Two tools to decide with numbers
A calculator to estimate how much time and value an automation frees up, and a ten-question check-up on the security of AI systems, based on the OWASP Top 10 for LLM applications. Free, no sign-up: what you enter stays in your browser.
What is automating a process worth?
Think of a repetitive task: data entry, answering the same questions, reports, moving data between systems. Enter your numbers and see how much time comes back.
The starting values are only an example: replace them with yours.
414hours freed every year
€12,420yearly value of the time freed
- Time that comes back
- Time that stays with people
- Today
- 690 hours a year
- After automation
- 276 hours a year
With an investment of up to €12,420 the project pays for itself within twelve months.
Hours freed = people × hours per week × weeks × automatable share. Value = hours freed × hourly cost.
This is a rough estimate: it leaves out running and maintenance costs, and indirect benefits such as fewer errors and faster replies.
Is your AI system protected against the most common risks?
Ten questions, one for each item of the OWASP Top 10 for LLM applications. It applies to chatbots, assistants and AI agents, live or planned.
- In place
- To check
- Unanswered
0controls in place out of 10
0 of 10 answered
Answer the questions: the result updates with every answer.
A solid base: the main controls are in place. An independent test is the way to put them to the proof.
A few areas need fixing before they turn into a problem.
Several areas are uncovered: a security assessment is the place to start.
Areas to check
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Prompt Injection LLM01
Separate instructions from external content, filter inputs and test the system with prompt injection attacks.
Prompt injection: how to protect chatbots and AI agents (OWASP Top 10 for LLMs)
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Sensitive Information Disclosure LLM02
Map the data reaching the model, cut what is not needed and check how the provider stores and uses it.
ChatGPT, Claude and Gemini at work: how to use them without exposing your data
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Supply Chain LLM03
Keep an inventory of models and components, with versions, licences and provider terms.
ChatGPT, Claude and Gemini at work: how to use them without exposing your data
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Data and Model Poisoning LLM04
Control who can add content to the knowledge base and track where every document comes from.
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Improper Output Handling LLM05
Treat model output as untrusted input: validate it, encode it and never execute it directly.
Prompt injection: how to protect chatbots and AI agents (OWASP Top 10 for LLMs)
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Excessive Agency LLM06
Give the agent only the tools and permissions it needs, and put a human confirmation on irreversible actions.
AI agents for business: what they are, what they do and how to introduce them safely
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System Prompt Leakage LLM07
Remove secrets and credentials from the prompt: security controls belong in code, not in instructions to the model.
Prompt injection: how to protect chatbots and AI agents (OWASP Top 10 for LLMs)
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Vector and Embedding Weaknesses LLM08
Enforce document permissions in semantic search too, and keep different customers’ data separate.
ChatGPT, Claude and Gemini at work: how to use them without exposing your data
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Misinformation LLM09
Make answers cite sources, measure quality on real cases and add human review where a mistake is costly.
AI agents for business: what they are, what they do and how to introduce them safely
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Unbounded Consumption LLM10
Set per-user and per-key limits, spending caps and alerts on unusual consumption.
This is a rough self-assessment: it does not replace a penetration test or a risk assessment. Your answers stay in your browser.
Frequently asked questions
How do you calculate the return on an automation?
Start from the time the task takes today: people involved times hours per week times working weeks. Multiply by the share the software can take over and by the cost of one hour of work to the company: the result is the yearly value of the time freed. Dividing the investment by the monthly value gives the payback time. It is a cautious estimate, because it leaves out indirect benefits such as fewer errors.
Does the AI security check-up replace a penetration test?
No. The check-up is a self-assessment that shows where to look, based on the ten items of the OWASP Top 10 for LLM applications. A penetration test verifies in practice, with controlled attacks, whether those controls really hold.
Is the data I enter saved or sent anywhere?
No. The calculations run in your browser: numbers and answers are neither sent nor saved. We only receive data if you choose to write to us through the contact form.
Tell us what you want to build.
Write a few lines about your project: we will reply personally to set up a first call.
What happens next
- We read your request and reply personally.
- We set up a first call to understand goals, processes and constraints.
- You get a written proposal with phases, timeline and costs.