Recently, Digidarts, a digital-first marketing agency pioneering AI-led marketing innovation, has launched DareAISearch, a first-of-its-kind AI-GEO solution that helps brands rank natively across AI-powered platforms like ChatGPT and Gemini. Alongside it, we’ve introduced SearchScore, a free tool that enables brands to measure and enhance their AI visibility.
Medianews4u.com caught up with Siddhartha Vanvani, CEO Digidarts.
Q. Are the lines blurring between performance marketing and brand building due to AI?
Over the last year, AI hasn’t just changed marketing, it has changed how we see marketing. What used to be two parallel tracks, “brand” and “performance,” now behaves like one system. Not because the definitions disappeared, but because consumer behaviour no longer separates them.
When AI models read a brand, they don’t differentiate between a review, a click, a story, or a purchase. They treat all of it as one stream of intent and trust. And that has quietly rewritten the rules.
Brand signals, consistency, sentiment, authority, now influence the same optimisation loops that drive conversions. And performance data, search patterns, click behaviours, audience pockets—feeds back into long-term brand building. The real story isn’t blurring. It’s convergence.
AI doesn’t blur brand and performance, it unites them. The future marketer’s job is to optimise a single funnel where brand signals are strategy inputs, not vanity outputs.
Q. How will AI Search redefine brand discovery in 2026? Will AI Search platforms/tools challenge Google?
Brand discovery is shifting from “searching” to “being guided.”
By 2026, consumers won’t type and scroll, they’ll ask, compare, and decide inside conversational, multi-modal environments powered by AI assistants. And in those moments, the brands that appear inside the answer, not just on a results page, will shape demand.
AI Search doesn’t evaluate brands as pages. It evaluates them as entities, stories, facts, sentiment, authority signals—woven together across the internet.
The brands that become easiest for AI to understand will become easiest for consumers to choose.
Google won’t disappear; it will remain the backbone of traditional search. But AI Search will grow into a parallel discovery ecosystem with its own rules, its own visibility hierarchy, and its own winners. For many high-intent journeys, product comparisons, “best for me” decisions, complex research, AI assistants will become the first touch, long before a SERP loads.
The shift isn’t about competition between platforms. It’s about a new layer of discovery that rewards clarity, structure, and trust.
Think of AI Search as a new media owner, one that chooses voices instead of links. Brands that can be the voice will own demand, regardless of where traditional SERPs land.
Q. Could you talk about the R&D that has gone into solutions like DareAISearch and SearchScore?
Over the last 18 months, we’ve invested heavily in R&D to understand one fundamental shift: search is no longer keyword-led, it’s model-led. Solutions like DareAISearch and SearchScore were born out of hundreds of experiments across large language models, knowledge-graph behaviour, entity recognition, prompt clusters, and structured data ingestion patterns.
For DareAISearch, our R&D spanned three layers: 1. AI Search Engine Behaviour: We ran thousands of prompt tests across ChatGPT, Gemini, Perplexity, Claude, and others to decode how LLMs interpret brands, rank entities, and decide which sources to cite. 2. Entity & Schema Engineering: We built proprietary frameworks to map a brand’s entities, relationships, and structured data so LLMs can correctly understand and recommend the brand. 3. Citation & Visibility Tracking: We developed a multi-platform tracking system that measures AI-Search visibility, citations, and prompt-level rankings, something that didn’t exist in the market until now.
SearchScore was developed to solve a complementary problem, brands needed a simple, universal metric to understand their AI-Search health.
We studied how LLMs absorb information from websites, feeds, third-party sources, and customer-generated content. We then converted these insights into a scoring system built on 40+ AI-readiness parameters: structured data, entity clarity, page quality, knowledge gaps, and AI-crawlability signals.
In total, our team has run over 50,000 prompt evaluations, 300+ structured data audits, and stress-tested models across 15 industries and 5 geographies. That’s what has shaped the intelligence layer inside DareAISearch and the scoring logic inside SearchScore.
Both products are still evolving and that’s by design. AI Search is moving fast, and our R&D engine allows us to continuously update models, signals, and execution workflows so our clients always stay ahead.
We built DareAISearch because the internet is about to be read by machines more than humans. Our R&D is less about tweaking titles and more about making a brand ‘understandable’ to a thinking engine.
Q. WhatsApp has been introducing new tools for businesses. Has this platform become a more useful platform for Digidarts’ clients as a result?
WhatsApp has quietly evolved from a chat window into one of the most powerful commerce surfaces in the country.
