300%Increase in email response rates for some customers
2xOutbound account penetration reported by a customer
90%+Data accuracy perceived by users
DAS PROJEKT IN KÜRZE
Loyee.ai is an AI-powered B2B sales intelligence platform that helps teams identify, prioritize, and engage their best-fit leads. It analyzes large datasets to detect buying signals, enriches and segments leads, and automates personalized outreach. Customers report 300%+ email response rate increases, higher engagement, and more effective outbound campaigns.
- KUNDE
- Loyee Inc
- BRANCHE
- Technology
- DAUER
- Multi-month engagement from PoC to scalable production system
- DAS TEAM
- 1 Delivery Lead, 1 Software Developer
01 / Loyee Inc
Die Herausforderung.
- Parsing inconsistent SEC filings (10-K, 10-Q, 8-K) with highly variable HTML/XML structures, tables, and footnotes.
- Scaling real-time processing of 50,000+ quarterly filings without exceeding AWS Lambda concurrency limits.
- Overcoming LLM context window limits (e.g., 128k tokens) when filings can exceed that size and still require precise question answering.
02 / Loyee Inc
Unser Ansatz.
- Built an automated data pipeline to fetch filings from the SEC EDGAR system, normalize them, and store them for analysis.
- Used OpenAI NLP models to parse complex financial text, extract key metrics, and tag relevant sections.
- Implemented Weaviate as a vector database to enable semantic search and RAG-style question answering.
- Architected microservices with NestJS plus Python scripts on AWS Lambda, orchestrated with queues to handle large volumes.
03 / Loyee Inc
Was wir entwickelt haben.
- An AI-driven SEC financial report analysis platform where users:
◦ Ask natural language questions about companies or metrics.
◦ Receive precise, context-rich answers linked to specific report sections. - React.js frontend presenting insights with deep links into original filings.
- Highly scalable, serverless backend processing tens of thousands of filings.
04 / Loyee Inc
Die Wirkung.
- Reduced time for complex financial analysis from hours of manual reading to seconds.
- Achieved 90%+ perceived data accuracy in query responses.
- Enabled customers to drive 300% email response increases, 30% higher engagement, and 2x account penetration in some outbound efforts.
HINTER DER UMSETZUNG
Die Technologie.
- React
- NestJS
- Node.JS
- Python
- Weaviate
- OpenAI API
- AWS Lambda
NÄCHSTES PROJEKT / VNR Verlag / Platform X