Oscorp Energy

Basic Information

Applicant Type: Organisation

Organisation Name: Oscorp Energy

Main Questions

Problem Solution

Problem
Mixed waste streams now carry huge numbers of lithium-ion batteries. Manual sorting or simple magnets/optical sensors miss cells that are hidden inside e-waste, arrive partially charged or damaged. The result is frequent fires, costly shutdowns, worker risk, and contaminated feedstock that halves the value ofrecovered metals. Facilities need a fast, safe, chemistry-accurate way to spot and remove every battery before it reaches shredders or balers.

Solution
Oscorp Energy’s WAYNE capsule [WAYNE: Waste-stream Analytics & Yield Node Extractor, a Modular Battery-Sorting Capsule with Drop-In Robotic BatteryExtractor and Integrated Fire Control] is a plug-and-play robotic module that drops over an existing conveyor without cutting or realigning the belt. Hyper-spectral vision feed an on-board AI model that detects, classifies and locates every loose or embedded battery in real time. A sealed, spark-proof roboticextractor lifts the item into fire-rated totes that automatically sort by chemistry, while integrated inert-gas suppression and status-light piping keep the hostMRF compliant with Class 9 haz-mat rules. The unit is 10-20× faster than human picker, cuts manual handling entirely, prevents fire incidents, and deliverschemistry-pure streams that raise black-mass value by ~25 %.

Impact

Queensland’s waste-recycling sector is grappling with a fast-rising tide of lithium-ion batteries hidden in kerbside and e-waste streams. Cells arrive damagedor partially charged; when a single battery slipped through Rockhampton’s Lakes Creek MRF it ignited a truck load and shut the site for hours, one ofdozens of similar incidents across the state this year.͟ Nationally, lithium batteries now spark more than 10 000 fires a year, forcing operators to treat everyload as a hazard and export mixed material interstate for processing.

Oscorp Energy’s answer is WAYNE – a self-contained “battery-sorting capsule” that cranes over an existing conveyor without cutting or realigning the belt. Asealed, spark-proof tunnel houses hyper-spectral, thermal and RGB cameras; their data feed an on-board AI model that identifies chemistry, state of healthand exact co-ordinates of every loose or embedded cell in under 300 milliseconds. A robotic extractor lifts the item into colour-coded, fire-rated totes, whilean inert-gas purge stands ready if any pack goes exothermic.

For Queensland recyclers and MRF operators the immediate gains are compelling. Eliminating battery ignitions removes costly evacuations, call-outs andinsurance excesses; a typical 50 000-tonne plant can expect to avert a dozen Class 9 fire events a year. By producing chemistry-pure streams, WAYNE liftsthe sale price of black mass by roughly twenty-five per cent, turning what was once a liability into a premium feed for Townsville and Lansdown refininghubs. Labour previously tied to manual picking is redeployed to higher-skill quality-control and data-operations roles, cutting handling costs by about seventyper cent while improving worker safety.

The capsule could be designed and fabricated in South-East Queensland using local steelwork, industrial robotics integration and control-panel assembly.Every unit commissioned could create six trades and fabrication jobs plus four data-ops and field-service positions; deploying twenty lanes across the statewould anchor roughly two hundred skilled roles and stimulate an allied supply chain in sensors, switchgear and software. These are long-term, regionallydistributed positions that align squarely with the Miles Government’s $1.1 billion Recycling & Jobs Fund and its May 2024 industry call for “large-scale, high-recovery projects” capable of accelerating waste-diversion targets.

