werqly Pro management
Your own server room
We operate the node and the models
— per month
—
- Data never leaves your premises
- No outside party in the processing
- Updates, monitoring and support by werqly
Private AI knowledge base
Practical answers for the people responsible for data, security and compliance. What goes wrong when AI runs outside your control, what the rules ask of you, and how to bring AI into your own environment.
What is private AI? Meaning, forms and when you need it
Private AI means language models run on infrastructure that belongs to your organisation alone. What it is, which forms exist and when it is the right choice.
Read the article →Is ChatGPT GDPR-compliant for your organisation?
Can your organisation use ChatGPT under the GDPR? The difference between free and business use, when it becomes a data breach and what you need to arrange.
Read the article →Shadow AI: what to do when staff use ChatGPT on their own
Shadow AI is AI use outside IT’s view. Why a ban alone does not work, what happened at the Dutch city of Eindhoven, and how to bring it under control in five steps.
Read the article →The EU AI Act in 2026: what must your organisation have in place?
The AI Act after the Digital Omnibus: what applies now, what is postponed to 2027 and what you must arrange as a user of AI. An overview with timeline and checklist.
Read the article →An on-premises LLM server: what do you need?
What does it take to run a language model in your own server room? GPU memory per model, concurrent users, software, power and cooling, and the operations around it.
Read the article →Microsoft 365 Copilot or your own AI environment?
Microsoft 365 Copilot or AI in your own server room? A fair comparison on data, privacy, the CLOUD Act, control, and when each choice fits your organisation.
Read the article →AI in healthcare: patient data, hosting rules and the GDPR
Can a care organisation use AI with patient data? What medical confidentiality, the GDPR and hosting rules (NEN 7510, C5, HDS) require, and how to do it safely.
Read the article →AI for law firms: professional secrecy and bar guidance
May a lawyer use ChatGPT for client files? What professional secrecy and bar guidance on AI (CCBE, NOvA, BRAK, CNB) require, and how a firm uses AI responsibly.
Read the article →AI at financial institutions: DORA, outsourcing and the AI Act
What does DORA mean for AI at banks, insurers and investment firms? Outsourcing, the register of ICT providers, the exit strategy and high-risk rules in the AI Act.
Read the article →Writing an AI policy: what belongs in it and how to make it stick
An AI policy for your organisation in ten parts: approved tools, data classes, human review, AI literacy and incidents. With an approach and the common pitfalls.
Read the article →A DPIA for generative AI: when is it required and how do you do it?
When is a DPIA required for an AI tool, and how do you carry it out? The criteria, the steps, the AI-specific risks and how your hosting choice shapes the outcome.
Read the article →The CLOUD Act and your European data: does hosting in Europe help?
What is the US CLOUD Act, why does data in a European datacentre of a US provider not fully protect you, and what does? An explanation for CISOs and DPOs.
Read the article →AI on your own documents: how RAG works, and how to keep it safe
With RAG a language model answers from your own documents. How it works, where it goes wrong with access rights and data leaks, and how to set it up safely.
Read the article →May you read your employees’ AI prompts? GDPR, works councils and policy
May an employer read what staff ask AI? What the GDPR, works council rules in the Netherlands, Germany and France, and the AI Act say, and a balanced set-up.
Read the article →NIS2 and AI: what the directive asks of your use of AI
What NIS2 means for AI: supplier risk, incident reporting and board accountability, and where transposition stands in the Netherlands, Germany and France.
Read the article →Llama, Mistral or Qwen? Choosing open-weight models for your organisation
Which open-weight model fits your organisation? Licences, the EU restriction on multimodal Llama models, language, size and hardware side by side.
Read the article →Prompt injection and other AI security risks: what a CISO needs to know
Prompt injection, data leaks through AI and AI agents with too many rights: the main security risks of language models per OWASP, and what helps.
Read the article →AI literacy: what the AI Act asks and how to train your staff
Article 4 of the AI Act asks for measures on AI literacy. What that means after the Digital Omnibus, what belongs in training, and how to record it for a supervisor.
Read the article →A data breach through an AI chatbot: a plan for the first 72 hours
An employee put personal data into ChatGPT. What now? A plan: establish, contain, assess, notify the supervisory authority and prevent a repeat.
