Arga raises $10M to help enterprises safely train AI agents before deployment

Training AI agents to work reliably in the real world has proven far more difficult than many organizations anticipated. A wave of new companies is stepping in with tools designed to address this gap, offering better mechanisms for testing and refining agent behavior before rollout—especially when it comes to the messy realities of enterprise software.

Arga, a startup focused on this exact problem, announced Wednesday that it closed a $10 million seed round led by General Catalyst, with backing from Box Group, Emergence, Gradient, and SV Angel.

How Arga's approach differs#

Most training and testing environments for software operate as bare APIs without context or state. Arga takes a different approach: it constructs a complete digital replica of enterprise applications like Salesforce, Workday, and email platforms—essentially duplicating the entire system alongside its access controls and event-handling mechanisms. This full-fidelity model enables far more authentic agent training across interconnected tools.

CEO and co-founder Philip Li offered a concrete scenario to illustrate the challenge his platform solves. Imagine an agent must handle a situation where one team member creates a sales prospect in Salesforce while another simultaneously logs an inquiry in HubSpot, both referring to the same organization. The agent must then determine whether these represent duplicate records, verify that outreach hasn't already occurred, and route communications to the right contact. Today's agentic systems routinely stumble on such real-world complexity.

Why traditional testing breaks down#

Enterprises could theoretically use reinforcement learning—running scenarios thousands or tens of thousands of times to isolate winning strategies—but the infrastructure simply doesn't exist. Systems like Salesforce and Outlook can't be cleanly reset between test runs, nor are they easily cloned for experimentation. Building a sandbox environment for enterprise software is far harder than it sounds.

Arga's solution#

Arga rebuilds these applications as controlled digital environments, much as a crash test dummy replicates human anatomy. With full ownership over the replica, the company can reset configurations instantly, tweak parameters on demand, and spin up multiple parallel instances simultaneously. This allows teams to construct realistic multi-system workflows—where tasks span across different platforms and data sources—and train agents to navigate them effectively.