According to Fortune, voice AI startup Giga just raised $61 million to expand its enterprise automation platform, with food delivery giant DoorDash already using its technology. Founded by IIT Kharagpur graduates and Forbes 30 Under 30 alums Varun Vummadi and Esha Manideep, the company claims it can deploy enterprise-scale AI support in less than two weeks. Giga’s system handles complex multi-step tasks in real-time, like maintaining live connections with delivery drivers while simultaneously calling customers and checking policies. The funding will help scale usage within Fortune 100 companies and expand into regulated sectors like healthcare and finance, where Giga deploys entirely on client infrastructure to maintain data privacy.
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Voice AI gets real
Here’s the thing about voice AI – everyone’s been talking about it for years, but we’re finally seeing systems that can handle actual business workflows rather than just answering simple questions. Giga’s approach is interesting because they’re not just building another chatbot with a voice interface. They’ve created what they call a “unified real-time orchestration layer” that manages listening, understanding, decision-making, database checks, and speaking back – all in under half a second.
That speed matters when you’re dealing with something like a DoorDash delivery going wrong. Imagine a driver can’t complete a drop-off. Giga’s system can stay on the line with the driver, automatically call the customer to verify the address, and check compliance policies – all without human intervention. That’s way beyond “please say your account number.”
The accent problem
But let’s be real – we’ve all had terrible experiences with voice systems that can’t understand basic requests. The historical weakness of voice AI has been handling nuance, emotional intelligence, and especially non-standard accents. Most training data skews heavily toward “standard” American or British English, which means people with regional accents, elderly users, or those with speech impediments constantly get misunderstood.
Giga’s approach to this is actually pretty smart. Instead of trying to perfect accent recognition, they’re letting users opt into speaking in 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 working with open-source and multilingual models, and the system stores user preferences over time to improve with each interaction.
Regulated industries play
What’s really interesting is their push into healthcare and finance. These are sectors where voice AI has struggled because of data privacy concerns and regulatory requirements. Giga’s solution? Deploy the entire system on the client’s own cloud infrastructure using open-source models. The company says they never even access client data when configured this way.
In financial services, they’re already automating compliance processes like flagging unusual transactions. If you make a transfer that doesn’t match your normal pattern, the AI can reach out to confirm details and maintain the paper trail regulators require. They’re even cross-referencing external databases like Zillow to verify property sales and prevent fraud. Basically, they’re building what amounts to an automated compliance officer that works at AI speed.
Crowded space, big potential
The voice AI market is projected to grow from $3.14 billion this year to $47.5 billion by 2034, which explains why everyone from specialized startups to Amazon and Microsoft are fighting for position. But as the current state of voice AI shows, there’s still a huge gap between basic voice assistants and systems that can handle complex enterprise workflows.
Giga’s bet seems to be that implementation speed and real-time multi-action capability will set them apart. Being able to deploy in under two weeks by having companies upload existing support transcripts and policies is a compelling value proposition for enterprises that don’t want to wait months for ROI. The question is whether they can maintain that speed and reliability as they scale across more Fortune 100 companies and regulated industries. If they can, they might just deliver on the voice AI promise that’s been just out of reach for years.
