OnCorps AI Secures $55M to Automate Asset Management Operations
OnCorps AI has secured $55 million in Series A funding from Long Ridge Equity Partners to address a critical operational bottleneck crushing the $13 trillion asset management industry. While fund managers focus on investment strategy, they’re drowning in manual back-office work that threatens their margins and competitiveness.
The Boston-based company operates agentic AI agents that autonomously handle trade reconciliations, fund documentation, and exception resolution—the complex operational workflows that typically require armies of skilled analysts working around the clock to maintain accuracy across trillions in assets.
The Asset Management Operations Crisis
Asset management firms face an operational perfect storm. Transaction volumes surge while regulatory requirements multiply, yet operating margins continue to compress under persistent fee pressure. Traditional back-office operations can’t scale to meet these demands without exponentially increasing headcount and costs.
Fund operations teams spend countless hours investigating trade breaks, reconciling complex transactions, and ensuring regulatory compliance across multiple jurisdictions. A single discrepancy in a billion-dollar trade can cascade through systems, requiring manual investigation that delays settlements and increases operational risk.
The manual nature of exception handling creates bottlenecks that prevent firms from scaling efficiently. As one industry executive noted, “Every day, our systems close exceptions, reconcile trades, and oversee trillions in assets with high accuracy and low error rates—but only because we’ve built AI that can work at the speed and scale our human teams simply cannot match.”
Autonomous Exception Resolution Architecture
OnCorps approaches this challenge through specialized AI agents trained on millions of real-world operational discrepancies. Unlike general-purpose automation tools, their platform understands the nuanced patterns of asset management workflows, from complex derivative trades to multi-currency settlements.
The system autonomously investigates root causes of operational exceptions, provides specific resolution recommendations, and learns from patterns to prevent similar issues in the future. This goes beyond simple rule-based automation—the AI agents adapt to new market conditions, regulatory changes, and evolving trading strategies.
Their architecture handles the full spectrum of fund operations challenges: trade processing anomalies, fund accounting discrepancies, and regulatory reporting inconsistencies. The platform integrates with existing fund administration systems while adding intelligent automation that scales with transaction volumes.
Enterprise Validation at Massive Scale
Leading institutions representing $13 trillion in assets under management have deployed OnCorps in production, including PIMCO and GMO. These aren’t pilot programs—they’re full-scale operational deployments handling mission-critical workflows that directly impact fund performance and regulatory compliance.
The platform processes hundreds of millions of operational events across complex global trading strategies. Real-time accuracy matters when a single reconciliation error can impact investor returns or trigger regulatory scrutiny. Enterprise customers report significant reductions in manual effort and operational cycle times.
Production deployment at this scale validates the technology’s readiness for mainstream adoption. Asset managers can implement OnCorps without overhauling existing infrastructure, critical for firms managing active trading strategies worth billions of dollars.
Market Infrastructure Transformation
The asset management industry represents one of the largest opportunities for agentic AI infrastructure. Unlike consumer applications, operational efficiency directly translates to competitive advantage and regulatory compliance in this heavily regulated sector.
OnCorps’ funding reflects growing investor conviction that specialized AI agents can solve industry-specific bottlenecks more effectively than horizontal automation platforms. The company’s deep domain expertise and production-proven technology position them to capture significant market share as the industry modernizes.
This operational transformation enables asset managers to allocate more resources toward investment research and client service rather than manual reconciliation work. The competitive advantage comes from speed and accuracy in operations, not just investment performance.
Looking Forward
OnCorps plans to expand into adjacent capital markets workflows including cash management, regulatory reporting, and complex trade processing. Their specialized approach—training AI agents on domain-specific operational data—could become the standard for financial services automation.
The fund operations market represents just the beginning for this infrastructure approach. Similar operational complexity exists across banking, insurance, and other financial services sectors where manual exception handling creates scaling bottlenecks.
As regulatory requirements continue expanding and transaction volumes grow, the operational infrastructure advantage becomes increasingly critical for asset management competitiveness.
The convergence of operational complexity and AI capability is reshaping how financial institutions handle mission-critical workflows. OnCorps demonstrates how specialized agentic infrastructure can solve sector-specific bottlenecks that generic automation platforms cannot address.
This operational transformation represents a broader shift toward AI-native business processes in regulated industries. Tools like Overclock enable organizations to orchestrate these specialized AI agents alongside human expertise, creating robust operational frameworks that scale with business growth while maintaining the precision required for financial services.