Overview of Our Client

Our client is a technology startup operating in the blockchain and cryptocurrency analytics domain. The company focuses on users who require real-time access to data on tokens, wallets, NFTs, and market trends, as well as an intuitive tool for analyzing blockchain ecosystems based on up-to-date information.

The client aimed to deliver an intelligent solution capable of aggregating and processing large volumes of public blockchain data, transforming complex on-chain information into clear and actionable insights for traders, investors, and Web3 enthusiasts.

Challenge

The client faced the challenge of lacking a unified tool for real-time blockchain data analysis. Users had to rely on fragmented sources to track tokens, wallet contents, NFTs, and market trends, which made the analysis process complex and time-consuming.

An additional challenge was handling large volumes of on-chain data and performing complex analytical queries without deep technical expertise. Existing solutions did not provide convenient real-time access to Ethereum and Solana data or allow users to formulate analytical queries in a simple, natural language format.

Primary Objectives

  • Build an AI-powered blockchain consultant that analyzes tokens, wallets, NFTs, and market trends using real-time data from Ethereum and Solana.
  • Enable natural language interaction with large-scale blockchain data through text-to-SQL, making complex datasets easier to explore and understand.
  • Develop an AI agent that can help perform analysis using text2SQL, search, analytics, and reporting tools.
  • Ensure high performance and scalability when handling large volumes of on-chain and market data.
  • Create a flexible foundation for future monetization, including crypto-based subscription models.

Summary of the Project

As part of the project, the SCAND team built an AI-powered blockchain consultant that analyzes tokens, wallets, NFTs, and market trends using real-time data. The solution brings together on-chain data from Ethereum and Solana with AI agents and smart analytics to give users quick access to the latest insights.

Special attention was paid to handling large volumes of data, ensuring architectural scalability, and enabling convenient interaction with the system through natural language queries using text2SQL techniques.

  • Region: Global
  • Industry: Blockchain / Web3 / FinTech
  • Project Type: AI-powered blockchain analytics solution

Solution

As a result, the SCAND team delivered an AI-powered blockchain consultant that brings together on-chain data analysis, market trends, and cryptocurrency news within a single intelligent system. The solution is built on AI agents and a scalable architecture, enabling real-time processing of large volumes of data from the Ethereum and Solana networks.

The platform provides an intuitive way to interact with blockchain data through natural language queries, automates analytical workflows, and delivers structured insights without requiring deep technical expertise.

Key solution features include:

  • Integration of Ethereum and Solana blockchain data using Allium for real-time analysis of tokens, wallets, NFTs, and market activity.
  • Use of AI agents to track blockchain trends, perform analysis, and build reports.
  • Application of text2SQL techniques to handle complex analytical queries over large-scale on-chain and market datasets backed up by a cloud data warehouse
  • Scalable architecture ensuring high performance as data volumes and user demand grow.
  • Support for personalized analytics scenarios and delivery of actionable insights.
  • Readiness for commercial use, including crypto-based subscription models.

Platform Features

  • Scheduled scanning of numerous news portals using browser automation
  • Topic- and keyword-based selection of relevant articles
  • Concise summaries forged for faster consumption of information
  • Storage and retrieval of previously processed articles
  • Instant delivery of updates and reports via a Telegram bot

Technology Stack

We selected the following technology stack to meet the performance, scalability, and real-time analytics requirements of the AI blockchain consultant:

Frontend

Next.js

Backend

  • Node.js
  • Python

Databases

  • Postgres (PostgreSQL)
  • MongoDB
  • Snowflake

Caching

Redis

Blockchain Data

Allium (Ethereum & Solana)

AI & LLMs

  • OpenAI
  • local open-source LLM’s

Vector Database

  • Pinecone

AI & Data Processing

  • Text2SQL
  • AI Agents

Core Team

  • AI Architect: Designed the overall AI architecture, including AI agents, data pipelines, and text2SQL integration.
  • Blockchain Engineer: Responsible for integrating Ethereum and Solana data sources and handling on-chain data processing.
  • Backend Engineer: Implemented the server-side logic, APIs, and data processing workflows.
  • Frontend Engineer: Delivered a user-friendly interface for interacting with blockchain insights and analytics.
  • Data Engineer: Managed large-scale data ingestion, storage, and optimization across multiple databases.
  • QA Engineer: Ensured system reliability, data accuracy, and performance across all components.
  • Project Manager: Coordinated project delivery, timelines, and stakeholder communication.

Impact

As a result of the project, the client obtained a production-ready AI blockchain consultant capable of delivering real-time insights across tokens, wallets, NFTs, and market trends. The platform significantly reduced the time required to analyze blockchain data by consolidating multiple data sources into a single intelligent interface.

The use of AI blockchain agents and text2SQL enabled non-technical users to work with large-scale on-chain datasets, while the scalable architecture ensured stable performance under increasing data volumes and user demand. The solution also laid a solid foundation for commercial growth through crypto-based subscription models and future feature expansion.

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