Fidelity, Brevan Howard, and Franklin Templeton just backed Puffer Finance's Series A. Fidelity partnered with Fireblocks for custody infrastructure. Mastercard invested in Paxos. JPMorgan put capital into ConsenSys. Lloyd's of London backed Circuit for digital asset recovery.

These aren't experiments. These are infrastructure bets by institutions that have historically built and governed traditional financial systems. They're now placing capital behind the protocols they expect to rely on as on-chain adoption scales.

The institutional question has changed. It's no longer "is crypto safe?" The capital flows answer that. The question now is: "We're committed to this future. How do we prove correctness, controls, and accountability?"

The answer the crypto security industry has given them is insufficient. And $2 billion in losses from 2025 alone proves it.

The Broken Security Model

Over $2 billion was lost to smart contract exploits in 2025. The vast majority of exploited contracts had already been audited. Balancer lost $121 million. It had been audited.

This keeps happening because the crypto security ecosystem is backwards. It's saturated on the right side of the development lifecycle with incident response, on-chain monitoring, and manual audits. It's nearly empty on the left, where security actually needs to happen: during development, before code reaches production.

The current model is inherently reactive. Teams get audited, deploy, hope nothing breaks, and rely on monitoring to catch exploits in progress. When hacks happen anyway, they turn to incident response firms to recover what they can.

This worked when crypto was smaller, when the stakes were lower, when only early adopters willing to accept higher risk were participating. That era is over.

Mission-Critical Systems Demand Formal Methods

Smart contracts now control institutional capital, settlement systems, and critical financial infrastructure. A single logic error can result in irreversible loss, market contagion, or cascading failures across protocols. This puts them squarely in the category of mission-critical systems.

Other industries figured this out decades ago. Aerospace, aviation, defense, nuclear energy, and rail transport all use formal methods: mathematically rigorous techniques for the specification, design, and verification of software. In those environments, software controls physical systems, human safety, or systemic financial risk. "Best effort" testing isn't acceptable. Mathematical verification is required to prove that certain classes of failures cannot occur.

The evolution follows a familiar pattern. These industries all started out like early crypto: fast-moving, unregulated, built by innovators willing to accept higher levels of risk. Early security practices were manual, reactive, and improvised. That worked while the scale was smaller.

As those industries matured, security spend shifted left. It became proactive, automated, and embedded into the development lifecycle itself. Manual review and reactive controls weren't sufficient anymore, not because people weren't trying hard enough, but because human-driven processes simply don't scale to complex, evolving systems.

The internet followed the same arc. Early systems were insecure by default, breaches were common, and security was patched after things broke. As software began underpinning critical business and financial systems, that model stopped working. Security spend shifted left: automated testing, secure-by-design frameworks, CI/CD guardrails, and continuous validation became standard.

Crypto is at that same inflection point right now.

What Institutions Actually Need

Institutions aren't asking nicely for better security. They're demanding it as a prerequisite for the capital they're deploying. The requirements are clear.

Security must be proactive. Issues need to be found during development, before they reach production, by identifying failure paths and invariant violations early. That's when they're cheapest and safest to fix. That's how teams reduce reliance on late-stage audits and reactive monitoring.

Security must be automated. Institutional systems are large, complex, and constantly changing. Security testing needs to run continuously without manual configuration or human review. Every code change needs to be analyzed automatically during development. That's the only way security can scale across large codebases, remove human bottlenecks, and support enterprise development velocity.

Security must be verifiable. Results need to be derived from formal, mathematical methods that are deterministic and auditable, not probabilistic AI output. Teams need to show what has been tested, which properties have been verified, and where coverage gaps remain. That's what allows enterprises to track assurance over time and explain residual risk to auditors, partners, and regulators.

This is the bar institutions expect. It's the bar the crypto security ecosystem has to meet if this space wants to move beyond early adopters into mainstream adoption.

Why AI-Based Security Tools Aren't Enough

LLMs and AI-based security tools are useful for certain contexts. They work well for smaller projects, early-stage teams, tight budgets, getting quick coverage, or surfacing obvious issues you might otherwise miss. They can speed up reviews and act like a second set of eyes.

But they cannot be sufficient for institutions. The reason is structural: they're fundamentally unverifiable. LLM outputs are probabilistic, not deterministic. You can't reliably reproduce the same result, and you can't generate audit-grade evidence that a specific property was proven rather than merely suggested.

