Audit before automation
The first step is mapping document types, manual decisions, approval gates, systems, outputs and measurable failure cases before recommending a build.
About
DocBeaver provides professional services for controlled AI document automation: custom AI agent development, AI integrations, document extraction, validation rules, review workflows, traceability and business-system handoff.
Founder note
I remember well,
how I was inspired by the idea of a clever document automations with AI almost a year ago. By that time big SOTA LLM models showed such a huge jump in performance and capabilities, that - we might accept it or not- it was clear to me:
We live in an era, that changes how our businesses work.
So, I literally started to play around with these technologies whithin my personal environment first. In October 2025 I have built a desktop AI assistant called Alfy (after the Batman's Alfred Pennyworth, as he is precisely that sort of personal assistant, that I would like to have in my own life). It understood my enquiries about documents, locally stored on my laptop, attached via email, or on Goggle Drive - wherever these pdfs/docx existed, - Alfy could extract them, sort, save in any location, summarize and even split/merge them on-the-go with a single click.
And just a few weeks later I have read in the news, that the guy named Peter Steinberger created OpenClaw, AI Agent that basically did the same, but with much broader permissions and features. I realized I wanted to build agentic systems, that would be safe, deterministic, while leveraging incredible reasoning capabilities of AI models. That was totally possible via existing frameworks, such as LangGraph. And this is how it went: well-designed AI workflows process hundreds and hundreds of documents near zero-error, fully observable and under human control.
That is the future. And it is happening now.
Delivery stance
Built for document-heavy operations that need control
The work is strongest where teams already have repeatable document flows, clear review responsibilities, measurable manual effort and a need for dependable outputs inside existing systems.
Source-grounded outputs
Reviewers should be able to trace extracted values, summaries and generated outputs back to the originating document, email, page, table or attachment.
Human approval where it matters
Regulated, financial, client-facing and low-confidence outputs remain behind review gates until a responsible user approves release.
Integrate with current tools
DocBeaver designs workflows around existing repositories, email, spreadsheets, CRM, ERP, SharePoint, Drive and internal tools instead of forcing a platform migration.