Accel doubles down on Fibr AI as agents turn static websites into one-to-one experiences

While advertising and targeting have become increasingly personalized, the website — the final destination for that traffic — has remained largely static. Fibr AI aims to bridge that gap by using AI agents to turn generic webpages into one-to-one experiences tailored to each visitor, a thesis that has prompted Accel to double down on the company.

Accel has led Fibr AI’s $5.7 million seed round following an earlier $1.8 million pre-seed investment in 2024. The fresh funding also included participation from WillowTree Ventures and MVP Ventures, alongside Fortune 100 operators joining as angel investors and advisors, bringing the startup’s total funding to $7.5 million.

For large companies, the gap between increasingly personalized ads and largely generic website experiences has traditionally been filled by a mix of personalization software, engineering teams, and marketing agencies — a model that is slow, expensive, and difficult to scale. While ads can be tailored instantly for different audiences, changing what happens once a visitor lands on a site often requires weeks of coordination and limits teams to running only a handful of experiments each 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.

Fibr AI replaces the agency- and engineering-heavy model with autonomous systems that operate continuously, Ankur Goyal (pictured above, right), the co-founder and chief executive, said in an interview.

“We are [the] software, and the agency is the workforce of agents we are deploying,” Goyal told TechCrunch, adding that this allows Fibr AI to run thousands of experiments in parallel rather than a few dozen each year.

Adoption was initially slow. Founded in early 2023 by Goyal and Pritam Roy (pictured above, left), Fibr AI had just one or two customers for much of its first two years as enterprises took time to evaluate the approach. That began to change last year, Goyal said, with adoption picking up among large U.S. companies, including banks and healthcare providers, bringing the total number of customers to 12.

“We are an infra afterthought layer,” Goyal told TechCrunch. “Once it’s set up, nobody wants to think about it again.” That dynamic, he added, has led Fibr AI to sign three- to five-year contracts with large enterprises, which tend to treat website infrastructure as something to standardize rather than continuously revisit.

At a technical level, Fibr AI operates as a layer on top of an existing website, connecting to a company’s advertising, analytics, and customer data systems to understand how visitors arrive and what they are likely looking for. Its AI agents then assemble and adjust page content, such as copy, imagery, and layout, treating each URL as a system that learns and optimizes continuously rather than a fixed page. Instead of relying on manually configured rules or sequential A/B tests, the platform runs large numbers of micro-experiments in parallel and updates experiences systematically as traffic flows in from different channels.

That shift has direct cost implications for large enterprises. Traditional website personalization typically combines software licenses with agency retainers and engineering time, tying costs to people rather than outcomes. Goyal said enterprises are increasingly evaluating Fibr AI’s platform based on cost per experiment and conversion impact, rather than the number of tools or people involved.

For Accel, that operating model — rather than the AI buzz — was central to the decision to invest again. “Advertising today is one-to-one, but when users land on a website it becomes one-to-many,” said Prayank Swaroop, a partner at Accel. “You can create hundreds of ads for different audiences, but they all still land on the same page.” Fibr’s ability to turn that dynamic into one-to-one personalization, he said, stood out because it removed the agency and engineering bottlenecks that typically limit how far enterprises can push experimentation.

Swaroop added that early enterprise adoption, particularly among banks and healthcare companies, helped validate the thesis. “These are regulated, conservative industries,” he said. “When they start saying, ‘We need this, and we’re willing to pay for it,’ that’s when we feel confident doubling down.”

Future-proofing for the agentic-commerce era

While most of Fibr AI’s business today is driven by personalizing experiences for human visitors, Accel and Fibr AI also see potential in how AI agents are beginning to mediate online discovery. As users increasingly research, compare, and shortlist products using large language models and AI chatbots, including OpenAI’s ChatGPT, before visiting a website, Swaroop said, the ability for sites to adapt based on what a visitor — or an AI system acting on their behalf — already knows could become more important over time.

“That part is still early,” Swaroop said, “but the companies building for today’s needs while being ready for that shift tomorrow are the ones we want to back.”

With the new funding, Fibr AI plans to focus on expanding its sales and customer-facing teams in the U.S., while continuing to build out its technical base in India. The San Francisco-headquartered startup maintains an office in Bengaluru, with 17 of its roughly 23 employees based in India and the remaining six in the U.S.

Goyal said the startup targets about $5 million in annual recurring revenue by the end of this year and around 50 enterprise customers.

Fibr AI is entering a space long dominated by incumbents such as Adobe and Optimizely, which offer experimentation and personalization tools to large enterprises. But both Goyal and Swaroop argued that those platforms are constrained by how they are built and sold, typically relying on marketing agencies and engineering teams to configure and operate them. That model, they said, makes it difficult to move quickly or scale experimentation, even as customer acquisition and messaging have become increasingly dynamic.

“Incumbents have been slow in bringing out products,” Swaroop said, adding that even when new features arrive, they often come years after demand has shifted.