About Cyrenza

To extend specialist-level expertise to every team that needs it. Whether you're a growing company building capacity or an enterprise expanding into new domains, the constraint shouldn't be headcount.

We build AI Knowledge Workers that operate at professional depth across finance, legal, real estate, insurance, consulting, marketing, and business operations. Eighty specialists, each built to work the way practitioners actually work, available whenever the work demands it.

A world where expertise scales with ambition. Where organizations of any size can pursue opportunities that once required building entire departments. Where the best teams get even better because they can focus on the work that matters most.

We see a future where humans focus on judgment, relationships, and the work that requires being human, while AI handles the research, analysis, and execution that consumes so much of professional life today. Not automation for its own sake, but genuine collaboration between human insight and machine capability.

Walk into any successful enterprise and you'll find the same thing: layers of specialists. Financial analysts poring over models. Legal teams reviewing contracts clause by clause. Compliance officers tracking regulatory changes. Research teams synthesizing market intelligence. Each person brings years of training and domain-specific intuition to their work.

Now walk into a growing mid-market company. You'll find talented people, but they're stretched. The CFO is also handling investor relations. The operations lead is managing HR. Everyone is doing three jobs because hiring specialists for each function isn't realistic yet.

This gap, between the expertise organizations need and the expertise they can access, shapes almost every business decision. It determines which opportunities get pursued and which get passed over. It influences the quality of analysis behind major investments. It affects how quickly companies can respond when markets shift.

We started Cyrenza because we believed this gap was solvable.

The question wasn't whether AI could perform business tasks. By 2024, that was settled. Large language models could write, analyze, summarize, and reason across almost any domain. The real question was whether AI could work the way professionals actually work.

A good financial analyst doesn't just run numbers. They know which assumptions matter most. They understand how different stakeholders will read the same projections. They've seen enough deals to sense when something doesn't add up, even before they can prove it.

A good contract attorney doesn't just spot legal issues. They understand business context. They know which terms are worth fighting for and which are standard. They anticipate how a clause might play out three years from now in a dispute no one is planning for.

This kind of expertise isn't just about information. It's about pattern recognition accumulated over years of practice. It's about judgment refined through repeated exposure to real situations. Could AI develop something similar?

We thought so. But only if we built it differently.

Most AI tools are generalists. They're designed to handle any question about any topic. Ask about tax implications, they'll give you an answer. Ask about lease terms, they'll give you an answer. The problem is that the answers have no depth. They read like someone looked something up rather than someone who actually works in the field.

We took the opposite approach. Instead of one AI that does everything adequately, we built many AIs that each do one thing well. We call them Knowledge Workers.

Each Knowledge Worker is designed for a specific professional function. A financial analyst that understands how to read balance sheets, build projections, and stress-test assumptions. A contract reviewer that knows what terms matter in different deal types and how to flag risks that aren't obvious. A compliance specialist that tracks regulatory frameworks and can assess where an organization stands.

We've built 80 of these specialists across finance, legal, real estate, insurance, consulting, marketing, and business operations. Each one understands the vocabulary of their field, the standards that apply, and the patterns that matter. They're not generalists pretending to have expertise. They're specialists that work within defined domains.

You open Cyrenza and start a conversation. You explain what you're working on. Maybe you need to analyze a potential acquisition. Maybe you're reviewing vendor contracts. Maybe you're trying to understand how a new regulation affects your operations.

A Knowledge Worker picks up the conversation. If they need more context, they ask. If you've uploaded relevant documents to your Vault, they reference them. Then they get to work.

The Vault is where your documents live. Financial statements, contracts, market research, internal memos, whatever context is relevant to your work. You organize it however makes sense. When Knowledge Workers need to reference something, they pull from what you've provided rather than guessing or hallucinating.

As Knowledge Workers complete tasks, the outputs are saved to your Records. An analysis becomes an artifact you can reference later. Sources are tracked. If you asked for a contract review last month and need to revisit it, you'll find it organized and accessible.

The whole system is designed around how work actually happens. You have a conversation. Work gets done. Outputs are preserved. Context accumulates over time rather than starting from scratch with every session.

When we say a Knowledge Worker specializes in finance or legal or real estate, we mean something specific.

A financial Knowledge Worker understands that a DCF model is only as good as its assumptions. They know how to stress-test projections and identify which variables matter most. They can read a set of financial statements and flag anomalies that deserve attention. They understand the difference between GAAP and IFRS and why it matters for cross-border analysis.

A legal Knowledge Worker knows how to parse contract language and identify terms that create risk. They understand that an indemnification clause in a software license is different from one in a construction contract. They can flag non-standard terms that might require negotiation and explain why they matter.

A real estate Knowledge Worker understands lease structures, cap rate analysis, and property valuation methods. They know the difference between triple-net and gross leases. They can analyze rent rolls and identify occupancy trends that affect asset value.

This isn't about having access to more information. It's about understanding how professionals in each field think about problems. The same facts look different to a lawyer than to a financial analyst. We built Knowledge Workers that reflect those differences.

We're careful about how we position what Cyrenza does. Knowledge Workers are not replacements for human professionals. They're tools that extend what humans can accomplish.

A Knowledge Worker can analyze a contract and flag potential issues. The decision about whether to push back on a term, how hard to negotiate, and what tradeoffs to accept still requires human judgment. The AI surfaces information and identifies patterns. The human makes decisions.

This isn't false modesty. It's an accurate description of what the technology can and cannot do. AI is very good at processing information, identifying patterns, and applying frameworks consistently. It's less good at navigating ambiguity, understanding organizational politics, or making judgment calls where the answer depends on values and priorities rather than analysis.

We designed Knowledge Workers with this boundary in mind. They show their reasoning. They cite their sources. When they're uncertain, they say so. They're built to support human decision-making, not to bypass it.

When you give an AI access to your financial statements, your contracts, or your strategic plans, you're extending significant trust. We take that seriously.

Your data is yours. We don't use customer data to train models that other customers access. We don't share it with third parties. Your environment is isolated from other customers.

We maintain SOC 2 Type II compliance, which means our security controls are audited annually by independent assessors. We meet GDPR requirements for customers operating in Europe and CCPA requirements for California. Enterprise customers can specify geographic data residency to meet regulatory requirements.

These aren't aspirational statements. They're operational commitments that we invest real resources to maintain. When you upload a sensitive document to Cyrenza, it stays within boundaries you control.

Cyrenza is an early-stage company building something we believe will matter. We're not a finished product. We're a team that ships improvements every week based on what we learn from customers actually using the platform.

Some of our most useful features came from watching how people work and noticing friction we hadn't anticipated. The platform today is meaningfully better than it was six months ago, and it will be meaningfully better six months from now.

We work closely with customers because that's how we figure out what to build next. If you're evaluating whether Cyrenza could help with the work you're already doing, the best way to find out is to try it. We'd rather show you than convince you.

We believe the organizations that thrive over the next decade will be those that figure out how to work with AI effectively. Not by automating everything, and not by ignoring it, but by finding the right division of labor between human judgment and machine capability.

We believe access to expertise shouldn't depend on how many specialists you can afford to hire. A ten-person company should have access to the same quality of financial analysis or legal review as a Fortune 500 firm. The barrier should be whether you know what you need, not whether you have headcount.

We believe AI should be transparent about what it's doing and honest about its limitations. Technology that asks to be trusted blindly isn't trustworthy. Technology that shows its work and invites scrutiny is.

That's what we're building. That's why Cyrenza exists.