AI agents in the neuland.ai HUB
A prompt belongs to one person.
An agent captures what makes a good request: instructions, knowledge, tools, and model. Once tested and shared, it gives everyone on the team the same result, backed by sources.
Jeder formuliert seine KI‑Anfrage anders. Also bekommt jeder ein anderes Ergebnis.
One person writes three lines, another half a page; one attaches the policy, the other doesn't. An agent ends this: it works for every person to the same specification, with the same knowledge and the same permissions.
Define
Your team sets these four inputs once, plus an input form if needed. Anyone who uses the agent afterward only writes what they want checked.
Test
A new version of the agent first runs in the Playground against real contracts, version 3 and version 4 side by side. Only when the results are right does the new version apply to everyone who uses the agent.
Old and new side by side
The live comparison shows the same input in both versions. You see deviations before anyone else does.
Every version can be restored
The version history records what changed and when. An earlier version is active again in one click.
Tested with your contracts
Tests use contracts whose review outcome your organization already knows. That way, every deviation shows a real difference.
Share
Version 4 goes to procurement, data protection, and IT security. From today, all three review with the same version, no one with a copy of their own.
Procurement: before signing
Procurement uploads a new supplier's DPA to the form and has the note with citation before signing.
Data protection: right in the chat
The data protection officer brings the Vertragsprüfer AVV into her chat on a third-country transfer with “/”; the context stays in the same conversation.
Organization: via the Marketplace
If the agent proves itself, you make it available to everyone via the Marketplace. Every new department starts with version 4.
Example · Agent chains
With “/”, you bring any agent available to you into the ongoing conversation. An example: the Vertragsprüfer AVV reviews, the Datenschutz Navigator assesses the third-country transfer, the Corporate Mail Writer drafts the response. Nothing is sent until procurement agrees.
Industrie AG
Task: /Vertragsprüfer AVV reviews the Spedition Keller DPA, then /Datenschutz Navigator and /Corporate Mail Writer
/Vertragsprüfer AVV has reviewed § 6
/Datenschutz Navigator has assessed the transfer
/Corporate Mail Writer has drafted the response
Email to Spedition Keller
Spedition Keller receives the response after procurement approves it.
Each agent uses only its own tools: read SharePoint and Confluence, write the email only after the OK.
Agent Library
Several hundred pretrained agents. Adopt them and adapt them to your requirements.
From the Vertragsprüfer AVV to the Onboarding Coach: several hundred pretrained agents in ten industries. You adopt one and adapt its instructions and knowledge to your requirements.
Limits
Admins decide once for the organisation which locations, models and tools are enabled. Your team then decides per agent what it reads, what it prepares and what it never does alone.
Permissions
You define tools, data spaces, and recipients for each agent, granular and versionable.
Knowledge
The agent reads only the knowledge bases assigned to it; in SharePoint, the permissions of the person using it also apply.
Writing
Emails, meetings, and data changes wait for a human OK, in agent chains too.
Log
Every tool call of the agent is in the history, with arguments, response, and duration.
FAQ
Your most frequent request.
Your first agent.
During onboarding, our Customer Success team supports your first agent: on your documents, tested in the Playground, shared with the departments that need it.
After your request
01
You name the request that comes back every week
02
You see in the neuland.ai HUB how an agent from the library handles such a request
03
You decide which departments it starts with