In institutional settings, that's not a philosophical concern. It's a governance problem. Regulators are increasingly explicit that AI systems require strong controls around testing, validation, transparency, explainability, and accountability, precisely because complex models are hard to explain and hard to govern.

In April 2025, Patrick Opet, Chief Information Security Officer at JPMorgan Chase, published an open letter to third-party software providers warning that modern SaaS and AI-driven integration models are increasing systemic risk by prioritizing speed and convenience over provable security. The message was direct: large financial institutions are no longer willing to rely on opaque, black-box systems or checkbox compliance. They expect security controls that are demonstrable, auditable, and verifiably effective.

This is where formal methods diverge. In mission-critical industries, you don't rely on probabilistic outputs to certify safety properties. Aerospace software certification standards like DO-178C exist because systems have to behave predictably and verifiably. You need traceability, rigorous verification, and repeatable evidence throughout the lifecycle, not "best effort" assurance.

That same logic applies to smart contracts once they're carrying institutional-grade value and systemic risk. You need deterministic testing grounded in formal methods: the ability to prove, not assume, that certain behaviors are impossible.

There's also a market dynamic institutions understand instinctively: AI-first security is inherently commoditizable. Widely available models converge. Anyone can spin up an LLM wrapper, call it an "AI auditor," and compete on UX and pricing. That becomes a race to the bottom because the underlying intelligence isn't proprietary in a durable way. It's constrained by the same frontier models everyone else has access to, and those models are optimized for general language, not formal correctness.

Formal methods and deterministic tooling aren't subject to that same dynamic. They compound through proprietary infrastructure, deep program analysis, and verifiable outputs. They produce the one thing institutions actually need: evidence. Evidence of what was tested, what was proven, what remains unproven, and how that posture changes over time, in a way that stands up to auditors, partners, and regulators.

What We're Building at Olympix

We recently published an analysis of all 2025 EVM smart contract exploits. The findings are stark:

Over $2 billion was lost to smart contract exploits in 2025. The vast majority of exploited contracts had already been audited. Most losses stemmed from deep logic errors and invariant violations, not known vulnerability patterns. These failures occurred in complex, composable systems: upgradeable contracts, protocol integrations, and edge-case execution paths that manual review cannot reliably reason about.

98% of EVM smart contract exploits in 2025 would have been prevented had the teams used Olympix's proactive, automated, verifiable tooling during development.

We're working with organizations that sit at the intersection of crypto and traditional finance. Circle and Uniswap interact daily with banks, asset managers, payment networks, and regulators. They feel the pressure of institutional standards long before most of the ecosystem does. They don't have the luxury of treating security as a best-effort exercise or a box to check once a year.

We're also supporting a growing set of fintechs and traditional financial institutions building and deploying on-chain for the first time. These teams bring expectations shaped by Web2 and TradFi around controls, auditability, governance, and risk ownership. They quickly realize that existing crypto security workflows don't map cleanly to those requirements.

What we're delivering to both groups is the same thing: proactive, automated, verifiable security grounded in deterministic systems. Instead of relying on one-off audits or probabilistic tools, we help teams continuously surface deep logical issues during development, long before code reaches production.

As our systems mature, the improvements compound. We're seeing exponential gains in the depth of issues we can identify, the coverage we can achieve across complex codebases, and the confidence this gives teams operating under real regulatory and fiduciary constraints.

That confidence matters. For organizations that need a high degree of rigor, whether they're public companies, regulated financial institutions, or infrastructure providers underpinning both, security isn't about feeling comfortable. It's about being able to explain, defend, and prove decisions.

Olympix enables teams to answer the question institutions are asking: How do we prove correctness, controls, and accountability, not once, but continuously, as systems evolve?

The Shift Is Already Happening

Institutions aren't waiting for crypto to be safe. They're betting that it will be, and they're helping shape the infrastructure that gets it there.

The move on-chain is inevitable. The shift left of security spend is inevitable. The winners will be the ones who help institutions prove correctness, controls, and accountability.

Olympix is built for that moment. If investors and builders want crypto to scale beyond early adopters, they need to start demanding the level of security the ecosystem now requires, not the one it's been willing to accept.