Corporate treasury teams face a persistent challenge: fragmented banking data scattered across dozens of bank portals, manual reporting trapped in spreadsheets, and legacy Treasury Management Systems (TMS) that can’t scale for modern enterprise needs. For treasury teams these manual processes create delays, errors, and an inability to make real-time cash decisions when they matter most.
Trovata is an AI-native cash and liquidity management platform with direct connections to over 10,000 banks, serving enterprises globally from a single cloud-based platform. In 2023, Trovata launched the first generative AI built specifically for treasury. Now, with Trovata’s latest AI-native updates, they’ve evolved from delivering insights to deploying autonomous agents that act on behalf of treasury teams.
Trovata’s customers have seen measurable results: $1M+ in annualized cost savings, over 5 hours per day saved per accounting team, a 77 percent reduction in annual TMS costs, and treasury reporting reduced from hours or days to under a minute.
In this post, we explore how Trovata built autonomous treasury agents on Amazon Bedrock and Amazon Bedrock AgentCore, the architecture secured with role-based access control (RBAC) that supports bank-branded AI deployment, and how agentic workflows are transforming corporate treasury from manual operations to real-time decision-making at enterprise scale.
Trovata operates as an AI-native treasury operating system, providing direct connections to over 10,000 banks through a single system for cash reporting, forecasting, analysis, and money movement.
Trovata’s evolution from its first generative AI for treasury in 2023 to its AI-native capabilities with autonomous agents represents a fundamental shift.
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