Read the article →AI hallucinations: why language models make things up and who is liable
Language models sometimes invent facts, sources or case law. Why it happens, what it cost in court, who is liable and how to manage the risk in your organisation.
Read the article →Setting up an AI register: an overview of all AI in your organisation
An AI register gives an overview of all AI in your organisation. Why you need it for the AI Act, GDPR and NIS2, which fields to include and how to keep it current.
Read the article →AI agents in your organisation: what they are and how you stay in control
AI agents carry out tasks themselves: sending email, updating systems, processing documents. What that brings, which risks come with it and which limits to set.
Read the article →AI in HR and recruitment: what is allowed, and what becomes high-risk?
AI for recruitment, selection and appraisal faces the strictest rules of the AI Act. What is banned already, what applies from December 2027, what to do now.
Read the article →An AI chatbot for customer service: transparency, liability and data
An AI chatbot for customers? Since August 2026 you must disclose that it is AI, you are liable for what it says, and customer data deserves protection.
Read the article →Where to start with AI automation: choosing processes that pay off
Which processes suit AI automation, and which do not? Five traits of a good candidate, a four-step approach and the pitfalls that often trip organisations up.
Read the article →Assessing an AI vendor: twenty questions for the CISO, DPO and procurement
Which questions should you ask an AI vendor before you sign? Twenty questions on data, training, location, security, contract, exit and the AI Act, explained.
Read the article →Access control for AI: roles, SSO and least privilege
Who may use which AI model, which sources and which automations? How to connect AI to your identity provider and stop AI from bypassing permissions.
Read the article →Hardware for your own AI server: GPUs, memory and model size
How much GPU memory does a language model need, how many users can one server handle and what does it ask of your server room? A practical explanation.
Read the article →What does private AI cost? The cost items of your own AI environment
Hardware, placement, management, models and automations: the costs of your own AI environment, and how they compare with licences per user.
Read the article →Summarising confidential documents with AI: how to do it safely
Having AI summarise contracts, case files and reports saves hours. But where does the document go? How to summarise confidential documents safely.
Read the article →Transcribing meetings and conversations with AI: privacy and professional secrecy
AI turns a recording into minutes in minutes. But a conversation with a client or patient is sensitive data. What to watch for when transcribing with AI.
Read the article →Generative AI in local government: what is allowed, and how to set it up
Public bodies may use generative AI, under conditions. What the AI Act asks of them, what the Dutch 2025 policy shows, and how to set up AI in-house.
Read the article →AI for accountants and accounting firms: confidentiality and the three principles
Accountants use AI in every phase of the audit. What the duty of confidentiality requires, the three principles regulators name and client data in-house.
Read the article →AI in permit decisions: faster handling, without giving up the reasoning
Permit decisions run on short statutory deadlines. Where AI speeds up the work of case handlers, and where the decision has to stay with the authority.
Read the article →AI in social services: where it becomes high-risk, and what is still possible
AI that decides who is entitled to a benefit or service is high-risk AI. What that means, and which applications remain justifiable for public bodies.
Read the article →Handling freedom of information requests with AI: faster searching, not faster judging
Information requests run on short deadlines. Where AI speeds up finding, sorting and redacting documents, and why the assessment stays with a lawyer.
Read the article →Algorithm registers: what does a public body publish, and when?
Which algorithms belong in a public algorithm register, what goes into an entry, and how does it relate to the EU database and your own AI register?
Read the article →Procuring AI as a public body: contract terms, roles and exit
What do you put in the contract when buying AI? The European Commission’s model clauses, your role under the AI Act, and terms on data, logging and exit.
Read the article →An AI assistant of your own: from pilot to daily use in a public body
Many public bodies get stuck in the pilot stage. How to roll out an AI assistant that staff actually use, with policy, roles and measurable results.
Read the article →AI in administrative objections: keeping the deadline without automating the judgement
Objections run on tight statutory deadlines. Where AI speeds up the preparation, and why the reconsideration and the hearing stay human work.
Read the article →Letters to residents in plain language, with AI as first editor
Many government letters are too complicated. How AI helps rewrite them into plain language, and which mistakes you have to prevent while doing it.
