About
Why Datahelyx exists
Most companies don't have a software problem — they have a translation problem. Business needs get lost between stakeholders, agencies, and code.
Datahelyx was founded on a simple observation: the companies that struggle most with technology aren't short on tools — they're short on partners who understand both the business problem and the engineering to solve it. Off-the-shelf software forces workarounds; big agencies deliver slowly and bill by confusion; freelancer patchworks leave nobody accountable.
We sit in the gap. A small, technically deep team that takes a problem from a conversation to a deployed, documented, supported system — whether that's a full product, a data platform, or an AI co-pilot that quietly removes hours of manual work every week.
The name comes from the double helix: two strands — software engineering and data — wound together. Everything we build combines both.
How we think
Operating principles
Outcomes over output
We scope engagements around a business result — reporting time cut, a workflow automated, a product shipped — not a pile of features.
Technically honest
If a spreadsheet solves your problem, we'll say so. We don't sell AI where a cron job will do — and we don't overclaim on areas we haven't delivered.
Built to hand over
Everything we ship comes documented, tested, and explained. Your team keeps the keys — no black boxes, no lock-in.
The team
Small by design, senior by default
Datahelyx is founder-led and deliberately small: every project gets senior engineering attention, not a hand-off to juniors after the sales call.
Founding team
Engineers with backgrounds spanning data science, full-stack development, and machine learning — experience across education, retail, and professional-services projects, from database design and ETL pipelines to production LLM systems. Detailed bios and photos are coming soon; in the meantime, the fastest way to evaluate us is a conversation.
Tech stack
The tools we reach for
Chosen for reliability and longevity — boring where boring is right, cutting-edge where it earns its place.
Open-source work and code samples: github.com/datahelyx