Closing the loop on institutional waste.
"Turn every waste incident into a verified environmental improvement."
The Operational Premise
Colleges, corporate campuses, and residential municipalities produce thousands of tons of recyclable and compostable waste every month. Yet over 60% of recyclable volume is lost to landfill diversion due to lack of immediate reporting, cross-contamination, and sluggish custodial dispatch.
GreenLoop AI creates a continuous closed loop:
1. Report it — Geotagged community reporting with photo evidence
2. Understand it — Server-side Gemini AI multi-modal material triage
3. Resolve it — Dynamic field task assignment & routing
4. Prove it — Dual before-and-after photographic verification
5. Measure it — Empirical diversion metrics & zero greenwashing
Enterprise Cloud Architecture
Engineered with serverless cloud primitives for horizontal scalability, least-privilege security, and sub-second cold starts:
Amazon API Gateway routes traffic to secure AWS Lambda functions with IAM least-privilege roles.
Single-table key schema optimized for fast spatial queries, status lookups, and append-only audit events.
Client uploads directly to isolated S3 buckets via time-limited presigned URLs with MIME type enforcement.
Server-side structured schema inference identifying polymers, hazardous e-waste, and facilities handling tips.
Operational Principle:
"Report it. Understand it. Resolve it. Prove it. Measure it."
GreenLoop AI includes a built-in deterministic demo adapter. You can test the end-to-end user journeys immediately in local development, or deploy directly to AWS using the provided SAM templates in infra/template.yaml.