9AI is an AI-powered platform that streamlines data analysis with automated cleansing, chatbot insights, and real-time integration. It supports secure API sharing and enhanced context through RAG and LLM features.
The Challenge · The Challenge · The Challenge
Develop an integrated, AI-powered data analysis platform that streamlines data management, cleansing, and insights generation while ensuring seamless connectivity with existing systems and providing flexible access to analyzed data.
The ultimate goal is to reduce the complexity of data analysis workflows by offering a centralized platform that combines data uploading, automatic cleansing, AI-driven insights, and API generation capabilities.
Solution
Our team has adopted a strategic approach that leverages both technology and user engagement:
- Streamlined Project Workflow: We designed a flow that allows users to create projects, upload datasets, and access data cleansing recommendations, simplifying the data management process significantly.
- AI-Driven Interaction: The development of a conversational AI chatbot enables users to engage with their data intuitively, fostering enhanced understanding and interactive analysis.
- Robust Integration: We implemented a robust mechanism for syncing data with the contained system, ensuring that purchase orders are efficiently integrated into the 9ai platform for real-time analysis.
- Automated API Generation: We established functionalities that automatically generate APIs and tokens, making it easier for users to share datasets securely without complex setup processes.
- Contextualized Analysis Tools: By allowing the upload of RAG files, we enhance the analytical context for users, enabling them to make better-informed decisions based on enriched data insights.
- Designed an AI-driven summary generation feature that automatically analyzes datasets and provides insights on data structure and content.
- Integrated RAG (Retrieval-Augmented Generation) file support to enhance contextual understanding of datasets.
Build
- Developed a user-friendly interface for project and dataset management, allowing users to create projects and easily upload datasets.
- Enhanced the system with AI capabilities for data cleansing recommendations and interactive chatbot features for data exploration.
INTEGRATION
Contained
Integrated with the contained system to automate the syncing of purchase orders.
API
Developed an API for secure dataset sharing with user authentication.
LLM
Ai generates code for repetitive tasks saving time and effort
Our Approach
The team began with a Proof of Concept (POC) to establish baseline technology choices and core functionalities. Development followed an incremental approach, allowing for continuous improvements that kept pace with evolving technologies and user feedback. Throughout the process, the team maintained close collaboration with stakeholders to ensure regular updates and alignment with business needs. Feedback loops were actively used to refine features and prioritize development efforts based on user requirements and market demands.
TECH STACK
- Backend: Python (Flask), AWS Lambda (microservices)
- Frontend: React + TypeScript (via AWS Amplify)
- CI/CD: GitHub Actions, AWS Amplify
- Version Control: GitHub
- Hosting & Infrastructure: AWS (EC2, S3, Amplify, Lambda)
- Email/Notifications: AWS SES
- AI compliance automation (multi-region)
- Blockchain audit trails
- AI Models:
- Claude (for code generation & summarization)
- GPT-4o-mini (for agent processing & classification)
- o1-mini (for hybrid retrieval tasks)
- Frameworks: LangChain, LangGraph (with LangSmith logging)
- Advanced AI insights
- Certifications & compliance initiatives
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