INTRODUCING SUVARN
The Next Generation of Minerals Supply Isn't Underground.
It's Already Around Us.
We are reimagining how critical minerals are recovered, refined, and returned to industry through intelligent resource recovery and advanced metallurgy.
THE opportunity
Hazardous Waste.
Extraordinary Opportunity.
India generated nearly 1.4 million tonnes of officially estimated electronic waste in FY2024–25, originating from an increasingly connected economy of consumer electronics, telecom infrastructure, data centres and industrial equipment. Hidden within these complex materials is a remarkable concentration of valuable metals — copper, gold, silver, palladium, nickel, tin and more — that support everything from semiconductor packaging and telecommunications to clean energy and advanced manufacturing.
With India's National Critical Mineral Mission recognising the strategic importance of mineral recovery from secondary resources, an opportunity is emerging to transform discarded electronics into a domestic source of industrial metals. At Suvarn, our ambition is to unlock this resource through intelligent material identification, advanced metallurgy and precision refining — turning yesterday's electronics into tomorrow's mineral supply.
India's Future Can't Depend Entirely On Imported Minerals.
India's ambitions in semiconductors, electric mobility, renewable energy, defence and advanced manufacturing depend on a secure and reliable supply of critical minerals. Yet the country's industrial growth remains exposed to global supply chains. India imported ~95% of its copper concentrate requirements in FY2023–24, while its dependence on imports of several strategic minerals, including nickel, lithium and cobalt, remains exceptionally high.
Recognising this challenge, India launched the National Critical Mineral Mission, backed by ₹16,300 crore in government expenditure, to strengthen domestic mineral capabilities across exploration, processing, refining and recovery.
At Suvarn, we believe mineral security must extend beyond conventional mining. By recovering valuable metals already circulating within India's electronics and industrial infrastructure, and refining them into high-quality industrial materials, we aim to help build a more resilient, technologically capable and self-reliant mineral supply chain for India.
Mineral Security Is the Foundation of Industrial Independence.
THE TECHNOLOGY
Identifying material origin, composition, and estimated recoverable value through analytical assays, traceability and data-driven prediction
Precision Metallurgy
Engineering metallurgical pathways around the actual composition of feedstock, controlling impurities, processing conditions and metal recovery.
Digital Metal Accounting
Connecting source identity, laboratory assays, process data, recovered products and residual materials through a traceable mass-balance systems.
Complex Waste→ Precision Refining.
At Suvarn, we are building an intelligence-led metallurgical platform that integrates advanced material characterisation, multi-technique elemental assays, AI-assisted recovery prediction and precision refining. Every material stream is designed to be digitally traceable, every processing stage measurable, and every recovered metal accountable.
Our ambition is to bring the precision of advanced manufacturing to critical mineral refining — transforming variable secondary resources into consistent, high-purity industrial materials through science, data and process engineering.
Material Intelligence
CHALLEnges keeping us awake..
λₖ(t | xᵢ(t)) = λ₀ₖ(t) exp(βₖᵀ xᵢ(t))
Here k denotes a possible retirement or disposition event, and xᵢ(t) includes asset age, OEM support status, network generation, refresh cycles, utilisation and other observed signals.
Competing risks-survivor model
Stochastic optimisation problem
max_π E[Profit(π)] − λ Risk(π)
Maximize the expected financial returns of resource recovery while weightedly penalizing volatility and supply chain exposure, ensuring a stable and efficient supply. π represents procurement policy.
Minimise total assay error
Var( C̄ ) = σ² / n_eff
where n_eff represents the number of effectively independent increments.
Selective metal dissolution prediction
dCᵢ/dt = kᵢ(T, pH, Eₕ, d, …) Aᵢ
Determining kinetic reaction rates as a function of thermodynamics and surface area. Here Cᵢ is the dissolved concentration of metal i, Aᵢ represents its accessible reactive surface area, and kᵢ is an effective kinetic term.