Блог

Статья | 14 April 2026

Russia’s AI Regulation Bill: Overview and Proposed Improvements for Neural Network Governance

Russia is preparing its first comprehensive AI regulation bill. The draft introduces trusted AI models, synthetic content labeling rules, and citizen rights protections. However, it also contains controversial provisions — from broad cross-border AI restrictions to conflicts with existing IP law. This article reviews the key clauses and offers practical legal amendments.
Статья | 08 April 2026

Turn your law firm website into a lead generation machine with an AI compliance checker. This lead magnet scans business websites for 152-FZ and 38-FZ risks, generates a report, and helps convert visitors into clients. Build it fast with Botman.one — no code needed.
Статья | 06 April 2026

How to Use Botman.one to Build Client Acquisition Services for a Law Firm Website and Increase Traffic

Want more clients for your law firm? With Botman.one you can quickly create AI-powered services such as automated legal consultations, document generators, and contract review tools. These services increase website traffic, improve SEO, and turn visitors into paying clients.
Статья | 01 April 2026

Why Many Companies Prefer On-Premise Solutions Instead of Cloud Platforms

Legal and HR departments handle highly sensitive data that many companies cannot store in the cloud. On-premise automation ensures full control, compliance, and security. Botman.one can be easily deployed on your own servers with support from the Botman.one team—making automation reliable and enterprise-ready.
Статья | 31 March 2026

How to Quickly Create a Contract Template with Claude Cowork and Build a Contract Generator in Botman.one

Claude Cowork can turn a plain contract into a professional DOCX template with legal design formatting and Botman.one markup in minutes. In this article, you’ll learn how to generate the template, fix slashes in Word, and build a contract generator in Botman.one without manual markup.
Статья | 30 March 2026

Why Task Decomposition Matters When Working with LLMs: Accuracy, Control, and Cost Efficiency

Why does a single large prompt often lead to weak results? This article explains how breaking tasks into smaller steps improves LLM output quality, reduces costs, and turns AI generation into a controlled workflow. We also explore how Botman.one enables prompt chaining and multi-LLM orchestration using a low-code approach.