Syllo, an AI-driven data infrastructure company, has raised $30 million in funding to power a new generation of self-learning enterprise systems. The round was led by Venrock and Two Seas Capital LP, alongside participation from additional institutional investors.

Founded by Jeffrey Chivers, Syllo is rethinking how organizations handle data in an era defined by machine intelligence. Its mission is straightforward but ambitious  -  to make data infrastructure that learns, adapts, and optimizes itself, the same way humans do.

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From Static Storage to Living Systems

For decades, data infrastructure has been built for one purpose  -  to store and serve information. But the explosion of AI and real-time analytics has exposed a massive flaw: most enterprise data remains passive. In fact, IDC estimates that over 70% of enterprise data goes unused, and data teams spend more than half their time preparing or cleaning data instead of generating insights.

Syllo’s answer is to turn data into a living system  -  one that continuously re-organizes around context, learns from interactions, and becomes more intelligent over time. Its platform integrates machine learning orchestration, data lineage mapping, and predictive optimization to eliminate friction in how data flows between tools and teams.

“We’re designing infrastructure that thinks with you,” said Jeffrey Chivers, Syllo’s founder and CEO. “The future of enterprise software won’t just be about data visibility  -  it’ll be about data that adapts in real time to how the business evolves.”

This approach collapses the distance between insight and execution, enabling organizations to deploy AI-driven decisions faster and with higher accuracy.

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Riding the AI Infrastructure Wave

The timing couldn’t be better. The AI infrastructure market is projected to exceed $193 billion by 2032, growing at a CAGR of 24.5%, according to Fortune Business Insights. Meanwhile, the broader data infrastructure market is expected to reach $72.8 billion by 2030, driven by the enterprise shift toward hybrid and cloud-native environments.

Companies are learning that it’s not enough to collect data  -  they need to make it intelligent. A 2025 Forrester study found that 64% of enterprise leaders cite “data fragmentation” as their biggest barrier to AI transformation. Syllo’s platform directly addresses that by unifying data pipelines and teaching them to self-optimize over time.

And it’s here, in this intersection between scalability and learning, that Syllo’s true advantage  -  and a crucial insight for founders  -  reveals itself.

Most companies chase efficiency. Syllo chases adaptability. Efficiency makes things faster; adaptability makes them future-proof.

This is the kind of design principle that separates good infrastructure from great ones  -  and it applies to startups as much as to systems.

If you build for efficiency, your product performs well in today’s conditions. But if you build for adaptability, your product evolves with tomorrow’s conditions. The former is linear; the latter is exponential.

Syllo’s architecture is essentially a metaphor for startup survival itself: systems  -  and companies  -  that learn faster than their environment are the ones that dominate it.

This is the silent truth of AI’s new wave: the real competitive advantage isn’t data volume, it’s learning velocity. Every founder building in AI, SaaS, or analytics should take note  -  the winners won’t be those who automate the most tasks, but those who automate the act of learning itself.

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Backed by Long-Term Builders

Syllo’s $30 million round was led by Venrock, one of Silicon Valley’s oldest venture firms, known for early investments in Apple, Cloudflare, and Nest, alongside Two Seas Capital LP, which specializes in deep-tech and cloud automation.

Their participation signals that investors see Syllo not just as a data company, but as a foundation-layer bet  -  the type of platform that underpins how future AI systems will operate.

The backing also reflects a broader funding shift. According to PitchBook, global investment in AI infrastructure startups rose 42% year-over-year, reaching $14.7 billion in 2024, as investors increasingly move capital from consumer AI applications to the underlying infrastructure layer  -  the so-called “picks and shovels” of the AI revolution.

This influx of capital into enterprise-grade AI infrastructure validates the thesis that intelligent automation starts at the data layer  -  not the model layer.

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Data as a Strategic Weapon

Syllo’s technology isn’t just improving how companies use data  -  it’s redefining the role of data in strategic decision-making.

Through AI-driven data orchestration, Syllo ensures that every byte of information a company stores is continuously validated, prioritized, and contextualized. That allows decision-makers to move faster, cut costs, and build feedback loops that sharpen over time.

It’s not just automation  -  it’s cognition at scale.

And as Gartner predicts that by 2026, 45% of large enterprises will implement AI-driven automation in data governance, Syllo is perfectly positioned to power this evolution. By 2030, over 80% of new enterprise applications are expected to rely on adaptive, learning-based infrastructure (IDC).

For clients, this means that the once “back-office” data stack becomes a front-line competitive advantage.

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The Road Ahead

With its new capital, Syllo plans to expand its engineering and AI research teams, deepen integrations with major cloud ecosystems, and roll out new modules for predictive governance and autonomous optimization.

The company is also partnering with early enterprise customers in sectors such as healthcare, logistics, and finance  -  industries where milliseconds matter and real-time learning translates directly into bottom-line results.

Its long-term vision is bold: to become the operating system for adaptive data intelligence, powering the world’s most dynamic organizations.

“The enterprises that win this decade will be the ones whose data infrastructure evolves faster than their competitors,” said Chivers. “We’re just building the tools to make that evolution automatic.”

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