General Magic Closes $7.2M Oversubscribed Round to Transform Insurance Workflows with AI

Toronto-based General Magic has raised $7.2 million in an oversubscribed funding round aimed at accelerating the deployment of its AI agents across the insurance industry. The round was led by Radical Ventures, with significant participation from a16z Speedrun, alongside a group of operators from leading AI and product companies.

The company has now raised $8.4 million to date.

Rather than positioning itself as another broad AI platform, General Magic is focused on a specific operational bottleneck: the coordination work that happens before a quote is finalized, after it is issued, and during claims. In many insurance organizations, that work still depends on calls, inboxes, and fragmented portals stitched together by manual effort.

Cutting Quote Times from 30 Minutes to 3

General Magic builds SMS-native AI agents that sit directly on top of broker management systems, quoting platforms, and CRMs. Its core product, Cell, allows customers to text questions and receive responses grounded in real system data. The agent can request missing information, follow up automatically, and update records as workflows progress.

In early deployments with large personal lines insurers, the impact has been measurable. The company reports reducing average time-to-quote from roughly 30 minutes to under 3 minutes by automating routine clarification and follow-ups over SMS across auto and life insurance workflows.

Beyond speed, the model aims to prevent post-quote drop-off — one of the most failure-prone stages in insurance distribution. By keeping conversations in a single, continuous thread and preserving context, the system reduces the need for manual chasing while keeping customers engaged.

Designed Around Insurance, Not Around Hype

General Magic’s founders, Anthony Azrak and Jai Mansukhani, are second-time entrepreneurs who previously sold AI products into legacy industries. Their move into insurance followed firsthand frustration with the claims process, which revealed how much coordination friction still exists in a technically functional but operationally fragmented system.

Instead of building a horizontal agent framework, the company chose to specialize deeply in insurance workflows. That includes designing agents that reflect how licensed professionals communicate within regulatory structures such as the Registered Insurance Brokers of Ontario (RIBO) licensing framework and the Other Than Life (OTL) insurance agent license in Ontario, ensuring conversations align with the compliance standards and communication norms required of certified brokers and agents.

 The goal is not simply automation, but conversations that feel accurate, compliant, and aligned with how brokers and advisors actually explain coverage.

A Large, Legacy Market Facing Structural Pressure

Insurance carriers and brokers operate in an environment where retention rates lag other industries and customer acquisition costs continue to rise. At the same time, digital distribution has made it easier for customers to shop aggressively at renewal.

In that context, improving follow-through after a quote — and reducing delays in document collection and clarification — has direct financial consequences. Automating those interactions expands effective quoting capacity while lowering inbound call volume, which the company says has dropped by around 30% in early deployments.

Building a Reasoning Layer for Legacy Systems

A recurring theme in investor commentary is the idea that most financial and insurance data remains locked inside rigid systems never designed for AI. Rather than asking enterprises to rebuild their infrastructure, General Magic is building a reasoning layer that sits on top of existing systems of record.

That architectural choice reflects a broader shift in enterprise AI strategy: augmentation over replacement. By connecting to current tools instead of displacing them, the company positions its agents as an operational overlay rather than a systems overhaul.

Insurance Is Moving Toward Conversational Workflows

Beyond one company’s expansion plans, a larger shift is underway in insurance. Carriers and brokers face growing pressure to modernize customer interactions while still relying on legacy policy, billing, and claims systems. As customers expect faster, simpler communication, traditional models built around calls and portals are showing strain.

AI agents that operate directly within existing systems point toward a transition from portal-driven service to conversational workflows layered on top of legacy infrastructure. This could reduce reliance on call centers, increase quoting capacity without proportional hiring, and streamline coordination across the policy lifecycle.

The long-term direction appears less about replacing core systems and more about augmenting them. If conversational automation proves reliable and compliant, it may become a foundational interface for how insurance work gets done in the years ahead.