How Attero is using AI to solve recycling’s pricing and compliance challenges

Attero is an Indian company that recycles e-waste and lithium-ion batteries. Its work involves buying materials, deciding their value, processing them and meeting regulatory requirements. Matrix and Lightspeed are AI-powered systems built to support those operations.

Matrix is Attero’s pricing engine. It combines material intelligence, such as likely components and recoverable metals, with market intelligence, including commodity prices and local conditions. Lightspeed is the compliance engine. It checks documents, reconciles information and flags unusual or incorrect records for review.

These tools address different business problems but work toward the same goal: consistent, scalable decisions. Matrix helps Attero price thousands of incoming materials without relying entirely on human judgement. Lightspeed helps create audit-ready records and lets the existing team process more documents without increasing headcount.

Attero handles a very large flow of recyclable material every year. According to Ayush Agarwal, the company processes around 200,000 metric tonnes of e-waste and 10,000 metric tonnes of lithium-ion batteries annually. Those figures show why manual decisions become difficult to scale.

The company also procures material worth more than Rs 1,000 crore each year. This is not simply a measure of waste volume. It represents a major purchasing activity, where inaccurate estimates of recoverable metals, processing costs or transport can affect financial results.

That scale explains Attero’s investment in AI systems. Matrix aims to standardise scrap pricing across suppliers and locations. Lightspeed supports the large document trail created by those transactions. The company’s stated goal is to handle growth through better systems, rather than relying only on larger teams.

Matrix treats scrap pricing as a calculation rather than a fixed commodity quote. It first estimates an appliance’s components and recoverable metals. That matters because two products that look similar may contain different materials, missing parts or recovery potential.

The system combines this material intelligence with recycling records, exchange data, commodity prices and market conditions. It also considers processing and transportation costs. Attero trained or informed the system with three years of recycling data, two years of exchange data and information covering thousands of appliances.

The result is a market-specific estimate of what material should cost. A washing machine may receive one price in Delhi and another in Mumbai because logistics and local supply and demand differ. Matrix is intended to make these decisions consistent as Attero’s volumes grow, instead of expanding teams to judge every transaction manually.

Scrap does not have one universal price in the way standard commodities may have exchange-based references. An appliance’s value depends on what remains inside it, which components are missing, how much material can be recovered and what processing will cost.

Location adds another layer. Moving a washing machine to a plant or market creates transportation costs, while regional supply and demand can affect what buyers will pay. Matrix combines these factors with appliance information and commodity prices. It uses data from thousands of appliances and historical recycling and exchange records to produce an estimate.

That is why the same washing machine can command different prices in Delhi and Mumbai. The difference does not necessarily reflect a change in the appliance itself. It reflects the economics of recovering and moving its materials in each market, along with local conditions.

In Attero’s business, compliance involves maintaining extensive records connected with each recycling transaction. These include supplier details, transporter information, invoices, vehicle documents and other regulatory requirements. Accurate records matter because the company may need to answer regulatory or client questions long after a transaction.

Lightspeed is Attero’s AI-powered compliance engine. It checks submitted documents, compares information across records and flags exceptions for people to review. This reconciliation helps identify inconsistencies rather than treating every document as an isolated file. The system is designed to produce reports that are ready for audits.

So far, the platform has processed 50,000 documents and flagged over 500 errors, according to Agarwal. Attero aims to improve efficiency by 70%. Its target is for the existing team to handle four times as many documents without increasing headcount, while retaining human review for flagged issues.

When pricing, procurement and recovery data sit together, Attero can see more than the movement of materials. It can compare what it paid for incoming scrap with the value of materials recovered from it. That creates a clearer picture of profitability at the individual order level.

The same connected approach also brings compliance records into the operating picture. Matrix supports pricing and Lightspeed checks transaction documents, while shared data can help reveal exceptions or questions around an order. AI therefore becomes a way to connect fragmented business information, not merely automate repetitive tasks.

For Attero, the practical change is greater financial visibility and operating capacity. The company wants to improve document efficiency by 70% and let its existing team handle four times the volume. It is also developing image-based learning to identify incoming materials, with its dataset growing from 10,000 toward 100,000 images.

Economically, recovering metals and other materials gives discarded electronics measurable value. Attero uses estimates of recoverable materials to decide scrap prices, processing choices and order profitability. Without that information, the company could pay too much for material or overlook valuable components.

The article connects recovery directly to Attero’s business model. Matrix estimates what appliances contain and how much can be recovered, then combines that information with processing, transport and market data. Recovered-material values can also be compared with procurement costs, giving Attero clearer financial visibility for each order.

The article does not detail the environmental effects of metal recovery. More broadly, established recycling principles indicate that recovering materials can reduce demand for newly extracted resources and keep waste in productive use. Attero’s systems focus on making those recovery decisions more consistent, scalable and financially visible across growing volumes.