and backups — without stopping the product. Every step leaves the system in working order.
Hand over to your team
Documentation, incident runbooks and training. Infrastructure that only the contractor understands is a new risk, not a fix for the old one.
What it is built on
Containers and orchestration sized to the task
Kubernetes where load and the number of services justify it; Docker Compose where it is enough. We choose orchestration for the task, not for fashion.
A proven production setup
Secrets in a vault, security gates in CI and deployment by digest, hardened container isolation, encrypted backups with test restores and RPO/RTO targets — a repeatable practice from our projects.
Infrastructure for data and AI
Data pipelines, storage and queues, an environment for model training and inference — including local models, inside your perimeter, when data cannot leave it.
What we do for it
What it looked like in practice
Music tech · SaaS
MVP in operation (closed launch)Music releases without missed deadlines
Release ops for independent labels: 9-stage lifecycle, pitching deadlines for 12 stores, AI drafts with human approval. Zero to production-grade in 7 weeks.
- 7 weeks
- from first commit to a production-grade stack with Vault, encrypted backups, SLOs and a move to a Russian data centre (265 commits)
- 16 days
- from project start to an investor presentation with a live product demo
Marketplace e-commerce · Pricing
PilotRepricing without manual price control: a contract-guaranteed pilot
Competitor prices tracked per SKU on the marketplace, a price computed inside an agreed corridor, applied only after confirmation. Pilot: 10 SKUs, setup within 14 days.
- 10 SKUs · 2 scenarios
- pilot scope; the SKU cap and both scenarios are enforced in code and verified by contract tests — the cap cannot be exceeded
- up to 14 days
- contractual setup window from client inputs to launch, then a 1-month pilot; the service tracks the dates and closes access when the period ends
AI infrastructure / multi-agent systems R&D
Research projectA multi-agent environment where rules are code, not prompts
In four days we built and open-sourced (MIT) an agent environment where constraints are enforced in code: cryptography, Byzantine consensus, reproducible experiments.
- same hash
- a repeated run and a replay of the log give a byte-identical final event hash — anyone can repeat it from the MIT-licensed code
- 187 of 187
- engine tests green — master branch, commit 625b81d, as of 05.10.2026
Cost the effect on your own numbers
AVA is a process economics calculator. In a couple of minutes it shows whether automating your case is worth it — before you talk to us, with no commitment.
Estimate the impact with AVAFrequently asked questions
Do we need Kubernetes?
Often, no. It is justified with many services and serious load; for one or two services it adds complexity with no gain. We choose orchestration for the task and say honestly when Docker Compose is enough.
Can everything be deployed inside a closed perimeter or in a Russian data centre?
Yes. We deploy solutions inside closed perimeters and in Russian data centres, with secrets in a vault and no calls to external providers. In one project, moving production to a Moscow data centre took one day.
How can we be sure the backups actually work?
A backup without a tested restore is a hope, not a backup. We set up encrypted backups with automatic test restores and clear RPO/RTO targets, so that recovery is a tested procedure.
Other tasks
Build a software product
You have a product idea, a business model or a mock-up — but no working system, or one that cannot cope with growth. We design and build the product with operation in mind: the minimum scope that tests the hypothesis, on an architecture that will survive the second client.
Automate a business process
Manual work has become the bottleneck: people sort through requests and documents, move data between systems and answer the same questions over and over. Automation does not pay off everywhere — so we start with where exactly the time and money go, and automate what can be counted in money.
Adopt AI
You need AI, but it is unclear where to start and whether it will pay off. AI projects more often fail not at the model but earlier — the chosen process cannot be counted in money, or the data for it does not exist. We start with the process and a data check, and decide on the technology last.
Tell us about your task
Describe what needs solving. If it cannot be solved or will not pay off, we will say so straight away, before any work starts.
or email us directly: hello@xteam.pro