Read the article →AI and information security in public bodies: baselines, audits and a node in your own network
How does an AI environment fit your security baseline and annual audit? Which measures to take, and why a node in your own network shortens the story.
Read the article →Do you have to archive AI conversations? Records law and your AI assistant
When does an AI output become a record? How to treat prompts, drafts and outputs under public records rules, and what is best to keep.
Read the article →AI in citizen contact: transparent, accessible and accountable
An AI assistant for residents’ questions: what the transparency duty requires, why digital accessibility applies, and how to prevent wrong answers.
Read the article →Sharing an AI environment: what works between public bodies, and what does not
Sharing an AI node with neighbouring authorities or a joint body: what it delivers, how to separate data, and which roles to record under the GDPR.
Read the article →AI for the council and its clerks: questions, papers and minutes
Councillors receive piles of papers and ask many questions. How AI helps the clerk’s office and the administration, without changing the role of the council.
Read the article →AI for public space reports: faster to the right department
Broken street lights, litter, loose paving: AI can categorise and route residents’ reports. How authorities already do this, and what to watch for.
Read the article →AI for grant applications: faster assessment, without AI making the choice
Grant rounds bring peaks of applications. Where AI prepares the assessment, and why ranking and awarding stay with the public body.
Read the article →AI and civil affairs: why the population register is not just another source
Civil affairs handles the most sensitive data a municipality holds. Where AI helps at the desk and in the back office, and why it stays out of the register.
Read the article →Testing algorithms for discrimination: lessons for public bodies
Rotterdam and SyRI: what went wrong and how to test in advance whether an algorithm disadvantages groups. With the AI Act and a practical approach.
Read the article →AI in the budget cycle: budgets, annual accounts and council information
Budget, spring memorandum, annual accounts: lots of text, lots of coordination, fixed deadlines. Where AI helps, and where figures stay human work.
Read the article →AI in enforcement and inspection: faster reports, prioritisation with care
Inspectors and enforcement officers write many reports with limited capacity. Where AI helps, and why prioritising on the basis of profiles is risky.
Read the article →Processing consultation responses with AI: hundreds of submissions, one response report
A zoning plan or large project brings piles of consultation responses. How AI sorts them and prepares a response report, while every submission gets an answer.
Read the article →AI in property valuation and local taxes: objections, valuation reports and explanation
Property valuation for local taxes is already model-based. Where generative AI helps: preparing objections, explaining reports and answering questions.
Read the article →Incoming mail and the case system: AI that registers, routes and finds the case
Letters, emails and forms arrive in dozens of places. How AI classifies them, links them to the right case and brings them to the right department.
Read the article →Translating with AI for multilingual residents: what is allowed, what works and what to record
Many residents read another language more easily than the official one. When a public body may translate, where AI is good enough and where a person checks.
Read the article →AI literacy in local government: who needs to know what, from council to front desk
The AI Act asks organisations to support AI literacy. For a public body that differs per role: council, executive, case workers, contact centre and IT.
Read the article →AI in municipal debt counselling: early warning, intake and plans, without risk scores
Dutch municipalities receive payment-arrears signals by law. Where AI helps with intake, files and plans, and why a risk score per resident is the wrong step.
Read the article →AI in youth care: relieve reporting and files, never score children
Youth care is a local authority’s most sensitive task. Where AI relieves teams of reports and files, and why risk assessment of children stays off limits.
Read the article →DPIA, IAMA and fundamental rights assessment: one review for a municipal AI application
The GDPR DPIA, the Dutch IAMA and the AI Act rights assessment look alike. How a local authority does them as one, and when each is mandatory.
Read the article →AI and the zoning plan: reading plan rules, keeping them consistent and answering residents
Every Dutch municipality must have one environment plan by end 2031. Where AI helps convert old rules, guard consistency and answer “may I build here”.
Read the article →Shadow AI in local government: staff already use ChatGPT. Now what?
In almost every local authority, staff use public AI tools without IT knowing. How to map it, what to prohibit and how to offer an alternative.
Read the article →AI and digital accessibility: meeting WCAG with AI, and an AI assistant that is accessible itself
Public bodies must meet WCAG 2.1 AA. Where AI helps with alt text, plain language and accessible documents, and what an AI assistant must meet itself.
