Price: 0
Number of applications: 3
16.03.26 (inclusive)
By agreement
MVP
ICT tasks
Media sphere
Intelligent control systems
Mobile app
Conditions: Budget: up to 120,000 rubles (payment is made in stages over the weeks). Duration: 4 weeks. Work through my GitHub (daily commits). The main criterion: Experience working with RAG and long legal texts.
, FINAL TOR FOR 1 MONTH (For the contract) Sprint 1: Data entry and OCR (7 days) Functionality: Telegram bot accepts PDF (text or scanned). Technology: Using Marker or PyMuPDF + Tesseract/EasyOCR to clear text from "junk". Result: The bot outputs structured JSON: the case number, the court, the parties, and the operative part. Sprint 2: Legal Intelligence / RAG (7 days) Functionality: Search for "leads". The model compares the solution with the articles of the CPC/APC and the Plenum database. Technology: Vector search in the database of scientific information. Industrial engineering: "Find 3 violations of procedural law." Result: A message in the bot: "Chance of cancellation: 75%. An error was found in art. 330 of the CPC." Sprint 3: Document generation (7 days) Functionality: Assembling an appeal using a template. Technology: python-docx library. The use of masks (Plaintiff, Defendant, Arguments). Result: The "Download .docx" button. The file is ready for minimal editing by a lawyer. Sprint 4: Debugging and Prediction (7 days) Functionality: Setting the final accuracy. Assembling error logs. Result: The system has been tested on 20 real cases. The accuracy of the argument has been confirmed by a lawyer. Preparation of a demo video for the investor.
Ilshat
Purpose and description of task (project)
Create a core system for analyzing court decisions and generating appeals in 30 days. Stack: Python, LangChain/LlamaIndex, Vector DB (Chroma/Qdrant), YandexGPT/GPT-4o API. What needs to be done (MVP): OCR module: High-quality parsing of PDF scans (court decisions). RAG-pipeline: Indexing the database of laws and Plenums of the Armed Forces for accurate references. Reasoning: Analyzing the referee's mistakes and calculating the odds (Predict). Docx generator: Output of the finished appeal in Word.
Note
Send examples of your AI bots/projects with documents to BOS. @Fghhhh556