QuickAds’ $1.7 million bet: Can AI fix advertising’s 90% failure rate?

When nearly nine out of ten digital ads fail to make an impact, the problem isn’t lack of data; it’s disconnection. That’s the premise on which QuickAds, a global martech startup founded by former leaders from Accenture, McKinsey, and Ogilvy, is staking its $1.7 million seed round led by Kae Capital.

Positioned as the world’s first ‘Ads Operating System’, the company aims to fuse creative automation, ad intelligence, and performance analytics into one connected loop. This is a system designed to eliminate the guesswork that defines much of digital advertising today.

The company’s funding round today also saw participation from executives at Google, Meta, Traya, and Rainforest.life. This signals industry appetite for martech tools that can close the gap between idea, execution, and learning. However, in a world already drowning in AI-driven tools, QuickAds faces the challenge of proving that speed and scale don’t come at the cost of strategy or originality.

From dashboards to decisions

In a conversation with Campaign, Nitin Mahajan, founder and CEO of BrandBooster.ai and QuickAds.ai maintained that marketing doesn’t lack data; it lacks connection. “Every tool solves a slice, but no one unifies creative, media, and performance. Billions are lost in the gaps between idea, execution, and learning,” he added. “QuickAds was born to close that loop, with an OS where creative inspiration, data, and campaign results finally work as one continuous feedback system.”

That vision took shape in 2023, when Mahajan and his founding team—drawing on their consulting and advertising agency experience—recognised a flaw in how marketing systems operate. They realised that dashboards don’t fix disconnection. While Google and Meta optimise distribution; Adobe polishes output. However, Mahajan notes that none teach what to make next.

“Our consulting DNA showed us strategy dies between insight and execution. QuickAds bridges that: real-time creative intelligence that learns from outcomes and directly generates the next best creative, not another static report,” he emphasised.

This ‘OS’ is designed less as a dashboard and more as a living creative brain. It continuously analyses over 20 million ads, ranking them on metrics such as click-through rates (CTR), watch time, engagement, and return on ad spend (ROAS). Only the top performers feed back into its library, creating what the company calls a “creative feedback graph.”

Eliminating the guesswork

QuickAds’ pitch to performance-driven D2C brands, agencies, and enterprise teams is straightforward: turn advertising from a guessing game into a measurable science. “We don’t guess—we measure,” said Mahajan. “Across $200 million-plus in ad spend, clients see up to 2.5× higher ROAS and 40% lower CAC. Our AI ranks more than 20 million ads scene-by-scene on emotional tone, structure, and conversion probability. It’s not ‘what’s trending’ but it’s ‘what works.’ Every creative is pre-tested for fatigue, compliance, and resonance before it even launches.”

The company claims results that would appeal to any marketer facing performance fatigue. These include a 45.7% reduction in customer acquisition cost (CAC), 55% improvement in ROAS, and over 20,000 campaigns already managed through its system. However, Mahajan insists the deeper innovation isn’t automation. Instead, it’s the integration of learning cycles, by teaching the machine to understand why an ad works.

“Most ads fail not in creation, but in the gap between creation and learning,” he says. “AI closes that loop. QuickAds analyses every frame, word, and CTA against live benchmarks, predicting performance before spend. Big platforms optimise distribution, not content. We built the missing layer—the creative brain that learns before you waste budget.”

Where the funding flows

The $1.7 million seed round, Mahajan says, “powers depth, not breadth.” About 65% of the investment will go into AI engineering, which includes developing its proprietary Creative Graph, multilingual BrandKit 2.0, and pre-testing engine. The remainder will fund market expansion across India, Southeast Asia, and the UK.

“Milestone one is self-learning brand profiles that auto-generate on-brand assets in seconds,” he adds. “The goal is creative intelligence that feels bespoke, not generic.”

QuickAds’ product development hasn’t been linear. Mahajan is candid about the missteps. “We’ve failed plenty and that’s the point,” he says. “Early models misread sarcasm, cultural nuance, and over-indexed on engagement metrics. We rebuilt from scratch using a multimodal architecture that understands visuals, tone, and context together. Those mistakes taught us humility. AI must learn with culture, not just from it. That’s why QuickAds gets smarter every campaign.”

That evolution—from overfitting to contextual learning—highlights one of AI marketing’s toughest frontiers: understanding culture as data. QuickAds’ willingness to publicly discuss its failed experiments may help position it as a credible, learning-led player in a category where hype often outruns substance.

