AI agents and document automation
WATCH THE PROCESS
An idea becomes a working connection.
Scroll or choose a step to follow the journey.
Your request
We clarify the task, the people involved and the desired outcome.
Apply AI to knowledge retrieval, request classification and draft documents. Staff approve consequential actions.
Give the agent a task you can check
An agent can retrieve company information, extract invoice fields, route an inquiry or draft a proposal. Before development, we define an acceptable result and what should happen when information is missing. A single successful answer does not establish a dependable workflow.
Company knowledge and permissions
We review the documents the agent may use and who is allowed to see them. Employees should not receive information they could not access in the underlying system. Model choice, data transfer and storage are discussed before implementation. Outdated and conflicting documents need attention first.
Work that can be included
Assistants grounded in company knowledge
Extract document data and prepare draft responses
Integrate CRM and human review steps
Make approval meaningful
A draft can reach the reviewer with its supporting sources. Consequential actions require approval before information is sent or system records are changed. We test the agent against your examples and record failure cases to determine which tasks it can handle.
Assessing your use case
Share an anonymised document or inquiry and describe the result an employee currently prepares. This gives us a basis for estimating the prototype and its connections.
Frequently asked questions about AI agents
What is an AI agent in a business context?
An AI agent is software that performs repetitive work with documents and data according to agreed rules: it reads invoices or inquiries, extracts information, enters it into systems and prepares draft replies. People review the result instead of doing everything manually.
Which processes are worth automating with AI?
High volumes of similar documents or requests work best: invoice and order processing, email classification, moving data between systems, drafts of proposals or reports. We start with one process and expand once it runs reliably.
How do you ensure data security?
Data is processed in your own or an agreed infrastructure, access is limited by role, and sensitive data is not shared unnecessarily. With every client we agree which data may be sent to AI models and which must stay internal.
How accurate are AI agents?
Accuracy depends on document quality and process clarity. We design agents to hand unclear cases to a person for review rather than guess. In the first stage we measure accuracy on real data and only then widen the scope.
How long does it take to implement an AI agent?
The first working process usually launches within 3–6 weeks: we map the process steps, prepare integrations, test with real data and hand over. Further processes are added in stages.
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