CodeRabbit raised $60 million in Series B funding at a $550 million valuation just two years after founding, addressing a critical enterprise infrastructure bottleneck: AI-generated code is creating exponential review backlogs that traditional processes can’t handle.

The Scale Venture Partners-led round, with participation from NVIDIA’s NVentures, validates an urgent infrastructure reality—teams using AI coding tools now generate 2x to 3x more pull requests while senior engineers struggle to review 20-30 PRs daily instead of the traditional 5-10. This mathematical impossibility is forcing enterprises to choose between deployment velocity and code quality.

Gartner predicts that by 2028, one in four enterprise breaches will trace back to compromised AI agents. Yet today’s identity systems still assume browser logins and manual logouts—a fundamental mismatch as autonomous agents begin invoking business applications at scale.

Scalekit, founded by the team behind Freshworks’ authentication platform, just secured $5.5 million in seed funding to build the missing authentication infrastructure for AI agents. The round was led by Together Fund and Z47, positioning the startup to address what may become the most critical security bottleneck in enterprise AI deployment.

EvoluteIQ secured $53 million in growth investment led by Baird Capital, marking a critical inflection point for enterprise agentic automation as Fortune 500 companies move beyond fragmented point solutions toward comprehensive workflow orchestration.

The funding validates a fundamental shift in enterprise automation strategy. While traditional approaches layer disconnected RPA bots and isolated AI tools across business processes, EvoluteIQ’s approach addresses the core bottleneck: enterprises need unified platforms that orchestrate end-to-end business workflows, not collections of tactical automation tools.

WorkFusion raised $45 million in Series funding led by Georgian to scale AI agents that automate financial crime compliance operations, with deployment across 10 of the top 20 global banks processing over 1 million alert investigations daily.

The funding addresses a critical operational bottleneck in the $155 billion financial crime compliance industry, where manual alert review processes overwhelm analyst teams and create regulatory risk for financial institutions facing exponentially growing transaction volumes.

Tabs has raised $55 million in Series B funding led by Lightspeed Venture Partners to scale its AI agents for finance automation, processing over $1 billion in annual invoice volume across 200+ enterprise customers. The financing addresses a critical bottleneck: 75% of accountants are nearing retirement while the number of new CPAs has dropped 30% in the past decade, even as revenue operations become increasingly complex with usage-based and hybrid pricing models.

Syncari closed a $20 million Series B funding round led by Escape Venture Investing as Fortune 1000 companies adopt its “Agentic Master Data Management” platform to address a critical AI infrastructure bottleneck: enterprise data scattered across dozens of systems makes it impossible for AI agents to operate effectively.

While AI capabilities advance rapidly, the fundamental challenge of trusted, unified data remains the primary barrier to enterprise AI deployment. Syncari’s platform positions itself as essential infrastructure for the AI economy, with 2+ trillion data operations under management and deployment times 50x faster than traditional MDM systems.

Databricks closed a $1 billion Series K funding round at a valuation exceeding $100 billion, with the capital specifically earmarked to expand Agent Bricks—its automated platform for building production-ready AI agents on enterprise data.

The timing reflects a critical inflection point where enterprises demand AI agents that work reliably on their proprietary data, not just generic demonstrations. Databricks’ approach addresses the deployment gap that has left 95% of AI agent pilots failing to reach production, according to enterprise surveys.

HappyRobot just closed a $44 million Series B round, less than a year after raising its Series A, as demand for AI workforce automation in supply chain operations reaches a tipping point. The San Francisco startup reports 70+ enterprise customers including DHL, Ryder, and Werner achieving returns exceeding 119 times their initial investment in collections operations.

This rapid funding cycle reflects the broader infrastructure build-out required to deploy autonomous AI workers at enterprise scale, where traditional workflow automation hits operational complexity limits. Supply chains generate millions of daily coordination tasks—rate negotiations, appointment scheduling, payment collections, shipment updates—that overwhelm human teams while creating critical bottlenecks in global trade operations.

Conversations generate 5 times more words annually in the workplace than exist on the entire internet, yet this massive dataset remains largely inaccessible to AI systems. Recall.ai just raised $38 million in Series B funding led by Bessemer Venture Partners at a $250 million valuation to solve what may be the most overlooked infrastructure bottleneck in enterprise AI deployment.

This isn’t about building better AI agents—it’s about giving existing agents the conversational context they need to be useful. When an AI needs to update a CRM after a sales call or draft follow-up emails based on meeting discussions, the challenge isn’t intelligence; it’s accessing the conversation data in the first place.

Benchmark has led an $85 million Series B round in Exa Labs at a $700 million valuation, betting that the next wave of AI infrastructure will be purpose-built for agents, not retrofitted from human-centered systems.

This timing reflects a fundamental shift: as AI agents become the primary interface between enterprises and web-scale data, the search infrastructure powering these interactions has become a critical bottleneck. Exa’s neural search architecture delivers sub-450ms latency with zero data retention, addressing the dual enterprise demands of speed and privacy that traditional search engines can’t meet at agent scale.