Advertising and targeting are becoming increasingly personalized, but the final destination of traffic, the website, remains largely static. Fibr AI aims to fill that gap by using AI agents to turn common web pages into one-to-one experiences tailored to each visitor, a theory that has led Accel to step up its efforts.
Accel led Fibr AI’s $5.7 million seed round following a $1.8 million pre-seed investment in 2024. The new funding also includes participation from WillowTree Ventures and MVP Ventures, with Fortune 100 operators also participating as angel investors and advisors, bringing the startup’s total funding to $7.5 million.
For large companies, the gap between increasingly personalized advertising and a near-universal website experience has traditionally been bridged by a combination of personalization software, engineering teams, and marketing agencies. This model is time consuming, expensive, and difficult to scale. While ads can be instantly adjusted to suit different audiences, changing what happens once a visitor lands on your site often requires weeks of adjustment, and teams can only run a few experiments a year. Fibr AI argues that this human-heavy operating model no longer works. Instead, the startup uses autonomous AI agents to infer intent, generate variations, and continuously optimize pages in real-time.
Co-founder and CEO Ankur Goyal (pictured above, right) said in an interview that Fibr AI replaces a model focused on agency and engineering with autonomous systems that operate continuously.
“We are the software, and the agency is the workforce of agents that we deploy,” Goyal told TechCrunch, adding that this allows Fibr AI to run thousands of experiments in parallel each year instead of dozens.
Adoption was initially slow. Founded in early 2023 by Goyal and Pritam Roy (pictured above, left), Fibr AI only had one or two customers for most of its first two years as companies took time to evaluate the approach. Things started to change last year, Goyal said, with increased adoption among large U.S. companies including banks and health care providers, bringing the total number of customers to 12.
“We are an afterthought layer of infrastructure,” Goyal told TechCrunch. “Once you set it up, no one wants to think about it again.” This dynamic has led Fibr AI to sign three- to five-year contracts with large companies, he added. Large companies tend to treat their website infrastructure as something that should be standardized rather than continually reviewed.
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On a technical level, Fibr AI operates as a layer on top of existing websites, connecting to a company’s advertising, analytics, and customer data systems to understand how visitors arrive and what they might be looking for. AI agents then assemble and adjust page content, including copy, images, and layout, treating each URL not as a static page but as a system that continuously learns and optimizes. Rather than relying on manually configured rules or sequential A/B testing, the platform runs many micro-experiments in parallel and systematically updates the experience in response to traffic flows from different channels.
This change has a direct cost impact for large companies. Traditional website personalization typically combines software licenses with agency maintenance and engineering time, tying costs to people rather than results. Goyal said companies are increasingly evaluating Fibr AI’s platform based on cost per experiment and impact on conversion, rather than tools or number of people involved.
For Accel, its operating model, not the AI topic, was at the heart of its reinvestment decision. “Advertising today is one-to-one, but when a user visits a website, it’s one-to-many,” said Prayank Swaroop, partner at Accel. “You can create hundreds of ads for different audiences, but they all appear on the same page.” Fibr’s ability to transform this dynamic into one-to-one personalization stood out because it removed the agency and engineering bottlenecks that typically limit how far companies can push their experiments, he said.
Swaroop added that early adoption among businesses, particularly banks and healthcare companies, helped validate the paper. “These are regulated, conservative industries,” he says. “When they start saying, ‘We need this and we’re willing to pay for it,’ that gives us double the confidence.”
Securing future potential for the age of agent commerce
While much of Fibr AI’s business today is driven by personalizing experiences for human visitors, Accel and Fibr AI also see potential in the way AI agents are beginning to mediate online discovery. As users increasingly use large-scale language models and AI chatbots like OpenAI’s ChatGPT to research, compare, and shortlist products before visiting a website, Swaroop said a site’s ability to adapt based on what the visitor (or the AI system acting on the visitor’s behalf) already knows could become more important over time.
“It’s early days in that part, but the companies we want to support are those that are building for today’s needs while preparing for tomorrow’s shifts,” Swaroop said.
With the new funding, Fibr AI plans to continue building its technology base in India while focusing on expanding its sales and customer-facing teams in the US. The San Francisco-headquartered startup has an office in Bengaluru and has about 23 employees, with 17 based in India and the remaining six in the US.
Goyal said the startup is targeting about $5 million in annual recurring revenue and about 50 enterprise customers by the end of this year.
Fibr AI is entering a space long dominated by incumbents like Adobe and Optimizely, which provide experimentation and personalization tools to large enterprises. However, both Goyal and Swaroop argued that these platforms are constrained by how they are built and sold, and typically rely on marketing agencies and engineering teams to configure and operate them. They say this model makes it difficult to move quickly and scale experimentation, even as customer acquisition and messaging have become increasingly dynamic.
“Incumbent companies have been slow to bring products to market,” Swaroop said, adding that new features often arrive years after demand has changed.