Read the article →AI in social care assessments: writing up the home visit, meeting the deadline, the decision with the assessor
Six weeks for the assessment, two for the decision under Dutch law. Where AI helps assessors with the report and the decision, and what stays with people.
Read the article →AI in running elections: polling staff, instructions and voters’ questions, never the count
A local authority runs elections with hundreds of volunteers and strict electoral law. Where AI helps the elections team, and why the vote itself stays AI-free.
Read the article →AI in crisis management: situation reports, crisis communication and aftercare, with the mayor in charge
In a crisis a local authority must build a picture fast and communicate fast. Where AI helps the crisis team with situation reports and messages, and its limits.
Read the article →AI in executive reports: a good proposal faster, with the weighing left to the executive
Dozens of executive reports a week, each with the same structure and checks. Where AI helps the officers drafting them, and what stays with the elected members.
Read the article →Monitoring AI in production: what a local authority measures, keeps and reassesses every year
After roll-out the real work begins. Which figures a local authority tracks, which logs it keeps, how it catches errors and when it reassesses an application.
Read the article →An exit strategy for AI: how a local authority switches supplier or model without starting over
Whoever buys AI must know how to get out again. What a local authority records on model, data, prompts and logs, and what the Data Act has required since 2025.
Read the article →AI for notaries: what is allowed, what helps and what professional secrecy demands
How a notary’s office uses AI without breaching its duty of secrecy. What the Dutch notarial guidance asks, which tasks AI does well and which environment fits.
Read the article →AI security in healthcare: what the information security standard asks of an AI environment
Dutch healthcare runs on NEN 7510, built on ISO 27001. What AI adds to the risk register, which requirements an AI environment must meet and how to show it.
Read the article →AI policy: a one-page example you can use today
A complete example of an AI policy for staff in ten articles: permitted tools, what never goes into AI, checking, reporting and training. Copy it and adapt it.
Read the article →GDPR-compliant AI: the twelve-point checklist for any AI tool
When is an AI tool GDPR-compliant? Twelve checks, from legal basis and processing agreement to logging and breaches, and public service or own environment.
Read the article →NIS2 incident reporting and AI suppliers: 24 hours, 72 hours, one month
NIS2 incident reporting applies in the Netherlands since 15 August 2026. When an AI incident is reportable and what to agree with AI suppliers.
Read the article →Setting up your own AI environment: from first process to production
How to set up an AI environment of your own: the four components, eight steps from goal to production, the choices that matter and the mistakes to avoid.
Read the article →Data processing agreements for AI services: what must be in them, and what ChatGPT lacks
Without a data processing agreement, no AI service may process personal data for you. What Article 28 GDPR requires and what to check with ChatGPT and Copilot.
Read the article →Your own company GPT: chat with your business data without it leaving the building
A company GPT answers questions from your own documents and systems. What it takes, which variants exist and why the location of the model decides the outcome.
Read the article →AI Act: provider or deployer? When your organisation becomes a provider without noticing
Deployer or provider under the AI Act? Three steps turn you into a provider: your own brand, a substantial modification or a new intended purpose.
Read the article →Calculate your private AI costs.
Enter your work email and number of employees. We work out four setups for you straight away: in your own server room or in our datacentre, self-managed or with werqly Pro management. werqly is not a cheap AI subscription: you pay for your own hardware and full control.
- 1Enter your email and number of employees
- 2Compare four proposals
- 3Request a quote straight away
Working out the proposals…
Your own server room
Your node in your own server room or rack
werqly Cloud
No server room? A locked rack in our EU datacentre
werqly Pro management
werqly Cloud
We operate the node and the models
— per month
—
- For organisations without a server room
- Dedicated node in a locked rack, never shared
- Updates, monitoring and support by werqly
Self-managed
Your own server room
Your IT department operates it; we supply software and updates
— per month
—
- Data never leaves your premises
- No outside party in processing or management
- Full control with your IT department
Self-managed
werqly Cloud
Your IT department operates it; we supply software and updates
— per month
—
- For organisations without a server room
- Dedicated node in a locked rack, never shared
- Your IT department runs policies and automations
Indicative amounts, excluding VAT. Custom automations are quoted separately. Only the quote is binding.