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Invendora: AI 驱动的 B2B 搜索平台

一个 AI 驱动的 B2B 平台,为电子商务和供应链企业自动化产品和供应商管理,利用 GPT 实现会话式产品查询和上下文推荐。

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11+
Technologies
7+
Key Features
Web
Platform
Invendora project screenshot

核心功能

集成 GPT 的 AI 驱动智能搜索来自全球市场的自动化数据抓取集中式产品与供应商管理高级搜索与持久筛选器管理面板与分析仪表盘电子邮件与通知系统

技术栈

Node.jsPostgreSQLChatGPTVector DatabaseLLM Prompt EngineeringElasticsearchReactPuppeteerCheerioApifySendGrid

我们的贡献

我们的贡献

我们开发并实施了 Invendora AI SaaS 平台,其特点包括:

  • AI 驱动的智能搜索:集成 GPT 实现会话式产品查询和上下文推荐
  • 自动化数据抓取:使用 Puppeteer、Cheerio 和 Apify 从全球供应商市场提取产品
  • 产品与供应商管理:构建了集中式目录、类别组织和批量上传功能
  • 高级搜索与筛选:实现了持久的全局筛选器和多条件搜索选项
  • 管理面板与分析:开发了用于用户管理、筛选器、类别和运营洞察的仪表盘
  • 电子邮件与通知:集成 SendGrid 以实现可靠通信
  • 可扩展基础设施:具备强大身份验证和性能优化的云就绪架构
  • 部署与维护:用于无缝更新和持续交付的 CI/CD 流水线

成果

Successful MVP launch with initial B2B user onboardingFaster and more accurate business and vendor discoveryAI-powered insights enhancing sourcing and procurement decisionsCentralized vendor and catalog management reducing manual effort

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可扩展的云基础设施
Scalable and secure enterprise-grade architecture
Future-ready platform with ongoing integrations

常见问题

MicrocosmWorks built Invendora's search using ChatGPT for conversational product queries combined with Elasticsearch for structured filtering and a vector database for semantic matching. Instead of keyword-based catalog browsing, buyers describe what they need in natural language and the AI returns contextually relevant products with explanations of why each matches. This approach surfaces products that keyword search would miss, especially for complex specification requirements.

MicrocosmWorks built a web scraping pipeline using Puppeteer, Cheerio, and Apify that crawls supplier websites, extracts product specifications, pricing, and availability data, and normalizes it into Invendora's unified schema. The pipeline runs on scheduled intervals with change detection to keep product data current. Extracted data is stored in PostgreSQL with vector embeddings indexed for semantic search, ensuring the catalog stays comprehensive and up-to-date.

Yes, MicrocosmWorks implemented a recommendation engine that analyzes purchase history, search patterns, and product affinities using the vector database. When a buyer searches for a product, the system cross-references their procurement profile to surface complementary products, preferred vendor alternatives, and quantity-based pricing tiers. LLM prompt engineering enables the AI to explain recommendations in the context of the buyer's specific use case.

MicrocosmWorks integrated SendGrid for automated email workflows between buyers and vendors. When a buyer expresses interest in a product, the platform generates a structured inquiry with specifications and quantity requirements, routes it to the appropriate vendor contact, and tracks the response pipeline. Vendors receive qualified leads with buyer context, while buyers get centralized communication tracking across all their product inquiries.

MicrocosmWorks built Invendora's core platform including the AI search engine, web scraping pipeline, vendor management system, and buyer-facing interface. At MicrocosmWorks development rates of $20-$40/hr, a similar AI-powered B2B search platform typically costs between $20,000-$45,000 for the initial build, with ongoing costs for scraping infrastructure, AI API usage, and platform maintenance available through our monthly support plans.