Voice AI Start-Up Arrowhead Raises $3M Led by Stellaris to Automate BFSI Sales

Seed round led by Stellaris; founders promise higher conversions, large BFSI opportunity

Arrowhead Raises $3Mn
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Summary
Summary of this article
  • Arrowhead raised $3mn in seed funding led by Stellaris Venture Partners

  • Angels including Kunal Shah (Cred) & Madhusudanan R (M2P) participated

  • Voice AI agents handle 20-minute sales calls, boosting conversions

Arrowhead, a Bengaluru-based voice AI startup building ultra-human sales agents for the financial services sector, said on Wednesday it has raised $3 million in a seed round led by Stellaris Venture Partners, with participation from marquee angels and customer-investors including Kunal Shah of CRED, Madhusudanan R of M2P, and several senior fintech executives. The fresh capital will be deployed to strengthen Arrowhead’s core AI models, scale its engineering and go-to-market teams, and accelerate deployments across India and Southeast Asia.

The company positions itself as a specialist provider for banks, NBFCs, insurers and payment companies seeking to automate long, consultative voice interactions without compromising conversion rates or regulatory compliance. Arrowhead’s founders say its AI agents can handle end-to-end sales conversations lasting up to 20 minutes and, in enterprise deployments cited by the company, have delivered conversion lifts of 45–50% compared with human agents, while enabling significantly higher outreach volumes.

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1 January 2026

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Enterprise Traction

Co-founder and CEO Devyani Gupta, a Wharton graduate and former BCG consultant, said Arrowhead has moved quickly from pilots to production with several large financial institutions. “We’re building voice AI agents that can handle long, complex sales conversations while delivering meaningfully better conversion outcomes. What’s exciting is how quickly financial institutions are moving from pilots to full-scale adoption,” Gupta said. The company reported a five-fold increase in annual recurring revenue between August and October last year and said every proof-of-concept to date has converted into a live deployment.

Arrowhead’s platform is built around a proprietary, in-house orchestration layer that manages multi-turn conversations, compliance prompts, dynamic scripting and fallback behaviours, allowing calls to remain natural while meeting audit and regulatory requirements. In one large deployment, the company said it replaced a manual calling operation for a major financial institution’s health insurance sales and recorded a 45% higher conversion rate. In another case, it expanded insurance renewal outreach to the entire customer base, lifting renewal rates by about 20%.

Market Opportunity

Stellaris Principal Vardhan Dharnidharka, who led the round, said the BFSI voice-AI market in India alone represents a significant opportunity. “Voice AI for the financial sector in India is a $3 billion market, with less than $50 million penetrated so far, underscoring how early we are in this transition,” he said, adding that top-down AI mandates at banks and fintechs are accelerating adoption. Investors cited measurable conversion gains, cost savings from reduced reliance on human call centres, and strong compliance controls as key drivers behind the investment.

Clients & Roadmap

Arrowhead was co-founded by Gupta and Vengadanathan Srinivasan, an engineer with prior experience at AWS, Rippling, Uber and Airbnb. The startup says it serves more than 50 customers across India and Southeast Asia, including Bank of Baroda Cards, Aditya Birla Capital, Paytm, Tata 1mg, Kissht, TurtleMint and InsuranceDekho. Customers report significantly higher outreach volumes and growing confidence in using AI agents for complex, compliance-sensitive conversations.

Following the funding, Arrowhead plans to deepen BFSI-specific conversation models, expand infrastructure to support tens of thousands of concurrent calls with sub-500 millisecond latency, and introduce emotion-aware voice agents. Over the next 12–18 months, the company also aims to build an omnichannel stack that extends its conversational intelligence across voice, chat and messaging channels.

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