New AI-powered assistant, VERA, helps organizations recover more, waste less, and automate compliance.
Diversys Software, a leader in digital innovation for waste and resource management, announced the launch of Diversys.ai, an advanced suite of artificial intelligence tools that empowers organizations to manage recovery systems with speed, accuracy, and confidence.
Built for producers, stewards, haulers, regulators, and governments, Diversys.ai combines the company’s proven waste data platform with next-generation AI to address persistent challenges in traceability, compliance, and operational performance.
“Diversys.ai isn’t just an upgrade, it’s a turning point for the industry,” said Roger Barlow, CEO of Diversys. “With VERA and AI-backed insights, our partners can uncover hidden inefficiencies, and reduce risk.”
At the core of Diversys.ai is VERA, the Virtual Environmental Recovery Assistant, an intelligent, always-on AI companion designed to support operational teams and decision-makers across the circular economy.
VERA helps users:
- Forecast material volumes and optimize resource allocation
- Identify anomalies, fraud, and confirmation bias in human-collected data
- Eliminate compliance risk through automated audit trail generation
- Generate smart, real-time reports that are regulator- and board-ready
Whether used to manage a national EPR program or a regional hauling operation, VERA empowers users to move faster, reduce manual effort, and make evidence-based decisions at every level.
Test deployments of Diversys.ai have shown transformative results:
- Improvement in operational efficiency within 90 days
- Reduction in unplanned downtime
- Automated regulatory compliance and real-time audit readiness
- New monetization models including:
- Performance-as-a-Service: SLA-backed efficiency and recovery guarantees
- Insight Monetization: Licensed market intelligence for manufacturers and policymakers
- Ecosystem Orchestration: Real-time coordination across multi-party recovery networks
- Precision Marketing: Data-driven packaging and collection strategy optimization
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