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How it Works

Created to provide reliable answers.

Vragen.ai turns your own knowledge into a reliable AI search experience. The platform combines retrieval-based search with generative AI, ensuring that each answer is substantiated, traceable, and consistent with the knowledge of your organization.

Vragen.ai turns your own knowledge into a reliable AI search experience. The platform combines retrieval-based search with generative AI, ensuring every answer is substantiated, traceable, and consistent with your organization's knowledge.

What is RAG technology?

RAG (Retrieval-Augmented Generation) allows AI to provide answers based on your knowledge, not what it 'thinks'.
First, Vragen.ai retrieves the correct information (retrieval) and then formulates a clear answer with source citation (generation). This way, you get the power of generative AI, without fabricated answers, with control over both content and tone.

RAG (Retrieval-Augmented Generation) allows AI to provide answers based on your knowledge, not on what it 'thinks'. First, vragen.ai retrieves the correct information (retrieval), then it formulates a clear answer with citations (generation). This way, you get the power of generative AI, without fabricated answers — maintaining control over both content and tone.

Why RAG technology is important

Many AI tools provide answers, but without a guarantee of accuracy or consistency. That is unsuitable for organizations that demand reliability.

With RAG, you maintain control, transparency, and a consistent tone. Each question also provides insights for improvement.

While other AIs ask for trust, RAG provides evidence. This is ideal for public organizations and knowledge-driven brands.

Many AI tools provide answers, but without a guarantee of accuracy or consistency. That is unsuitable for organizations that demand reliability.

With RAG, you maintain control, transparency, and a consistent tone. Each question also provides insights for improvement.

While other AIs ask for trust, RAG provides evidence. This is ideal for public organizations and knowledge-driven brands.

Enhancing the process for reliable answers

Vragen.ai only provides reliable answers if the foundation is correct. For this, the system needs three things: strong knowledge sources, clear instructions, and feedback from real questions.

1 Configure

2 tests

3 Integrate

4 Analyze

1.0 Configure Retrieval

Learn to search vragen.ai in your content

Everything starts with Retrieval: fetching, enriching, and structuring your knowledge. Here you determine what vragen.ai is allowed to use. The better this step, the more reliable the answers that come out of it. Always based on facts from your own knowledge base.

🔍

Content crawling

Automatically retrieves HTML, PDFs, and API data.

🧩

Smart Segmentation

Divides documents into meaningful knowledge chunks.

🧠

Context enrichment

Adds metadata (e.g., subject, source, date, type).

🧮

Semantic embeddings

Convert text into meaning (vectors) for relevant search results.

🏷️

Source Priority & Filters

Determines which knowledge is leading for each environment or target audience.

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Automatic reindexing

Keep content up-to-date without manual maintenance.

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Rewrite search query

Automatically adjust the user's query to find better results, for example by adding synonyms or extra context.

🧩

Question Breakdown

Breaks down complex or compound questions into smaller sub-questions for more complete and precise searches.

📚

Applying areas of expertise

Determines from which knowledge sources to search, depending on the topic or target audience.

🧠

Semantic search

Focuses on meaning rather than exact words. This allows Vragen.ai to find relevant information using different phrasings.

📊️

Reordering Results

Reorganizes found knowledge snippets based on reliability and relevance, bringing the best information to the top.

✂️

Remove unreliable results

Automatically ignores knowledge snippets whose relevance is too low, ensuring the AI bases its actions only on reliable sources.

1.1 Configure generation

Determine how vragen.ai should respond

Generation is the phase where vragen.ai converts information into language. But unlike generic AIs, every answer is formed within clear boundaries and rules.

🧠

System and agents instructions

You determine the tone, role, and limitations of vragen.ai in natural language.

🔗

Sources

Each answer cites excerpts from the appropriate source.

🛑

Fallback logic

If vragen.ai doesn't know something, users are directed to the right place or person.

2.0 TEST

Test and verify if vragen.ai does what you want

Before going live, you can extensively test, validate, and refine the behavior of vragen.ai. This ensures that every response is accurate, well-supported, and aligned with your policies.

🚧

Test environment

Ask questions in the test environment as customers would and validate if vragen.ai responds according to your instructions.

🔗

Autoplay simulations

Automatically play hundreds of test questions that simulate the behavior of your visitors.

🛑

Annotations & feedback

Evaluate each answer manually or with a rating (“good”, “incomplete”, “incorrect”).

🧪

Ground-truth datasets

Build a dataset with expected answers (the “golden set”) and use it to objectively measure whether vragen.ai consistently performs.

🔀

Compare runs and versions

Test different configurations side by side. For example, two prompt versions or different knowledge selection.

3.0 integrate

Integrate vragen.ai into your website or other channels

Once your system is stable and tested, you can seamlessly integrate vragen.ai into your website, knowledge base, or intranet. Vragen.ai should not be on the sidelines but should become a part of the experience. As if it was always part of your website.

💬

Embed on your website

Add vragen.ai as a widget, chat window, or inline FAQ block. Perfect for assisting visitors directly, without having to click through menus.

🔍

Search bar replacement

Replace the traditional search function with vragen.ai that understands questions and is also proficient in semantic search.

🧱️

API & SDK

Integrate vragen.ai into your own frontend, app, or knowledge portal using the REST API or JavaScript SDK.

🎨

Customize

Adjust the look & feel per brand, department, or website — fully white-label capable.

♿

Accessible & Fast

WCAG-compliant, with caching and CDN for minimal load times.

4.0 analyze and optimize

Continuously optimize with new insights

After going live, the real learning begins. With Vragen.ai, you can see exactly what people are asking, where they're getting stuck, and where knowledge is lacking. This allows you to make targeted improvements. AI performance doesn't deteriorate due to time, but due to change. By continuously measuring and adjusting, your AI remains current and reliable.

📥

Insights Inbox

An overview of frequently asked questions. Your cue to add content or instructions.

📊

Question Analysis & Trends

Discover patterns in questions, recurring topics, and seasonal peaks.

🔁

Feedback loops

Add enhanced answers directly to the ground-truth dataset or reindex relevant sources.

🧮

Quality and performance metrics

Monitor answer rate, citation coverage, and user feedback scores.

📤

Export & reporting

Export data to CSV or your own BI tools for deeper insights.

Ready for the next step?

Vragen.ai gives you control over the full RAG AI technology. From building knowledge to continuous improvement. Not a black box, but a platform that grows with your organization.

Request a demo

06-12150590

Ready for the next step?

Vragen.ai gives you control over the full RAG AI technology. From building knowledge to continuous improvement. Not a black box, but a platform that grows with your organization.

Request a demo

06-12150590

Ready for the next step?

Vragen.ai gives you control over the full RAG AI technology. From building knowledge to continuous improvement. Not a black box, but a platform that grows with your organization.

Request a demo

06-12150590

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