What the Beta Program Revealed About the Gap Between Generative AI and Compliance Grade AI

Earlier this year, our founding team joined Web Summit Vancouver as part of the Beta Startup program, a track reserved for companies with real traction and early customer adoption. With thousands of attendees, hundreds of AI products, and a global mix of founders, investors, and technical leaders, the event provided a clear snapshot of where the AI industry is today.

What we saw was a surge of generative AI tools built for speed, creativity, and automation. What we heard in private discussions was something very different. Investors and builders are beginning to realize that most AI tools cannot operate safely in regulated environments. Accuracy, provenance, and auditability were the missing pieces everywhere we looked.

Generative AI Dominated the Floor

From creative copilots to automated content systems and developer assistants, generative AI was the central theme across the exhibition halls and stages. Product demos focused on volume, efficiency, and rapid output. The narrative was consistent. Faster generation, fewer inputs, more automation.

But as impressive as many of these tools were, they shared a common limitation. Few of them had controls for:

• Verifying factual accuracy

• Enforcing source discipline

• Aligning with regulatory standards

• Tracking how answers were produced

This gap was noticeable to anyone with experience in finance, life sciences, or public market communication. The broader AI ecosystem is moving fast, but it is not yet building for environments where errors carry real consequences.

Investors Are Asking Harder Questions

The VCs we met did not ask about speed or creativity. They asked about safety, evidence, and reliability. This shift was clear across dozens of conversations.

They wanted to know:

• How hallucinations are prevented

• How answers align with the public record

• How systems can prove where information comes from

• How retrieval and reasoning steps are controlled

These questions suggest a maturing understanding of what makes AI viable at the enterprise level. Investors have seen the excitement around generative tools. They now want to understand how AI can operate in high stakes environments without introducing risk.

Founders in Regulated Sectors Recognize the Limits

The strongest validation came from conversations with founders in biotech, fintech, cybersecurity, and healthtech. They were excited about AI, but hesitant to use it beyond internal experimentation.

Their concerns were consistent.

• Benchmark scores do not guarantee reliability.

• Generic models misinterpret domain specific data.

• Tools without provenance increase legal exposure.

• No audit trail means no accountability.

One founder put it clearly. If a model misreads a single line of clinical data, that creates a regulatory problem, not a product issue. That mindset framed the entire event for us.

The Gap Between AI Hype and AI Reality

Web Summit highlighted a divide emerging in the market. On one side, generative AI continues to attract attention for its speed and creative potential. On the other, a growing group of investors and operators are looking for systems with discipline. They want AI that:

• Retrieves evidence, not assumptions

• Understands sequencing of events

• Flags uncertainty instead of speculating

• Provides audit trails for every answer

This is the difference between AI built for entertainment or convenience, and AI built for regulated industries.

Why the Beta Experience Validated Our Direction

Being selected as a Beta Startup placed Versance among companies building technology that already resonates with early customers. What stood out at Web Summit was how many investors and founders immediately understood why compliance grade AI matters, even if the term was new to them.

The conversations reinforced our core belief. The next chapter of AI will be shaped by accuracy, provenance, and verifiable reasoning. Generative AI created the excitement. Compliance grade AI will create the trust required for adoption in finance, biotech, and public markets.

Where This Points the Industry

Web Summit provided two important insights.

First, the AI industry is still focused on volume, speed, and creation. Second, the market is beginning to recognize that these qualities alone cannot serve regulated environments.

The companies that win in these sectors will be the ones that treat accuracy like a requirement, not a feature. They will be the ones that design for transparency and evidence discipline, not just impressive output.

Versance is committed to leading that category. The Beta program was a milestone, but more importantly, it confirmed a broader truth. AI is entering its next stage, and compliance grade intelligence is what will carry it into industries where trust is non negotiable.