Data Visualization & Business Intelligence
We build self-serve BI experiences on Looker, Power BI, Tableau, Sigma or Hex, governed by a semantic layer, embedded in your products and grounded in metrics your finance team has signed off on.
BI that gets used, not just built.
Most BI projects ship dashboards. Few ship adoption. The difference is in three places: the metrics layer (does the dashboard match what the business actually means by "revenue"?), the experience (does it load in under two seconds, on the device the user actually has?) and the governance (can you trust the number when the CFO asks?). Get those three right and BI becomes the most-loved tool in the company.
Audience-first design
Boardroom dashboards are not operator dashboards. We design for the actual person, not for the BI tool's default template.
Metrics certified once
Every metric is defined once, in the semantic layer, peer-reviewed by finance and product. No more reconciliation marathons before every QBR.
Adoption as the success metric
We measure dashboard opens, not dashboards built. If nobody opens it, it does not count and we kill or fix it.
Why BI is being reinvented for the second time in a decade.
AI-assisted analytics, embedded BI and the semantic-layer revival are converging to make the next BI generation fundamentally different from Tableau-era dashboards.
A decade of dashboard tools and most leaders still wait days for an analyst. AI-assisted BI plus a semantic layer finally cracks it.
Customer-facing analytics inside SaaS products is the fastest-growing BI segment and a real revenue lever for product teams.
A 2024 Mode study showed dashboard graveyards across every enterprise. Rationalization and governance are now competitive differentiators.
Data Visualization & BI services we offer.
Each item below is a discrete, measurable workstream we own end-to-end, with senior engineers, real timelinesand the test coverage to back it up.
Executive and operational dashboards
Boardroom-grade dashboards that pass finance review, plus operator dashboards engineers actually use mid-shift. Different audiences, different cuts, same governed truth.
Self-serve analytics
Governed semantic layer + LLM-assisted natural-language queries. Business users get answers in minutes, your data team gets time back to build.
Embedded analytics in products
Customer-facing dashboards inside your SaaS product, white-labelled, multi-tenant, row-level secured, with SDKs for React and mobile.
Data storytelling
Narrative-driven dashboards that explain WHY a number changed, not just what changed. Built for the audience that does not read SQL.
Mobile and tablet-first BI
Field teams, store managers, operations leads, dashboards that work on the device they actually carry, with offline caching and push alerts.
BI governance and rationalization
Catalog the dashboards you have, kill the ones nobody opens, certify the ones that matter. The "200 versions of the revenue dashboard" problem ends here.
We're fluent in your stack.
Vendor-agnostic by design. We pick the right tool for the problem in front of us, not the one our partner discounts apply to.
Real engagements. Real numbers.
Replaced 380 dashboards with 42 certified ones
BI rationalization audit identified 90% of dashboards as unused or duplicated. Curated catalog cut maintenance cost and ended metric-drift arguments.
Six reasons enterprises run Data Visualization & BI with Infivit.
Built for the 2026 reality of Data Visualization & BI: the actual buyer pain, the actual technical constraints and the actual outcomes that matter, not generic data buzzwords.
Dashboards designed for the actual user.
Boardroom is not operator is not customer. We design for the person, the moment and the decision, never for the BI tool's default template.
Performance you can demo to the CFO.
Aggregates, materializations and pre-computed semantics. Dashboards open instantly even on 50M-row tables, even on a phone, even on conference Wi-Fi.
Natural-language queries, governed answers.
Business users ask in English, the LLM translates against your semantic layer, the answer is correct because the metric is certified. Self-serve that finally works.
Every number traceable, every time.
Semantic layer defines metrics once, lineage shows derivation, governance approves changes. Reconciliation marathons before every QBR end here.
Customer-facing analytics in your product.
White-labelled, multi-tenant, row-level-secured SDKs for React and mobile. Turn your data into a paid product feature, not just an internal cost center.
We track who opens what, every week.
Usage analytics on the BI itself. Unused dashboards get deprecated, valued ones get invested in. The graveyard ends, signal-to-noise ratio rises.
The questions you were already going to ask.
Got a data visualization & bi problem?
Let's ship the fix.
A 30-minute call with one of our senior engineers, no slideware, no scoping doc. You leave with a concrete view of what the first 30 days look like.