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

AI Agents Are Rewriting the Web: Fibr AI’s Bold Play to Personalize Every Page in Real Time

In an era where ads are hyper-personalized down to the individual, the website—the final destination for all that carefully targeted traffic—has stubbornly remained a one-size-fits-all experience. That gap between personalized marketing and generic landing pages is exactly what Fibr AI is betting it can close. The startup is using autonomous AI agents to dynamically tailor webpages in real time, creating one-to-one experiences for every visitor—a vision that has just attracted a fresh $5.7 million seed round from Accel, following an earlier $1.8 million pre-seed investment.

With WillowTree Ventures, MVP Ventures, and a roster of Fortune 100 operators also participating, Fibr AI has now raised $7.5 million total. But this isn’t just another AI tool for marketers. It’s a fundamental rethinking of how large enterprises approach website personalization—moving from a slow, human-driven model to one powered by software agents that work at machine speed.

The Problem: Ads Are Smart, Websites Are Dumb

For years, companies have perfected the art of targeting ads to micro-segments. But once a user clicks through, they often land on the same static page as everyone else. Traditionally, bridging that gap meant hiring agencies, engineering teams, and personalization software—an expensive, slow, and unscalable process. Even with the best tools, most enterprises can only run a few dozen experiments per year, hamstrung by manual coordination and rigid workflows.

Fibr AI argues that this human-heavy operating model is obsolete. Instead, its autonomous AI agents infer visitor intent, generate content variations, and continuously optimize pages in real time—without waiting for a human to push the button.

From Agency to Agent: The Fibr AI Model

“We are the software, and the agency is the workforce of agents we are deploying,” said Ankur Goyal, Fibr AI’s co-founder and CEO. This shift allows the platform to run thousands of experiments in parallel—something unthinkable under the old agency-driven model.

Founded in early 2023 by Goyal and Pritam Roy, Fibr AI spent its first two years quietly proving its approach. Adoption was slow at first, with only one or two customers as enterprises took time to evaluate the concept. But in the past year, momentum has surged, particularly among large U.S. companies in regulated sectors like banking and healthcare. Today, Fibr AI counts 12 enterprise customers and is signing three- to five-year contracts—treating website infrastructure as a long-term, standardized investment rather than a recurring project.

How It Works: AI Agents as the New Web Layer

Technically, Fibr AI sits on top of a company’s existing website, integrating with advertising, analytics, and customer data systems to understand how visitors arrive and what they’re looking for. Its AI agents then assemble and adjust page content—copy, imagery, layout—treating each URL as a dynamic, learning system rather than a fixed page.

Instead of manually configured rules or sequential A/B tests, Fibr AI runs large numbers of micro-experiments in parallel, updating experiences systematically as traffic flows in from different channels. The result: a website that evolves in real time, optimized for each visitor’s context and intent.

Cost and Speed: The Real Differentiator

For large enterprises, the shift from human-driven to agent-driven personalization has direct cost implications. Traditional website personalization typically combines software licenses with agency retainers and engineering time—tying costs to people rather than outcomes. Fibr AI’s platform is evaluated on cost per experiment and conversion impact, not the number of tools or people involved.

That operating model—not the AI buzz—was central to Accel’s decision to double down. “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.

Future-Proofing for the Agentic-Commerce Era

While most of Fibr AI’s business today is driven by personalizing experiences for human visitors, both Accel and Fibr AI 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, 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.”

Scaling Up: The Road Ahead

With the new funding, Fibr AI plans to expand 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.

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