Reviewing hundreds of pages of contract documents, correspondence, and court orders is part of the daily bread of lawyers. Often, however, this is a manual, time-consuming process. In this application example, Wolfgang Richter shows, using a real private case against Telekom, how PyleHound revolutionizes this process.

Key Takeaways

• Massive time savings: Analyzing extensive file inventories and creating arguments takes only a fraction of the usual time (approx. 10%).
• Semantic search: PyleHound finds relevant text passages based on context, not just through exact keyword matching.
• Seamless workflow: From project creation to document upload via drag-and-drop to the finished lawyer's letter in one platform.

How does PyleHound accelerate the analysis of extensive file repositories?

PyleHound drastically reduces manual research effort by making large amounts of unstructured data (PDFs, Word documents) readable and analyzable in seconds. Instead of wading through files for hours, lawyers can interact directly with the file content.

In the shown example, approx. 50 documents regarding a legal dispute were imported. What would have taken hours manually – sifting through debits and contract details – the software handled in a few moments. The result: An estimated time saving of 90% compared to the conventional way of working.

How does the workflow from file to argumentation work?

The process in PyleHound is intuitively designed and guides users in a few steps from the raw document to the finished legal argumentation:

1. Project creation: A new project (e.g., "Telekom lawsuit") is created.
2. Document import: All relevant files are simply dragged and dropped into the "Knowledge Base". The system processes formats like PDF and DOCX immediately.
3. Semantic query: Via the chat function, you ask a specific question to the file (e.g., "Collect all passages having to do with the conclusion of the contract").
4. Curation: PyleHound provides quotes with source citation. Lawyers select the most relevant quotes ("Select Quotes").
5. Argumentation creation: With a further prompt (e.g., "Write from the perspective of a lawyer why no contract came into existence"), the AI generates a precise text draft based on the selected facts.

What distinguishes the search in PyleHound from a simple keyword search?

The search in PyleHound is based on semantic understanding, whereby the software grasps the context and meaning of a request instead of just scanning for identical character strings.

As Fabian Rittmeier explains in the video, the user does not have to hit exact keywords. If you are looking for arguments against a conclusion of contract, PyleHound also finds passages containing the context of "unjustified debits" or "missing signatures," even if the word "conclusion of contract" does not explicitly appear there. This minimizes the risk of overlooking decisive evidence.

How precise are the legal texts generated by the AI?

PyleHound creates legally sound drafts directly based on the actual content of the uploaded documents. Since the AI (the LLM) has access to specific quotes from the file, it does not hallucinate facts but builds the argumentation logically on existing evidence.

In the example, the tool generated a structured argumentation outlining why, due to lack of signature and valid declaration of intent, no contract with Telekom came into existence. This draft serves as a high-quality basis that lawyers only need to polish finally.

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Conclusion

The demonstration impressively shows: PyleHound is not just a search engine, but an active thought partner. It transforms a confusing pile of files into structured knowledge and finished text modules. For law firms, this means: More focus on strategy and client counseling, less time loss through searching and sorting.

Do you also want to accelerate your file analysis by 90%? Test PyleHound.

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Transcript

00:00 [Wolfgang Richter]: I have restarted PyleHound here in this context to simply show how to make quick progress here. I am creating a new project, clicking here on the project part.

00:33 [Wolfgang Richter]: Here I enter the matter. This is a situation I had privately, where I struggled with Telekom. They debited money from my account for years, even though I had not concluded a contract. I entered into a legal dispute with them. So now I have a whole lot of documents.

01:03 [Wolfgang Richter]: I go to "Add Knowledge Base". Here I can now drag-and-drop. I get this from my prepared documents. So there are lots of documents packed in here now – court information, highly varied information on this.

01:28 [Wolfgang Richter]: Now I click on Import. These are 50 files, they have all run into the area here now and can therefore be processed now. If I say now I want to process this, I click on "New Conversation".

01:45 [Wolfgang Richter]: I see the name of the project "2 Telekom" down here. I see the conversations that are in here. Now I can enter what I want to ask here. I have already prepared this so that we don't lose time while I type.

02:10 [Wolfgang Richter]: The prompt reads: "Collect all passages having to do with the conclusion of the contract with Telekom, i.e., both the argumentation of Telekom and that of the opposing side – i.e., mine." Now I send this off.

02:20 [Wolfgang Richter]: Now PyleHound is working in the context and writing down here what it is currently doing.

02:27 [Fabian Rittmeier]: Maybe I'll say a few words about what is happening here right now. PyleHound has now independently accessed all project files in the background and is thoroughly searching all these files for the quotes Wolfgang is looking for at this point. This is a semantic search. That means we don't have to enter individual keywords correctly here, but PyleHound actually finds the correct search spots from the context, out of the sentences.

02:58 [Wolfgang Richter]: Here you can see now where it is quoted from in each case, i.e., from the respective documents. Here I can also select a bit more, throw out what doesn't interest me. If I now click on "Use Selected Quotes" – i.e., those that remain in here – then there is a presentation here in the flow, in the execution.

03:23 [Wolfgang Richter]: Now you see the text that results from the compilation here. I had already looked at this before, these are indeed the relevant contexts listed here.

03:54 [Wolfgang Richter]: If I now enter my next prompt here, namely: "Now write me from the perspective of a lawyer why no contract came into existence here in this context", then it prepares the essential arguments now.

04:14 [Wolfgang Richter]: Since I know the case well, I know by now that all essential arguments have indeed been gathered here. This has already been a larger process now.

04:30 [Wolfgang Richter]: At the speed at which this has occurred here – even with the substantive certainty – I was effectively operating at about 10% of the time I would otherwise have needed to review the documents, attempt the compilation, and structure it accordingly.

04:51 [Wolfgang Richter]: One could refine this everywhere now, one could write in: "Show again exactly the documents having to do with the respective debits". All this could be cited in the further context. But I believe for the demonstration this is of no further importance. We have run through once now and have seen what it is like when I have documents in my database that I now want to see analyzed.