Build Intelligence
for the Circular Economy.
AI-powered infrastructure for smarter e-waste recovery, reverse logistics, and ESG intelligence.
Building the Intelligence Layer for the Circular Economy.
ReCircuit explores how artificial intelligence can modernize e-waste recovery, reverse logistics, ESG intelligence, and sustainable resource management. Current work focuses on research, architecture, and a prototype that makes circularity easier to understand, measure, and build.
One research pipeline from device upload to ESG report.
Signature concept: computer vision, component analysis, valuation, carbon reasoning, collection optimization, and evidence generation in one transparent flow.
Device Upload
Capture device photos, condition notes, serial evidence, and safety flags for one recoverable asset record.
Computer Vision
Early model concept reads category, condition, corrosion, battery risk, visible damage, and reusable modules.
Object Detection
Component-level detection maps processors, cells, PCBs, memory, cameras, ports, and salvageable assemblies.
Component Analysis
Rules and model outputs estimate repairability, harvest potential, material stream, and data-risk workflow.
Market Valuation
Valuation layer compares resale, refurbishment, component harvest, recycling, and certified destruction paths.
Carbon Impact
Carbon model estimates avoided emissions, material recovery benefit, transport burden, and evidence needed.
Collection Optimization
Routing concept balances pickup density, facility capacity, safety class, and recovery priority.
ESG Report
Report builder prepares Scope 3 notes, diversion logic, chain-of-custody fields, and confidence levels.
A product architecture for smarter e-waste recovery.
Early-stage concept for intake, recovery logic, ESG evidence, and dashboards that explain decisions instead of pretending certainty.
Research Platform
A founder-led product architecture for AI-assisted e-waste intake, recovery decisions, and evidence capture.
Recovery Logic
Decision paths compare repair, resale, component reuse, recycling, and certified destruction without hiding uncertainty.
ESG Evidence
Structured records explain what was known, what was estimated, and which proof would be needed for audits.
Map the journey from waste to recovery.
Move the timeline to inspect how electronics, lost materials, carbon, supply-chain friction, AI, and recovery decisions connect.
Timeline
AI
Models estimate value, carbon delta, data-risk workflow, and best circular path with visible confidence.
ESG intelligence without inflated claims.
ReCircuit frames ESG reporting as evidence design: what happened, what was measured, what was estimated, and what proof must be collected before a claim becomes credible.
Evidence model
Prototype reporting logic
A prototype workspace for circularity decisions.
A simulated dashboard shows how recovery value, route logic, evidence quality, and ESG reporting could live in one product surface.
Recovery path simulation
Concept readiness
An interactive architecture for asset intelligence.
A living technical map: upload, event pipeline, model layer, carbon reasoning, storage, dashboard, and APIs ready for future integrations.
An honest roadmap from research to pilot.
No fake traction. ReCircuit is early-stage: research first, prototype second, pilot learning before enterprise platform claims.
Research: e-waste recovery workflows, ESG reporting needs, computer vision datasets, and market constraints.
Prototype: interactive product demo, AI pipeline simulation, and first recovery decision engine draft.
MVP: device intake flow, component analysis, carbon estimate, and downloadable ESG evidence report.
Pilot Program: invite recyclers, campus labs, and local collection operators for controlled testing.
Enterprise Platform: expand integrations, compliance workflows, and recovery network intelligence.
Global Circular Intelligence Platform: connect recovery decisions, material traceability, and climate data at scale.
The intelligence layer for circular electronics.
A publication-ready research whitepaper covering the global context, architecture, AI methods, roadmap, risks, references, and current build status behind ReCircuit.
AI Recovery Economics
Circular electronics is no longer waste management. It is a data system that prices material, carbon, resale, risk, and compliance in one decision.
Mohnish M is building AI systems for the Circular Economy.
Computer Science Engineering student, founder of ReCircuit, and founder of House of Mohny. Current work combines product engineering, computer vision, ESG research, and reverse logistics systems thinking.
Mohnish M
Founder of ReCircuit and House of Mohny
Early-stage, transparent, and still being built.
ReCircuit is not presenting fake traction. This site shows the product vision, research direction, and current build status.
Discuss research, pilots, or climate AI collaboration.
strategy@recircuit.online
Founder-led research project. Pilot conversations opening after prototype.