Software R&D for complex decisions.

I validate technical bets before you bet the company. Then I build what actually works.

10 years building complex systems across energy, retail, and manufacturing. Emerging technology. Real-time simulation software. Machine learning pipelines at scale. Enterprise-grade backend services.

Now I apply my range to help technology leaders test and build high-uncertainty projects.

Technical decisions stick around

Your board needs an AI strategy by Q2. Your team is split on architecture: It's a big investment either way. That vendor's solution sounds perfect, but your engineers have concerns. The legacy system needs addressing, but a rewrite is a huge commitment.

These decisions stick around for years. The migration you choose today becomes the architecture your team lives with tomorrow. The vendor you select now shapes your product roadmap for the foreseeable future.

Many decisions get made based on who argues loudest, what worked in the past, or what's trending. But you're the one living with the consequences.

Diagram: The problem with technical decisions
There are many paths to a sticky technical decision.

Ship with confidence

I build the hardest part first.

You'll know if the system will scale in week 2, not month 8. We map the migration path (blockers and all) before you commit the team. We verify the vendor's claims for a fraction of the implementation cost.

No fluff. Just data and working code that you can test against your actual requirements.

The outcome is clarity: building with confidence or stopping before it gets expensive.

See how it works.

What you get

  • Week 1: You know if that "perfect" solution actually exists
  • Week 2: Your architecture debate ends with working prototypes
  • Week 4: You have confidence to proceed or evidence to pivot

Your senior engineers stay focused on current deliverables. You get an unbiased perspective from someone who's solved high-uncertainty problems in many domains.

You gain a competitive advantage through grounded technical decision-making. You move faster, because you know what works.

Diagram: Gut-instinct vs data-driven decisions
An empirical approach lets you see beyond the tip of the iceberg.

When you need it

  • You want to integrate emerging technology into your product
  • Your team can't agree on a critical architecture decision
  • You're evaluating build-vs-buy for new infrastructure
  • A vendor's promises need verification before you commit

I'm not a strategy firm (just talk) or a dev shop (just build). I validate through research and working code, then help you go where the evidence leads.

Ready to move with confidence?

Let's talk.