Moreover, an emphasis on engineering over expansion suggests that QuickAds is prioritising product credibility before aggressive scaling. This strategy could well differentiate it in a martech space crowded with marketing automation tools chasing quick wins.

QuickAds isn’t chasing enterprise marketing departments just yet. “We’re built for performance-driven D2C brands, agencies, and enterprise teams managing $10,000 to $500,000 a month in spend,” says Mahajan. The go-to-market model mixes self-serve SaaS for smaller clients with a managed ‘Creative-as-a-Service’ tier for larger brands.

Growth, he explains, will come through integration with Shopify, Meta, and Amazon ecosystems, with regional hubs in India and Singapore. “Every workflow adapts to the client’s existing stack—so adoption feels seamless, not surgical,” he adds.

QuickAds’ companion platform, BrandBooster.ai, adds another layer of strategic oversight. It merges creative automation with human-led strategic intelligence, offering what Mahajan describes as “AI + human collaboration.” According to the company, over 35,000 businesses have already used BrandBooster’s platform, with clients paying only for measurable outcomes under a “results-first” pricing model.

Localising for India

As QuickAds scales across APAC, India is central to its strategy, both as a market and as a testbed for cultural adaptation. “India is where creative meets chaos and we love that,” Mahajan says. “Our models are fine-tuned for local scripts, idioms, and cultural archetypes. One auto-care client ran eight-language campaigns in 48 hours, cutting cost 70% while lifting CTR 2.1×. Localisation here isn’t translation; rather it is emotion transfer, powered by AI that understands context, not just text.”

The localisation challenge goes beyond language. India’s digital advertising economy is high-volume but low-margin, where brands prioritise speed-to-market, cultural nuance, and price sensitivity. QuickAds is attempting to encode these variables into its AI, ensuring the system learns emotional resonance as much as engagement metrics.

In markets like India, where consumer diversity outpaces data consistency, such adaptability could determine whether the platform scales sustainably.

With creative automation proliferating, a growing number of marketers worry that AI-generated ads will lead to homogenisation or what the internet now calls ‘AI slop’. Mahajan acknowledges the concern.

And he insists that QuickAds was built to fight sameness. The system pre-tests every ad for originality, tone, and diversity before launch.

“AI brings speed and pattern learning; humans bring taste. Together, they outthink templates. We don’t automate creativity, we scale it. Think of QuickAds as the creative director that never sleeps,” Mahajan added.

The company’s architecture blends AI pre-testing with human feedback loops, designed to prevent creative repetition and ensure that output remains distinctive. Mahajan insists this balance between automation and taste is the only sustainable way to integrate AI into advertising workflows.

Redefining agency roles

If brands can now generate, test, and scale ads in minutes, what happens to creative agencies? Mahajan doesn’t see it as replacement but acceleration.

“This isn’t the death of strategy; it’s its acceleration,” he says. “When ads are created, tested, and iterated in minutes, creativity becomes an agile process. Agencies move from execution to insight; marketers move from dashboards to decision design. The new competitive edge isn’t bigger budgets; it’s faster, smarter learning cycles.”

For agencies, that shift could mean moving up the value chain—from making ads to designing adaptive creative systems. For marketers, it signals an era where creative iteration becomes the new competitive advantage, blurring the line between media optimisation and storytelling.

QuickAds enters the market at a time when marketing budgets are tightening, performance expectations are soaring, and AI adoption is simultaneously thrilling and unnerving the industry. With giants like Meta, Google, and Adobe expanding their own AI creative suites, startups like QuickAds must differentiate on depth rather than speed.

Its claim to build the first ‘Ads Operating System’ will face scrutiny as marketers test whether its intelligence truly connects creative, analytics and performance or simply adds another layer of automation to an already crowded stack. Yet, if QuickAds’ system can indeed cut through the noise and learn across markets, it could redefine how creative and media finally talk to each other.

For all the technology involved, QuickAds’ thesis circles back to a very human frustration: advertising’s inability to learn fast enough. As Mahajan puts it, “Marketing doesn’t need more tools. It needs a tighter loop between what we imagine, what we make, and what we learn.”

Whether QuickAds’ $1.7 million seed round is enough to prove that loop can be built remains to be seen. But if it succeeds, it might just mark the start of a new era—where creativity and computation stop competing and start co-evolving.