The data storage industry has a force problem.

The dominant playbook in enterprise infrastructure is to build moats through complexity. Multi-tier pricing. Proprietary protocols. Ecosystem lock-in. Capacity you don't need, bundled with features you won't use. The strategy isn't to solve your problem efficiently - it's to make switching so painful that you tolerate inefficiency indefinitely.

This is fighting with force. It works until it doesn't.

For over a decade, I've practiced Brazilian Jiu-Jitsu, which descends from Judo. When you're outweighed by 50 pounds, you don't win by being stronger. You win by being more efficient, using leverage, and timing.

The founder of Judo, Kano Jigoro, established two core principles that every practitioner embodies not just on the mat, but in all facets of life:

Seiryoku-Zenyo - Maximum efficiency, minimum effort
Jita-Kyoei - Mutual welfare and benefit

When we acquired JetStor two years ago, these weren't aspirational values we decided to adopt - they were the only rational way to survive. We're a 32-year-old data storage company competing against hyperscalers and billion-dollar vendors. We don't have the capital to outspend them. We can't out-market them. We can't win with force.

But we can win with leverage.

Seiryoku-Zenyo: Maximum Efficiency, Minimum Effort

Kano Jigoro wasn't a large man. He relied on timing, leverage, and technique to neutralize opponents. Seiryoku-Zenyo isn't laziness - it's respecting physical reality. Energy is finite. Time is finite. Resources are finite. The elegant solution accomplishes the goal with the least waste.

In Judo, this is kuzushi - breaking your opponent's balance before attempting a throw. You don't lift them; you redirect their momentum. Minimal effort. Maximum effect.

In infrastructure, this means questioning every layer of abstraction, every "feature," every dollar in the bill.

Does this solve the actual problem, or does it solve the vendor's need for margin expansion?

The AI infrastructure boom has created a fascinating inversion. Everyone wants to sell you the latest NVMe, "AI-native" storage with built-in GPU acceleration, real-time inference engines - on and on and on.

What does your workload actually need?

If you're running LLM training, you don't need sub-millisecond latency. You need sustained sequential throughput. If you're doing inference at scale, your bottleneck isn't storage performance; it's the network.

Purpose-built systems beat general-purpose platforms when efficiency matters. This isn't ideology; it's thermodynamics.

At JetStor, we ask questions like:

• Can we deliver the performance you need with spinning disks instead of flash? (Cost drops 10x)
• Can we eliminate proprietary protocols and use open standards? (Lock-in drops to zero)
• Can we remove middleware layers entirely? (Complexity drops by an order of magnitude)

Sometimes the answer is no. But asking the question is the difference between fighting with force and fighting with technique.

Jita-Kyoei: Mutual Welfare and Benefit

Jita-Kyoei means "mutual welfare and benefit." In Judo, this is literal. You cannot learn without a willing training partner - an uke. If you injure your partner through carelessness or ego, you have no one to train with tomorrow.

Kano wrote: "If one merely enforces his own selfish claims, not only will he become hindered by opposition from others, but such selfishness will lead to self-destruction."

Enterprise infrastructure has inverted this principle. The standard playbook:

1. Win the deal with competitive pricing
2. Lock in the customer with proprietary formats
3. Extract increasing margin through "upgrades" and capacity add-ons
4. Make switching so painful that renewal is inevitable

This works in the short term. It self-destructs in the long term.

The alternative isn't charity. It's recognizing that durable relationships require both parties to become stronger from the exchange.

Your storage vendor should make you more capable, not more dependent.

What Mutual Flourishing Looks Like in Practice

Honest Pricing: Our margin is our margin. We don't hide capacity fees, support tiers, or "data egress charges" that only appear in year two. If you know what you need, you know what you'll pay. This isn't altruism - it's efficiency. Opaque pricing requires sales cycles, negotiations, lawyers, and procurement theater. Clear pricing closes in a week.

Platform Sovereignty: We use open standards (NFS, S3, iSCSI) because proprietary protocols are vendor handcuffs. If you outgrow us, or if we go out of business, your data isn't trapped. This might seem like undermining our moat. Actually, it's the only moat that matters: being good enough that you don't want to leave, rather than making it impossible to leave.

Purpose-Built Solutions: We tell you when flash isn't worth it. We tell you when our system isn't the right fit. The goal isn't to maximize deal size; it's to solve the actual problem. Mismatched solutions create support nightmares and churn. Correct solutions create references and renewals.

Transparent Economics: The AI infrastructure market is experiencing a bout of collective insanity around pricing. Vendors see "AI" in your budget and multiply their quotes by 3x. We publish real-world cost numbers. We explain our cost structure. We don't pretend that NVMe flash costs the same as HDD when it's dramatically more expensive to operate.

Why This Matters Now

The AI infrastructure market is experiencing a vendors' gold rush. Every hardware company is rebranding as "AI-native" and slapping massive margin increases on existing products.

This is force-based selling. It works until customers realize they're being sold solutions to problems they don't have.

The countervailing trend: sophisticated AI workloads migrating back to on-premises infrastructure. Not out of ideology, but arithmetic. When you're training models 24/7, cloud costs become untenable. When you're doing inference at scale, network latency becomes the bottleneck.

These migrations are led by teams that do the math. They know their workload characteristics. They know their TCO models. They know the difference between NVMe latency and HDD throughput.

These are our customers. They don't need to be sold. They need a partner who respects physics, respects economics, and respects the fact that their success is inseparable from ours.

What We're Building

JetStor exists at a strange intersection: old enough to have 30+ years of storage engineering, young enough (under new ownership) to rebuild from first principles.

We're not pivoting to cloud. We're not bolting AI features onto legacy architecture. We're not selling buzzwords.

We're building purpose-built storage for teams that know what they need:

• Massive sequential throughput for LLM training (HDD-based, NFS/S3)
• Low-latency random I/O for inference serving (NVMe-based, direct-attached)
• Archival capacity for dataset versioning (tape-compatible, S3 glacier-class)

We're pricing it honestly. We're using open standards. We're being transparent about the economics.

Not because we're nice guys (though we try to be), but because it's the only strategy that survives long-term in a market where customers are sophisticated, vendor lock-in is untenable, and operational efficiency is existential.

The Dojo Principle

Here's the thing about training Judo: the better your partner is, the better you become. If you train with people worse than you, your technique stagnates. If you train with people better than you, you're forced to improve.

JetStor's thesis is simple: our customers are becoming more sophisticated faster than vendors are adapting. They're running their own models. They're building their own infrastructure. They're doing the math themselves.

We're not trying to stay ahead of them. We're trying to train with them.

That's Jita-Kyoei. Mutual benefit isn't a platitude. It's a forcing function. Our customers' success makes us better. Their challenges force us to build better solutions. Their honesty about what works and what doesn't makes our product better.

The alternative is the path most vendors take: stay ahead through information asymmetry. Bury pricing in complexity. Lock customers in before they realize the economics don't work.

That's fighting with force. It works until it doesn't.

We'd rather use leverage.

‍

JetStor is a data storage infrastructure company serving government, enterprise, and AI research teams. If you're building AI infrastructure and want to talk about storage economics, workload characteristics, or why your current vendor's pricing doesn't make sense anymore, reach out.