We build the analytics platform we wish we'd had.
BiAnalyzia exists because data engineers in regulated industries keep solving the same problems — and keep burning out doing it. We took the work nobody wanted and automated it properly.
The problem that started the company.
The founding team spent a combined twenty years building data infrastructure for hospitals, pharmaceutical companies, and enterprise operations groups. We wrote the ETL glue. We negotiated the data-sharing agreements. We built the dashboards and then watched them silently drift away from reality six months later.
Every engagement started the same way. A stakeholder needed a number — patient readmission rate, clinical trial enrollment velocity, pharmacy inventory turns, operational cost per bed — and nobody could produce it without three weeks of SQL, manual cleaning, and handwritten transformations. Even when the number came out, nobody could prove it was correct.
The existing BI vendors assumed the hard work was already done. The existing ETL tools assumed you had a team of data engineers. The existing data-catalog tools documented the mess instead of fixing it. Nobody solved the actual problem — that operational data in regulated industries arrives broken, arrives often, and cannot be trusted by default.
We started BiAnalyzia because we wanted to stop doing that work by hand.
Governed, trustworthy analytics — without the six-month runway.
Governance isn't an afterthought. It's not a dashboard theme. It's not something you sprinkle on at the end. Governance is the product. Every feature we ship is designed so that the resulting analytics can be defended in a board meeting, an audit, or a regulatory review.
We refuse to ship “magic” automation that can't be reviewed by a human.
We refuse to hide the pipeline under a no-code layer that makes it opaque.
We refuse to assume your compliance team is a bottleneck — we treat them as a first-class user.
We refuse to let AI silently replace engineering judgment. AI proposes. Humans approve. Always.
Four principles. Zero compromises.
How we make decisions when the easy path and the right path point in different directions.
Speed matters. Truth matters more. If a pipeline is fast but wrong, it's worse than no pipeline at all — because now someone is making a decision on it. We optimize for time-to-correct-insight, not time-to-any-insight.
Every AI suggestion in BiAnalyzia ships with its reasoning. Every pipeline ships with its lineage. Every KPI ships with its source rows. If we can't explain how a number was produced, we don't show it.
Automation is a tool, not a replacement. Every consequential action — approving a mapping, deploying a pipeline, overriding a quality rule — requires an explicit human decision. We build for the analysts and engineers doing the actual work.
We don't retrofit compliance. Multi-tenant isolation, row-level security, audit logging, and role-based access are in the architecture from the first commit. We assume someone will audit us one day — and we treat every release as if that day is tomorrow.
A remote-first team of builders.
BiAnalyzia is a remote-first team of data engineers, product designers, clinical informaticists, and former BI practitioners. We've built data platforms inside public hospital networks, pharmaceutical R&D organizations, municipal utilities, and global consulting firms.
We've seen what works, what doesn't, and what executives say works but quietly doesn't.
We don't have a PR team. We don't have a “thought leadership” function. What we have is an engineering-heavy org chart and a product-obsessed founding team that reviews every customer escalation personally.
Painful work, turned into product.
A six-month project at a regional healthcare system needed readmission reporting across four hospital acquisitions, each with a different EHR and a different definition of “patient ID.” The project ran six months over schedule.
A pharmaceutical client asked for a simple enrollment velocity dashboard across twelve clinical trial sites — and discovered the underlying data had never been validated, reconciled, or stored in a single place.
We turned the painful work into the product. The canonical models in BiAnalyzia v1 came directly from the transformations we wrote by hand on those engagements — so nobody would have to do it again.
Four canonical models live: Healthcare, Pharma, Utilities, Education. AI-assisted onboarding, governed pipelines, and deterministic KPIs — running across regulated organizations in production today.
The first day a dataset arrives is the day your team gets answers.
The long-term vision for BiAnalyzia is a data platform where the first day a dataset arrives is the day your team gets answers from it. Not weeks of prep work, not a three-month modeling engagement, not a migration project that stalls after the first executive review.
We're building a future where any qualified analyst can stand up a governed, audited, canonical-modeled analytics environment in an afternoon — and where the AI mapping layer does the unglamorous work that used to eat 80% of data engineering time.
We're not there yet. But every release closes the gap, and our customers tell us they see it happening in real time.
Join us — or work with us.
If BiAnalyzia sounds like the platform you wish existed — or the team you wish you worked on — we'd love to meet you.