An Agentic Data Collection Platform on AWS
Client Background
The client is a global B2B enterprise intelligence company serving more than 500 enterprise customers worldwide. Its platform combines data collection, analytics, AI-powered decision support, and research, supported by more than 25 years of proprietary longitudinal data. Its commercial value depends directly on the accuracy, coverage, and freshness of the underlying data.
Business Challenge
The existing collection model depended on human throughput across web properties, PDFs, spreadsheets, and image-based documents. As entity coverage expanded, collection speed remained tied to headcount, classification consistency varied between agents, multi-source reconciliation consumed significant effort, and mandatory supervisor review created growing quality-control overhead.
The Solution
CodeNinja designed and deployed a production-grade, agentic data collection platform on AWS. Autonomous agents ingest multi-format sources, extract structured data, identify duplicate candidates, and suggest classification headers against the client’s taxonomy, while mandatory supervisor verification remains in place. The event-driven platform uses Amazon SQS, Amazon ECS, Amazon Textract, and Amazon Comprehend inside the client’s own AWS account.
Measurable Outcomes
- 95% Extraction Accuracy across the source formats in scope.
- 70% Reduction in Manual Intervention on baseline collection tasks.
- 1–4 Minute Average Collection Cycle for a 100-item dataset.
- Mandatory Supervisor Oversight preserved before data enters production.
- Full Platform Handover, including source code, AWS infrastructure configuration, CI/CD pipeline, and documentation.
