Managed services
Managed services means we take over maintenance, monitoring and improvement of your live website, automations and AI features under a written service level agreement (SLA). Corrplus tracks updates, backups, incident response, model costs and answer quality, and sends you a monthly report of what was done and what needs attention next.
Book a free callTiming
Onboarding audit and setup usually take 1–2 weeks; monthly after that
Pricing
Fixed monthly fee set by scope; work outside scope is quoted separately in writing.
Tools we use
WordPress and WooCommerce, Cloudflare, UptimeRobot or Better Stack, Sentry, n8n and Make, OpenAI and Anthropic Claude usage dashboards
Who it is for
- Companies that had a website or app built, then found nobody owned it after launch
- Teams on WordPress or WooCommerce who avoid updates because every plugin update risks breaking something
- Operations teams with n8n, Make or RPA workflows in production who hear about a stopped workflow from a customer
- Companies with a chatbot, RAG assistant or language model integration live who want quality and cost reviewed regularly
When it is not a fit
- Companies looking for a full-time IT department or office hardware and printer support. We cover software and platforms.
- Systems where source code or access cannot be shared because another vendor keeps them locked. Access has to be handed over first.
What you get
- Onboarding auditA written report on the current state, security gaps, outdated versions and missing backups across the systems in scope.
- Service level agreement (SLA)A contract annex defining response times per severity and who an issue is escalated to.
- Planned updates and backupsCore, plugin, library and security updates tested on staging before production; scheduled backups with restore tests.
- Monitoring and alertsDefined alerts for availability, speed, automation failures and AI spend.
- AI quality reviewRegular review of sample conversations, fixes for wrong or incomplete answers and updates to the knowledge source.
- Monthly reportWork done, tickets opened and closed, risks worth knowing about and recommendations for the next month.
How we work
Discover
Together we list the systems in scope, who has access to them and the incidents you have had in the past.
Design
We run the onboarding audit and write down the SLA, the support channel and the monthly scope.
Build
We set up monitoring, backups, staging and ticketing, and close the urgent gaps the audit found.
Run
Every month we do planned maintenance, resolve tickets within the SLA and report. Scope is reviewed every quarter.
Why do you need managed services?
A website or automation is not finished the day it goes live. Plugins update, APIs change, certificates expire, a workflow quietly stops. A pattern we often see: the relationship with the original builder has ended, nobody dares to run updates, and problems surface only when a customer complains.
Managed services put that uncertainty under contract. Who does what, and how fast, is written down. You see what was done every month in a report.
Your own team, hourly support or managed services?
| Aspect | Your own team | Hourly support | Managed services |
|---|---|---|---|
| Who notices a problem | The team, when it has time | You, when you call | Monitoring and alerts |
| Updates | Depends on team priorities | When requested | Planned and tested on staging |
| Response time | Undefined | Depends on the vendor’s workload | Written in the contract |
| AI quality and cost | Needs specialist skills | Usually out of scope | Reviewed regularly |
| Cost predictability | Salaries and overhead | Variable | Fixed monthly |
Managed services do not have to replace an in-house team. Often your team focuses on the product while we handle monitoring, updates and AI upkeep.
AI features need maintenance too
A chatbot or knowledge assistant can work well on day one and start quoting outdated prices a few months later. When a model provider ships a new version, the tone of answers can shift. As usage grows, so does the API bill.
We know this from our own product, Promptor, which has cost guardrails built in: daily and monthly spending limits with automatic model fallback. We apply the same principle to client work: spend limits, sample conversation reviews and a knowledge source kept current. For the governance side, including GDPR, the EU AI Act and KVKK, Türkiye’s data protection law, see AI governance and compliance.
What can the scope include?
Scope follows your systems. Typically it covers monitoring and backups for cloud infrastructure, updates and security for WordPress sites, failure tracking for workflow automations and quality review for AI features. In the first call we list your systems and agree the scope of the onboarding audit together.
How would this work in your business?
Tell us where you are in a free first call; we will say plainly where it makes sense to start.
Related services and use cases
Further reading
Chatbot, agent assist or full automation?Chatbot, agent assist or an action-taking agent: request types, hand-off rules, AI Act disclosure and quality metrics.
How to evaluate a RAG systemTest sets, metric choice, LLM-as-judge and live monitoring for measuring retrieval and generation quality in RAG systems.
ISO/IEC 42001 vs NIST AI RMFCertifiable standard versus voluntary framework, how both relate to the EU AI Act, and a starting order for small teams.Our own products
We use the tools and checklists from client projects on our own products too.
All products →Key terms
- AI hallucinationAn AI hallucination is output in which a language model presents information, a source or a figure that does not exist, fluently and confidently, as if it were true.
- LLM (Large Language Model)An LLM (large language model) is an AI model trained on very large amounts of text that answers questions, summarises, translates and writes by predicting what text should come next.
- AI governanceAI governance is the set of policies, roles and processes that determine how an organisation selects, uses, oversees and manages the risks of its AI systems.
Frequently asked questions
Will you take over a system you did not build?
Yes, as long as access and ideally the source code can be handed over. We start with an onboarding audit and share the state of the system and its risks in writing. Gaps that must be closed before takeover are proposed as separate work.
What does the service level agreement cover?
It is a written commitment on how quickly we respond to each severity of issue and who steps in to resolve it. Response times are agreed in the contract based on scope and working hours.
What does maintaining AI features involve?
A language model feature drifts over time: the knowledge source goes stale, the model version changes, costs rise. We review sample conversations, correct wrong answers, and track spend limits and model changes.
What if an update breaks the site?
Updates are tested on staging first. If something still goes wrong in production, we roll back to the last backup and investigate separately. A backup is taken before every update.
Can our own team still make small changes?
Yes. We agree who can change what. The most common setup is your team handling content and simple settings while we handle the technical upkeep.
What happens if we end the contract?
All access, backups, documentation and monitoring settings are handed over to you. Your systems do not depend on us.
Managed services: let’s take the first step together
Tell us where you are in one call; we will share a scope and roadmap in writing.
How we start
- A free first callWe pin down the problem and the goal together.
- A 2-week discovery sprintWe look at the data, the process and the tools, and decide where to start.
- A written proposalScope, architecture and timeline, in writing.