According to Fortune, Giga has raised $61 million to expand its enterprise voice AI platform, with food delivery giant DoorDash already using their technology. 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 enterprises and grow its team. The voice AI market is projected to explode from $3.14 billion this year to $47.5 billion by 2034, putting Giga in competition with both specialized startups and tech giants like Amazon and Microsoft. Giga’s system can deploy enterprise-scale AI support in under two weeks and performs multiple real-time actions in less than half a second. At DoorDash, their AI maintains live connections with Dashers, calls consumers to verify addresses, and handles policy compliance automatically.
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The Speed Advantage
Here’s the thing that makes Giga interesting: they’re not just another AI company promising the moon. They’re actually delivering measurable results for massive companies like DoorDash, and they’re doing it fast. Co-founder Varun Vummadi says they can deploy enterprise-scale AI support in less than two weeks. That’s basically lightning speed in the corporate world where IT projects typically take months. Their product-based approach lets companies upload existing support transcripts and policies, and the system automatically builds everything out. No endless configuration meetings, no months of training data preparation. Just upload and go.
The Multitasking Magic
What really separates Giga from your average chatbot is their real-time orchestration layer. Most AI systems struggle with doing multiple things at once – listening, understanding, deciding, checking databases, speaking back. Giga’s system handles all of this in under half a second while maintaining context across different actions. At DoorDash, when a Dasher can’t complete a delivery, the AI doesn’t just hang up and escalate. It maintains the connection, calls the customer to verify addresses, checks policies, and resolves the issue – all automatically. That’s the kind of efficiency that actually saves companies real money rather than just creating more complexity.
The Accent Problem
Now let’s talk about the elephant in the room: voice AI has historically been terrible with accents and non-standard speech patterns. Most systems are trained on “standard” American or British English, which means anyone with a regional accent, elderly users, or people with speech differences get constantly misunderstood. Giga’s approach is actually pretty clever – they’re working with multilingual models and letting users opt into speaking their native language. As Vummadi noted, “We have seen a lot of accent issues go away if people speak in their native language.” It’s a simple insight, but one that many AI companies have missed while chasing perfect English comprehension.
Beyond Customer Service
Giga’s ambitions extend far beyond handling customer complaints. They’re already moving into regulated industries like healthcare and finance, where they deploy entirely on the client’s cloud infrastructure using open-source models. In financial services, they’re automating compliance processes like flagging unusual transactions and maintaining the paper trails regulators require. The system can even cross-reference external databases like Zillow to verify property sales and prevent fraud. This isn’t just about replacing call center workers – it’s about building what Redpoint’s Satish Dharmaraj calls “a foundational AI layer for customer voice” that understands nuance and scales with enterprise reliability. The question is whether they can maintain that reliability as they expand beyond their current success with DoorDash.
The voice AI space is incredibly crowded, but the state of voice AI in 2025 shows we’re finally moving beyond basic chatbots to systems that can handle real conversations. Giga’s $61 million war chest suggests investors believe they’ve cracked part of the code. But the real test will be whether their approach scales across dozens of Fortune 100 companies without losing the speed and accuracy that made them attractive in the first place.
