Internal knowledge search
The agent answers questions using approved documents and shows the sources behind each answer.
Agents for companies
AI agents for knowledge and recurring processes
We connect approved documents and existing systems to an AI agent. It researches, prepares drafts and plans work steps. Critical actions remain under human control.
SourcesDocumentsWikis · SOPs · Quotes
ToolsSystemsTickets · Projects · APIs
Limited taskAI agentSearches · compares · uses permitted tools
ControlApprovalBefore effective actions
ResultTraceableSources · Logs · Tests
- Limited task
- Approved data
- Human control
- Measurable results
Use cases
Tasks with context but no fixed solution path
An agent is useful when information is spread across systems and the next sensible step depends on the current result. Fully fixed processes belong in conventional automation.
Prepare quotes and emails
Drafts use previous quotes, style guidelines and the current case. A person reviews and sends them.
Assemble project context
Decisions, tickets and documents from several approved systems are brought together for a specific question.
Onboarding and SOP access
New employees find processes, responsibilities and work instructions without asking individual colleagues for every detail.
Processes with approvals
The agent researches and prepares actions. Changes and external actions remain blocked until a person approves them.
The right architecture
Not every automation needs an agent
We first check whether a simpler approach can produce the same result more reliably. An agent only makes sense when it must choose between permitted next steps.
Agents and workflows in detailRules determine the process
A good fit for stable processes with known steps, clear inputs and defined exceptions.
- Predictable sequence
- Easier to test
- Lower operating effort
The result determines the next step
Useful when research, tool selection or follow-up questions vary with each intermediate result.
- Limited set of tools
- Logged decisions
- Approval before risky actions
Process
Read and test first. Expand only when the evidence supports it.
The first version does not change production data. This lets us test quality and limits before an error can have real consequences.
- 01
Define the task and success criteria
We select a limited use case and use real completed cases to define what a useful result looks like.
- 02
Limit data and permissions
Sources, user roles, permitted tools and approval points are defined before technical implementation.
- 03
Test the agent in read-only mode
The first version searches, compares and prepares drafts. It does not change production data.
- 04
Measure the results
A fixed test set checks quality, sources, failure cases and the human intervention required.
- 05
Expand operations carefully
Additional data sources or limited actions follow only after evaluation. Every extension receives its own test.
Data and integration
The agent receives only the access it needs
Data sources and tools depend on the task. Sources can include document stores, wikis, ticket systems, project platforms and approved APIs.
DocumentsWikisTicketsProjectsAPIs
Operational controls
- Roles and access rights for each data source
- Approvals for changes and external actions
- Limits for runtime, cost and tool calls
- Logs for inputs, actions and results
- Repeatable tests before and after changes
Limited pilot
A real task instead of a general demo
Scope, data access and success criteria are recorded before the pilot starts. The result supports a technical and commercial decision.
Discuss a pilotOne defined use case
A task from your daily work, not a general assistant demo.
Representative test cases
Expected results, failure cases and stop criteria are defined before evaluation.
Controlled data access
The pilot starts with only the sources and permissions needed for the task.
A decision for the next step
The evaluation shows whether to stop, adjust or move the agent into operation.
Further reading
Technology, project selection and our own experience
What is agentic AI?
How agents choose tools, when a fixed workflow is the better fit and which limits are needed before use.
Read articleAI readiness in industry
A practical assessment of process, data, integration, risks and later operation.
Read the readiness checkAI Mux for coding agents
Our development log shows how we coordinate several agents and make requests for human attention visible.
Read development logSchedule Your Free Consultation Today
Book a free consultation and discover how we can help you achieve your business goals.
Gießen office: Flutgraben 4, 35390 Gießen
Visits by appointment, Mon-Fri, 09:00-18:00
Registered office and postal address: Auf der Grube 9, 35041 Marburg
Carsten Schmidt
CEO