New Startup DareAISearch Launches to Help Brands Optimize for AI Engine Recommendations

The landscape of digital marketing is undergoing a significant transformation. Historically, brands spent over two decades optimizing their websites and digital footprints for traditional search engines. However, a major shift in consumer behavior starting around 2024 has disrupted this status quo. Audiences are increasingly turning to artificial intelligence platforms to seek product recommendations, brand suggestions, and purchasing advice. This transition has led to a noticeable decline in organic visibility for companies on traditional platforms, as AI-generated summaries and direct recommendations become the primary point of digital discovery.

Recognizing this gap in the market, a new Gurugram-based startup called DareAISearch (DAIS) launched in 2025 to help companies navigate and optimize for this new paradigm of AI search engines.

A Shift in Consumer Discovery

The transition from search engine optimization (SEO) to AI visibility represents a massive change in how people find information online. Traditional search engines primarily served results in response to existing search volumes. In contrast, AI systems proactively guide consumer decisions by recommending the brands they evaluate as the most trustworthy and relevant.

This shift is rapidly expanding in scale. According to search giant Google, its AI Overviews feature now reaches more than 2.5 billion monthly active users, while its AI Mode has surpassed one billion monthly users. These numbers illustrate that consumers are increasingly delegating decisions—ranging from travel destinations and software purchases to consumer product choices—to AI assistants.

Inside the DAIS Platform

Founded by Siddhartha Vanvani (CEO), Siddhant Jain (CPO), and Nitisha Agarwal, DAIS operates with a 15-member team. The co-founders previously built their expertise as part of the founding and leadership team of Digidarts, a performance marketing agency.

Rather than offering another static dashboard, DAIS seeks to act as an operating system that enables brands to move away from tracking search rankings and instead focus on what they describe as 'engineering recommendations.'

The platform's proprietary technology is built around a 'Human Decision Intelligence Engine.' This engine scans publicly available marketing and discovery signals from across the open web, search engines, brand-owned sites, and various AI platforms. Key inputs analyzed include:

• AI citation data
• Behavioral and search trends
• Competitor brand visibility
• Brand content and recommendation patterns

To process this information, the DAIS platform is structured into three primary layers:

1. The Analytics Layer: This layer monitors how and where brands are being discovered across different AI systems.
2. The Intelligence Layer: This component analyzes and explains the reasoning behind why specific AI platforms recommend certain brands over their competitors.
3. The Deployment Layer: This layer outlines and implements strategic improvements designed to boost a company's visibility within AI engines.

Navigating the Future of Paid and Organic AI Search

While advertising is anticipated to play a larger role in AI search as the ecosystem matures, the recommendations provided by major large language models are currently still largely organic. DAIS has designed its future roadmap to support both organic optimization and sponsored AI discovery, positioning itself to serve as an infrastructure layer for search optimization regardless of how the industry evolves.

Market Traction and Competition

DAIS is currently operating in a competitive environment that includes global players such as New York-based Profound and Berlin-based Peec AI. Despite this competition, the bootstrapped Gurugram startup has established a strong foot in the market.

DAIS currently provides services to over 25 enterprise clients across diverse sectors, including healthcare, retail, automotive, technology, and consumer products. Notable brands utilizing its engine include ASICS, Ambuja Cement, Earthful, Suntone, and Sotheby Motorsport.

To date, the startup has remained largely bootstrapped and generated approximately Rs 2.89 crores in revenue over the last year. As AI platforms continue to see rapid adoption, the startup's founders believe that their intelligence engine will continue to grow stronger by learning from every new user interaction and recommendation pattern.