Blockusign.ai

Inspiration

As part of an open-source organization collaborating with sponsors, we often face lengthy and confusing processes while signing MoUs and agreements. Managing multiple deadlines and contracts is overwhelming, and missed deadlines often lead to setbacks.

To explore solutions, we spoke with industry experts and startup founders, only to discover they shared the same struggles. This highlighted a significant gap in the market and the urgent need for a streamlined approach.

Inspired by this, we set out to create a platform that simplifies agreement workflows, saving time, money, and opportunities while addressing a critical industry challenge. Our project isn’t just a tool—it’s a way to save time, money, and opportunities while bringing order to a disrupted system. This vision inspired us to create a smarter, more efficient way to handle agreements, and we’re excited to see its impact.

What it does

Project Functionalities

Our project offers a comprehensive suite of functionalities designed to streamline agreement workflows:

Agreement Generator: Create proposals using customizable legal document templates with the assistance of an AI chatbot that collects necessary information.
Collaborative Workspace: Share contracts with clients, discuss terms and conditions, and provide comments to clarify ambiguities during the negotiation phase.
Document Analysis: Utilize AI-based analysis to extract important details, deadlines, and terms & conditions from agreements, identifying favorable and unfavorable terms to aid negotiations.
Secure Signing: Sign agreements using cryptographically secured signatures to prevent signature forgery.
Fraud Prevention: Creates proof of the signed contract and posts it on the blockchain to prevent tampering and fraud.
Deadline Management: Maintain a scheduler that reminds users and clients of important deadlines and tasks related to agreements.
AI Chatbot: Access an AI-powered chatbot capable of answering queries about terms and conditions from multiple contracts, streamlining the information retrieval process.

These functionalities work together to optimize the agreement process, enhancing efficiency and reducing the complexities associated with traditional workflows.

How we built it

Our project is a RAG-based agentic legal document workflow management system. We utilize AI agents to generate drafts, along with text classifiers and LLM models to summarize and analyze agreements for easier use during negotiations.

Technology Stack :

Frontend: Built using Next.js, providing a responsive and user-friendly interface.
Backend: Implemented in Node.js, ensuring efficient handling of requests and data management.
Database: User data is stored in MongoDB for scalable and flexible data management.
APIs: We use DocuSign APIs for OAuth, user signatures, managing folders, and sending agreements as envelopes for clients to sign and proceed.
Security: We have integrated cryptography to enhance tamper and fraud prevention.

Challenges we ran into

During the development of our project, we encountered several challenges:

Token Limitations: We faced difficulties processing a large number of tokens with the LLM model for agreement analysis due to limitations in the free model.
Chatbot Performance: The AI agent's ability to retrieve relevant text for the chatbot was not functioning optimally, leading to inefficiencies in information retrieval.
Template Collection: We struggled to collect suitable legal document format templates, which impacted the initial stages of our agreement generation process.
DocuSign API Issues: We encountered challenges in understanding and effectively working with the DocuSign API, which complicated the integration of signature and document management features.

Accomplishments that we're proud of

Token Limitation Solution: We resolved token limitations with recursive token splitting, allowing comprehensive responses across API calls.
RAG AI Model Integration: We integrated a RAG AI model with Langchain and a vector database to enhance document analysis and retrieval.
DocuSign API Integration: We successfully integrated DocuSign APIs for OAuth, folder management, and user signatures, ensuring a seamless experience.
Cryptographic Security Algorithm: We developed an effective algorithm to secure both signatures and agreements cryptographically and post them on the blockchain, ensuring integrity and trust.

What we learned

AI Agents and Models: We learned about AI agents, selecting the right LLM model, and crafting precise prompts to minimize hallucinations. We also discovered how to blend AI agents with text classifiers and RAG models effectively.
Cryptography and Blockchain: We gained insights into cryptography and blockchain technology, enhancing our understanding of secure digital transactions.
Market Analysis: Analyzing the market helped us understand user needs and pain points, guiding us in designing an effective user experience.

These lessons have strengthened our approach and equipped us to improve our legal document workflow management system.

What's next for Blockusign.ai

Our next goals focus on enhancing functionality and user experience. We plan to implement an advanced analytics dashboard that provides insights into agreement workflows, tracking key metrics such as turnaround times and negotiation patterns. This feature will empower users to make data-driven decisions. Additionally, we aim to expand integrations with popular project management tools to facilitate seamless collaboration and document sharing. Introducing customizable workflow templates will also allow users to tailor the agreement process to their specific needs, improving efficiency and satisfaction.

We are excited about the potential of this project and eager to take it to market. Our curiosity drives us to explore its impact and discover our place in the industry. With a strong startup vibe, we are committed to addressing real-world challenges in legal document management and look forward to making a meaningful difference in the market.