Agentic Automation for Vertical Intelligence Platform
A leading global vertical intelligence platform serving enterprise customers across multiple international markets engaged CodeNinja to transform a labor-intensive data collection operation into a scalable agentic intelligence system.
The existing process relied on teams of human collection agents manually gathering structured intelligence from web pages, PDFs, HTML sources, and image-based documents. Every record required supervisor validation before entering production systems, making throughput, coverage, and scalability dependent on human capacity.
CodeNinja designed, built, and transferred a fully agentic collection layer powered by LangGraph stateful orchestration, Playwright-based browser automation, Model Context Protocol (MCP) integrations, and a multi-model reasoning architecture. Deployed within a sovereign AWS environment under the client's direct ownership, the platform autonomously performs source discovery, data extraction, duplicate detection, normalization, and submission preparation across diverse content formats.
Human oversight remains embedded by design. Supervisor review and final submission approval are maintained at every collection cycle, ensuring governance, quality assurance, and operational control while dramatically reducing manual effort.
Outcomes at Production Scale
- 95% extraction accuracy across web, PDF, HTML, and image-based sources
- 70% reduction in manual collection effort
- Collection cycle times reduced to 1-4 minutes per 100-item dataset
Upon engagement completion, all infrastructure, orchestration pipelines, model configurations, deployment assets, documentation, and operational knowledge were permanently transferred to the client, ensuring complete ownership and long-term operational independence.
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