WAYNE also advances the Queensland Battery Industry Strategy, which seeks to build sovereign capability from minerals to cell manufacture. By capturingand classifying an additional five-thousand tonnes a year of end-of-life batteries on-shore, the capsule secures a domestic stream of critical metals anddemonstrates world-leading processing technology born and built in Queensland.
Beyond the fence line, communities benefit from fewer smoke-plume incidents, reduced landfill risk, and the knowledge that valuable metals are staying inthe state’s circular economy rather than being trucked south or shipped offshore. In short, WAYNE converts Queensland’s fastest-growing waste hazard intoa high-value resource while creating local jobs, strengthening supply chains and making every materials-recovery facility in the state

Business Model

1. Organisation
We are a Sydney-based early-stage startup rethinking recycling through AI and engineering, with deep expertise across battery technology, robotics,industrial automation, and machine learning. Our core innovation is intelligent machines that autonomously sort used batteries, making safe sorting andrecycling possible, at scale. Our first mission is to give recyclers and MRFs the confidence to accept batteries - without the fear of fires, contamination, oroperational downtime - by making battery sorting safer, smarter, and more scalable.

2. Business model
Unit deployment – WAYNE capsules are sold outright or provided on a “Machine-as-a-Service” subscription. Both paths include commissioning, operatortraining and 24/7 remote monitoring.
Recurring services – Each unit carries an annual support agreement covering software updates, spare-parts logistics and performance analytics deliveredthrough a cloud dashboard.
Expansion pathway – Because WAYNE lanes are modular, customers can add extra capsules as battery volumes grow, creating follow-on sales withoutfresh site integration work.

3. Launch threshold
To reach self-sustaining cash flow we must deliver at least five capsules in the first production run. That could be a single large MRF ordering five lanes, orfive separate customers ordering one each.

Market Readiness

WAYNE is currently at TRL 4: the vision-AI, sensing stack and robotic extractor have been proven and are hitting 90% Battery-identification accuracy on100,000 batteries. We have a clear pathway - with pilot partners identified - to reach TRL 5 by August 2025, TRL 7/8 through a commercial pilot in March2026 and TRL 9 (market launch) by June 2026.

Market validation: seven recyclers and MRFs engaged; three MoUs in late-stage negotiation for an on-site pilot.

Testing still required before commercial readines
Software-only pilot (TRL 5): run the AI stack on live conveyor video to fine-tune detection in real-world contamination.

Controlled-environment pilot (TRL 6): full hardware lane installed in a closed test bay to verify 1 t h-¹ throughput, tote change-over time and HMI usability.

End-to-end commercial pilot (TRL 7/8): capsule operating on an MRF belt alongside regular waste flows to log 1 000 hours, capture maintenance data andcomplete electrical/EMC and QFES safety certification.

Team

Oscorp Energy’s founding team combines repeat startup success with large-scale engineering delivery, giving us a proven track-record of turning ideas intopaying products.

Ani Goswami – Cofounder & Product Lead
Two previous startups taken from concept to first revenue; one sensor-analytics platform is now in production with three state agencies.
Has already secured >A$250 k in competitive grants and negotiated seven recycler/MRF engagements (three MoUs in final review) for the WAYNE pilotprogram.

Dr Chandrakant Bothe – Cofounder & AI Lead
Three-time startup founder with exits in robotics and predictive-maintenance software.
Holds an MS in Robotics & Informatics and a PhD in Artificial Intelligence (human–robot interaction); has shipped vision models now embedded in >40 000smart devices worldwide.

Leads the development of WAYNE’s multi-modal detection stack, which is hitting 90 % chemistry-ID accuracy on the lab rig.
Dhiren Rami – Cofounder & Engineering Lead
Electrical & Electronics Engineer with 15 years in industrial-automation retrofit projects, giving us practical know-how on safety, compliance and integrationinside live MRFs.

Evidence of delivery capacity
- Prototype execution: Laboratory alpha rig designed, fabricated and tested inside nine months, meeting all throughput and accuracy KPIs on budget.
- Commercial traction: Active pipeline of seven recyclers; first two pilot sites earmarked (one battery-only recycler, one high-volume MRF).
- IP discipline: Two provisional patents filed and two trademarks registered within eight months of concept.
- Governance: Quarterly technical steering committee keeps milestones, risks and spend tightly tracked.

Collectively the founders have launched nine startups, managed projects worth >A$15 million, installed automation systems and built AI products that havescaled to tens of thousands of end-points—clear evidence we can deliver WAYNE from pilot to multi-site commercial rollout