Why We’re Different

The Problem With Commerical Software

In many commercial software platforms, even straightforward requests can take months and cost thousands. Not because exporting a table to CSV or adding a new data field is inherently complex, but because the systems supporting these platforms are.

Large vendors typically operate on shared, multi-tenant systems that must behave consistently across hundreds of laboratories. A single change, even a minor one, may require:

• extensive regression testing
• documentation updates
• coordinated release cycles
• approval across several departments
• validation for regulated environments

Combine this with legacy codebases and broad compliance requirements, and a simple request becomes a major project. These processes exist for valid reasons: stability, consistency, and regulatory assurance. But the result is that laboratories often pay for enterprise overhead, not the work itself.

We Build Software Differently

Our systems are crafted specifically for each laboratory or research group using modern, modular architecture that keeps complexity low and flexibility high.

When you need a workflow tweak, a new field, or a custom export, it stays simple, because your system is designed for your environment alone.
No unnecessary modules.
No multi-tenant constraints.
No barriers to accessing your own data.

This is how scientific software should work: clear, responsive, and shaped around your needs.

---

1. Purpose-Built for Your Laboratory

We don’t sell one product to hundreds of laboratories – we design one system for you.

Every workflow, data model, instrument integration, and permission structure reflects the reality of your daily work. No unused modules. No compromises. No bending your operations to fit someone else’s system.

No unnecessary modules.
No hidden add-ons.
No paying for features you’ll never touch.
Just the software you need and nothing you don’t.

---

2. Affordable and Realistically Priced

Custom solutions are often more affordable than enterprise software because they avoid the extra modules, bureaucracy, and overhead that inflate costs. We keep your software lean -and your expenses low.

We believe under-funded laboratories and research groups deserve world-class tools, not watered-down versions of large enterprise systems. That’s why we prioritize:

• Low implementation costs
• Fair, predictable support pricing
• Modular design – pay only for what you use
• Ease of modification – small request stay small
• Long-term sustainability

---

3. Full Data Ownership and Transparency

Your laboratory shouldn’t be locked into someone else’s system. We build solutions that respect your scientific autonomy – your data belongs to you.
We enforce this principle everywhere:

• open, queryable formats
• unlimited exports
• documented database schemas
• Application Programming Interfaces (APIs) and direct access options
• no locked tables or hidden structures

You can move your data, integrate it, analyze it, or take it to another system whenever you choose.

---

---

5. A team who understands both science and software

Hyperion Data is led by Daniel Pasin, who has deep experience across laboratories, forensic science, and academia – including hands-on research, software engineering, and laboratory operations. After developing the Laboratory Information Management System (LIMS) for the Forensic Toxicology Laboratory at the San Francisco Office of the Chief Medical Examiner, he saw firsthand why traditional LIMS platforms fail the very teams they’re meant to support:

• unnecessary complexity
• overpriced customisation
• slow support cycles
• data lock-in
• costly modules no one uses

He started Hyperion Data to fix these problems for organisations without enterprise budgets or the luxury of waiting months for small changes.

Our academic experience has shown us another gap: valuable scientific research often remains under-utilised simply because it’s never translated into practical, operational software. Hyperion Data specialises in converting research outputs (algorithms, methods, workflows, and prototypes) into robust systems that practitioners can rely on, whether they’re in a laboratory, a policing environment, or another scientific domain.

---

---