Daily diagnostics, backups, updates, fixes and a report — after launch.
Anyone after launch, whoever built the site.
Diagnostics at four in the morning, a backup at two, certificates renewed automatically, updates after testing and an agreed hour budget for changes. The work history lives in the task system, and you have access to it.
Our recommendation: the first three months included in the project, then voluntary. The promise "we stay after launch" should be true, not compulsory.
In this scope
01
Care after launch
Daily diagnostics, a backup off the server, fixes, and a work history you have access to.
A script at four in the morning checks the disk, the containers, the certificates, backup freshness, container writable layers and the framework cache, and the result is graded OK, WARN, FIX or ASK. On top of that, an IP ban after a hundred failed logins and a restart for containers that died.
A backup daily at two: database dumps plus an incremental copy to external cloud storage, with 7 days, 4 weeks, 6 months and 2 years of retention.
Why this is not empty. On 12 August the disk hit 100 percent and five services stopped. The repair went through without site downtime, and the lessons went into three places: the diagnostics script, the project canon and the documentation. That is what care that learns something looks like.
What you get
Daily diagnostics with a grade and 30 days of history
An off-server backup with a tested restore procedure
Dependency and service updates after testing
An agreed monthly hour budget for changes and fixes
A history of work and decisions in the task system, with access for you
What AI does
Diagnostics, the first analysis of an incident, preparing a fix.
Where a human is needed
Deciding what is an outage and what is noise, and writing the lesson into the procedure so it does not come back.
Private project: We do not promise an SLA with response times in minutes or 99.9 percent uptime. This is one server and one person. The honest promise: a reply within one business day, a backup off the server, a known restore procedure.
02
Analytics and reports
A cookieless visitor counter — so no consent banner — on our server, with access for you.
Custom events (a discount code clicked, a form sent) and a monthly report that answers "where did they come from and what did they do", not "how many page views were there".
Where it stands today: our own instance, five registered domains, the script wired into four sites, traffic confirmed on three.
What you get
A cookieless counter with no consent banner, data on our server
Custom events matched to the goals of the site
Panel access and a monthly report as part of care
What AI does
A draft report and spotting anomalies in the traffic.
Where a human is needed
Wiring the counter, defining the events and interpreting the numbers.
Private project: The analytics panel is private, so the proof is a screenshot on a call, not an address.
03
Performance and Core Web Vitals
Speed work measured with a tool, with a record of what helped and what did not.
Measured with the same engine as PageSpeed, locally, with the flags that cut out the browser artefact on a Mac — without them first paint lands about 1.5 s later and the whole analysis is fiction. A median of several runs, not one result, because a single run sits inside the tool’s own spread.
A result from a real project: mobile 81 → median 91 (spread 87–92), page weight 793 kB → 415 kB, fonts 166 kB → 105 kB and 10 files → 5, accessibility 96 → 100 on mobile and 92 → 100 on desktop.
What you get
A report with before and after, as a median of several runs
AVIF, image quality tuned to the overlay, a custom font subset
Heavy below-the-fold components deferred past first paint
A "checked and rejected" section — with the reason
What AI does
A first optimisation pass and spotting the obvious losses.
Where a human is needed
Measurement that tells the truth, and rejecting changes that only look good on paper. One such "57 kB saving" produced CLS 0.22 and minus 11 points — reverted.
Proof
toprawdziwe.pl — a median of 91 on mobile at 415 kB page weight
04
Audit and consulting
A site audit, a code audit after "vibe coding", model evaluation, or market analysis before you build.
Site audit: performance measured as a median, technical SEO, structured data, accessibility, form and header security. The result is a report ordered by payoff, plus what to reject and why.
The code audit after "vibe coding" is the most current service of 2026. We look for exactly the things that happened to us: caches with no boundary, data that passes validation and still makes no sense, no limits towards external APIs, secrets in the repository, no healthcheck, logs writing the same line thousands of times.
Market analysis before building: does the idea hold, who already does it, what does it cost, what can go wrong. We have two such documents and both of them stopped a build until the assumptions were validated.
What you get
A report ordered by payoff, not alphabetically
A list of things rejected — with the reason
For model evaluation: numbers (errors, time, cost per operation, content fidelity) and a cheaper fallback
What AI does
Reviewing the code and the content, a first pass of the report.
Where a human is needed
Recognising the errors of meaning and operation that syntax never shows, and setting priorities honestly.
Proof
toprawdziwe.pl — the result of a performance and accessibility audit
Common questions
Is this an SLA?
No. This is one server and one person. The honest promise is a reply within one business day, a backup off the server and a known restore procedure — not 99.9 percent uptime.
What if you did not build the site?
We start with an audit, because without one care is guesswork. After the audit it is clear what needs fixing before we take it over.
Packages
What does it cost?
We estimate in hours, after a phone call and a look at the project. Our latest projects took 15 to 45 hours.