According to Fortune, voice AI startup Giga has raised $61 million in fresh funding to expand its enterprise operations, with food delivery giant DoorDash already as a customer. Founded by IIT Kharagpur graduates and Forbes 30 Under 30 alums Varun Vummadi and Esha Manideep, the company plans to scale usage within Fortune 100 companies and grow its team. The funding comes as the voice AI market is projected to explode from $3.14 billion this year to $47.5 billion by 2034. Giga’s system can deploy enterprise-scale AI support in under two weeks and performs multiple real-time tasks—like listening, understanding, and database checking—in less than half a second. At DoorDash, their AI maintains live connections with delivery drivers, calls consumers to verify addresses, and handles policy compliance automatically.
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The Speed Advantage
Here’s the thing about enterprise tech—implementation speed is everything. Giga’s claiming they can get their AI fully deployed in less than two weeks, which is basically lightning speed in corporate terms. They do this by letting companies upload existing support transcripts and policies, then automatically building the AI around that data. So the time to value is dramatically low, as co-founder Varun Vummadi puts it. In a space where competitors might take months to get running, that’s a serious competitive edge. But can they maintain that speed as they scale up to more complex Fortune 100 clients? That’s the real test.
Beyond Basic Chatbots
This isn’t your grandma’s chatbot. Giga’s built what they call a “unified real-time orchestration layer” that handles multiple actions simultaneously. We’re talking about systems that can listen, understand context, decide how to respond, check databases, and speak back—all in under half a second. The DoorDash example is pretty telling: when a Dasher can’t complete a delivery, Giga’s AI doesn’t just escalate to a human. It maintains the connection, calls the customer directly, verifies addresses, and handles compliance checks automatically. That’s moving beyond simple Q&A into actual workflow automation. And that’s where the real business value lies.
The Accent Problem
Now for the elephant in the room: voice AI has historically sucked with accents and non-native speakers. Most systems are trained on “standard” American or British English datasets, which means anyone with a regional accent or speech pattern gets misunderstood. Elderly users and people with speech impediments face even bigger challenges. Giga says they’re tackling this by working with open-source, multilingual models and letting users opt into speaking their native language. “We have seen a lot of accent issues go away if people speak in their native language,” Vummadi told Fortune. They’re also storing user preferences to improve over time. But let’s be real—this is a massive technical challenge that even giants like Amazon and Google still struggle with. The state of voice AI in 2025 shows we’re still in early days for truly inclusive voice technology.
Regulated Industries Play
What’s really interesting is Giga’s push into healthcare and finance—two sectors where data privacy is non-negotiable. They’re deploying entire systems on the client’s own cloud infrastructure using open-source models, meaning Giga never touches the actual data. In financial services, they’re already automating compliance processes like flagging unusual transactions. When customers make transfers that look suspicious, the AI reaches out to confirm details and maintain the paper trail regulators require. It can even cross-reference external databases like Zillow to verify property sales and prevent fraud. Basically, they’re positioning this as AI that can handle sensitive, regulated work without compromising security. If they can pull that off, the $61 million investment starts looking pretty smart.
