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KNOWLEDGE CONNECTED TO AI

Your AI.
With the memory
of your company.

Turn your documents into context for the AI you already use. Answers with the source, so you can check and move on.

Your documents. Your context. The origin in view.

The knowledge stays in Next.
The conversation continues in your AI.

MCP over HTTP Your documentsYour assistant

See it in 15 seconds

The same question, three different answers. With Next, AI answers with what your company knows.

01 / FROM QUESTION TO SOURCE

A good answer has somewhere to start.

Explore what changes when your AI has the company's context.

A conversation with contextIllustrative example
You

How many days can I work from home?

ANSWER WITH CONTEXT

The policy allows 3 days of remote work per month. On Tuesdays, work is on-site. [1]

Remote work policyExample document · section 2
“Up to 3 days of remote work per month are allowed. On Tuesdays, work is on-site.”
Pick a topic and open the source to check the excerpt.

Illustrative example with fictional documents. The demo does not query real accounts or documents.

02 / LESS SEARCHING. MORE CONTEXT.

From file to conversation. A connected path.

A knowledge layer between your documents and your AI.

  1. 01

    Gather what your company knows.

    Organize the documents your team needs to consult, preserving the origin of each piece of information.

  2. 02

    Bring the context to your AI.

    After the index is prepared, an MCP-compatible client queries the authorized knowledge.

  3. 03

    Find it. Check it. Continue.

    Read the answer, see the source excerpt, and go back to the document to understand the context.

CONTEXT WITH CLEAR BOUNDARIES

Connected to the company. Respecting every access.

Personal and company knowledge have boundaries. Each query respects the asker's permissions.

Understand the approach

LGPD and GDPR compliant

03 / GET TO KNOW NEXT

Before your next question.

The essentials about knowledge, sources and AI queries.

What is Next?

Next is a knowledge platform that connects company documents to AI through clients compatible with MCP over HTTP. Each query brings references to the origin and respects authorized access.

How does RAG help query documents?

RAG combines information retrieval with answer generation. The relevant document content is retrieved to support the AI's answer. In Next, references to the origin help you check the context.

Is Next just another chat?

The knowledge stays in Next and can be queried from the AI you already use, through a compatible client. MCP is the protocol that connects the query tools to the assistant.

How do I check an answer?

Check the reference to the document and the excerpt used in the answer. In the demo on this page, open the source card to read the fictional passage. The source helps verify the information; on its own it does not guarantee an answer is correct.

Can an uploaded file be queried right away?

The file must go through index preparation before it can be searched. Saving a document and making it available for queries are distinct steps.

Who can query the documents?

Each query respects the permissions of whoever asks. Personal and company knowledge keep their access boundaries.

How do I start using Next?

Go to Next signup to create your account and review the available conditions. To learn the path from question to source, explore the demo on this page first.

THE KNOWLEDGE IS ALREADY YOURS.

Take what you know into your next answer.

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