For many of our clients, the customer journey no longer starts on a website, it starts inside a conversation. Payments, catalogs, carts, automated flows, and Ads-to-WhatsApp have turned the platform into a full-funnel ecosystem. Discovery, consideration, and purchase now happen without the consumer ever leaving the thread.
And when the journey feels this natural, performance follows. Lead-gen brands are seeing more qualified conversations. E-commerce brands are recovering carts faster than before. The intent is warmer, the decisions quicker, the drop-offs fewer.
The story is simple: When commerce becomes conversational, friction disappears and conversions rise.
WhatsApp is no longer a ‘support app’, it’s a conversion surface. For brands that treat conversation as commerce, WhatsApp shortens the path from discovery to purchase.
Q. Digidarts has had a busy 2025 including expanding to the Middle East. How was 2025 for the agency?
2025 felt like a year where the company grew up, not just out.
Our move into the Middle East wasn’t just an expansion — it was a signal of who we were becoming: a company built to operate across markets, not confined by one. At the same time, we launched DareAISearch, the first step in turning Digidarts into a product-led intelligence company.
For years, we’ve been known for strategy and execution. This was the year we began building IP, scalable, defensible, and rooted in the future of AI-led discovery.
Two shifts defined 2025: New geography. New identity.
The work we delivered multiplied, not because teams worked harder, but because the systems got smarter. And that’s the real story: 2025 was the year Digidarts moved from agency muscle to product leverage.
In 2025 we stopped selling time and started selling leverage, IP that scales. Expansion into MENA and the launch of DareAISearch were two sides of the same strategy: geographic scale meets product scale.
Q. Being bootstrapped the company has focussed on building with sustainability and profitability at the core. What has been the big challenge in not relying on external funding?
Being bootstrapped comes with one core trade-off: you gain control, but you lose speed.
Without external funding, we had to be extremely thoughtful about how fast we placed big product bets, especially in AI.
Our biggest challenge was funding sustained R&D. AI products need steady engineering investment, so we focused on revenue-backed product development. We built features that solved real client problems, monetised them, and reinvested that revenue back into R&D. It kept us profitable while still moving forward on innovation.
Hiring was another constraint. We couldn’t scale engineering teams overnight, so we hired lean, multi-skilled talent and used data and technology partnerships to extend our capabilities without expanding headcount too fast.
Bootstrapping also meant every risk had to be measured. It slowed down some “moonshot” ideas, but it made our go-to-market discipline sharper and our product decisions more grounded.
Bootstrapping is a constraint that becomes a discipline. It forces you to build products that pay for themselves, which, in volatile markets, is often the wiser bet.
Q. There has been a lot of consolidation in the agency space. Would Digidarts look at an exit at some point by selling to another agency?
The agency ecosystem is going through a natural consolidation cycle, driven by AI, productisation of services, and the shift from manpower-heavy models to intelligence-heavy ones. But for us at Digidarts, consolidation isn’t a trigger for an exit; it’s a trigger for strengthening our IP.
Over the past two years, we’ve moved deliberately from a pure-play performance agency to a product-driven marketing intelligence company. Tools like Decisionboard, Dartboard, DareAISearch and SearchScore are not extensions of our service line, they’re assets designed to scale independent of headcount. And when your core value lies in proprietary IP, “selling” becomes a much more strategic conversation.
An exit is not our default path. Our default is autonomy, compounding, and long-term IP stewardship.
That said, we’re realists, not romantics. If tomorrow there is an opportunity that accelerates our product roadmap, expands global distribution, and amplifies client impact, we will examine it with clarity, not emotion.
But what we prefer, and what you’ll continue to see from us, are strategic alliances. Partnerships that preserve ownership while multiplying reach. Our Semrush collaboration is a perfect example, scale without surrender.
In a world where AI-native IP will define the next decade of marketing, control is not just an advantage, it’s leverage.
We aren’t building to be bought; we’re building to be indispensable.
Q. What goals have been set for 2026 and what is the gameplan to get there?
In 2026, our priority is to accelerate our shift into a product-led company by scaling global adoption of our AI visibility products. We aim to expand DareAISearch and SearchScore across 50+ enterprise accounts, strengthen our AI-GEO and entity infrastructure, and establish industry benchmarks around AI citation share.
With AI search engines expected to introduce ads this year, our goal is to be among the first companies globally to maximise performance and value from this new ad ecosystem.
2026 is about proving that AI visibility can be productised. Our job is to make brands discoverable to machines and then translate that discoverability into measurable business outcomes.
