Finance, sales, and ops pull three reports and get three different revenue numbers. We build custom dashboards that give every team the same verified KPIs. They stay fast as your data grows, and your managers can ask them questions in plain English instead of waiting on an analyst.
Sales and finance count revenue differently. We move every KPI into one metric layer, and all dashboards show the same number.
Monthly exports leave reports weeks behind. For a US childcare operator, we switched to daily automated runs and saved the team 30+ hours a month.
Key data often sits in legacy or closed systems. We build integrations within each vendor’s terms and move that data into your warehouse.
Embedded analytics and custom permissions push Power BI and Tableau into workarounds. Custom code handles that logic directly.
Queries on production tables slow down as data grows. Separate layers, precomputed aggregates, and caching keep load times steady.
When every question becomes an analyst ticket, people stop asking. Natural-language queries let managers get answers themselves.
We start with your data model, your user roles, and the decisions your teams make every day. We define the metrics, aggregation logic, and API first, and only then design the screens.
If an off-the-shelf tool fits, we’ll build your dashboards in Power BI, Tableau, or Looker on top of a clean data model. Not sure which tool to pick? We can help you choose one and set up governance through business intelligence consulting.
Transactions, devices, and stock levels can change minute to minute. To show them live, you need streaming or scheduled feeds, and building those data pipelines is where most of the engineering goes. We set each refresh rate to match how fast the decision behind it has to happen.
Your customers expect to see analytics inside your product. We build embedded dashboards that follow your user model and your brand, whether you’re extending an existing app or building a new SaaS platform with us.
AI is worth adding when it gets people from a question to an answer faster. We add natural-language queries, forecasts, and anomaly alerts to the dashboards your team already opens every morning, using the same approach we take in AI-driven data analytics.
A chart can’t be more accurate than the data feeding it. That’s why data integration takes up a big share of every project. We connect your CRM, ERP, billing, marketing, and IoT sources and reconcile their records.
What should each role see first? What can sit one click away, and what doesn’t belong on the screen at all? We answer those questions through UX research and interface design with the people who’ll actually use the dashboard.
Enterprise dashboards need role hierarchies, audit logs, and rollouts across regions. We also take over dashboards that have gotten slow or unreliable. We audit the architecture and rebuild only the parts that don’t hold up.
We interview your stakeholders and turn what they tell us into a list of decisions, roles, and KPI definitions. Every metric gets a named owner, and you approve the list before we build anything.
We audit your sources, data quality, and volumes. Then you get a documented design for the warehouse, refresh schedule, and security, plus a cost estimate.
Our engineers build ETL or streaming pipelines first. On top of them, they add an API that sends pre-aggregated, validated data to the dashboard.
Your end users click through prototypes with real data. We adjust layouts, filters, and drill-downs based on how they use them, and only then start development.
We check number accuracy, load performance, and access rules for every role at your real data volumes. AI-powered testing takes care of the repetitive checks.
We train your users at launch. After that, we monitor the pipelines and add new metrics or sources when you need them.
Patient flow, utilization, procurement prices, and medical affairs insights. We design these dashboards for HIPAA and GDPR, with role-based access and de-identified datasets for partners. Our healthcare analytics clients include AstraZeneca and an Austrian pharmaceutical procurement platform.
Revenue, margins, cash flow, and risk exposure in one view. We reconcile accounting, billing, and banking data and keep an audit trail behind every number. If you need live payment oversight, we also build transaction monitoring software.
Track consumption, generation, grid load, and billing across sites and meters. We pull data from smart meters and sensors and alert operators to anomalies, much like the energy monitoring software we build.
Device status, health, and maintenance views built from telemetry. For a Canadian R&D company, we built a cloud platform that monitors robotic devices, collects logs and errors, and runs remote reboots and installs. If you’re planning your own, start with our guide to building an IoT dashboard.
Fleet status, delivery times, and exceptions on one screen, with telematics, warehouse, and order data tied to shared KPIs. We’ve written about which metrics belong on a logistics dashboard and why.
Your team tracks MRR, churn, activation, and feature adoption, and your customers get embedded analytics from the same data model. For a US childcare operator, one BigQuery warehouse feeds CRM workflows, a loyalty marketplace, and churn scoring.
We’re ISO 27001:2022 certified, GDPR covered, and HIPAA-ready. Encryption, row-level security, and audit trails go into the architecture from the first sprint.
Data engineers, designers, and frontend developers work as one team. They decide metric logic, performance, and usability together, with no handoffs between vendors.
We use AI-assisted development to cut delivery time by up to 50% and bugs by up to 20%. A senior engineer still reviews the code before every release.
We keep 96% of our people. The engineers who define your KPIs will most likely still be around when you add your next data source.
You get a roadmap in 14 days, with a scoped architecture and cost estimate, before you commit to the full build.
98% of our clients are satisfied with our work. Most dashboard projects turn into a second phase with new teams, sources, or metrics.
Dashboard development services cover everything it takes to turn data from your systems into interactive views. Each view uses one set of KPI definitions and shows every role the metrics it acts on. A full project usually includes KPI discovery, data integration and pipelines, a metric layer, UX/UI design, front-end development, testing against source systems, and support after launch. If you already have a warehouse, most of the data work drops away. A customer-facing analytics product needs every layer, plus multi-tenant security.
The price depends mostly on the data work behind the screens. Five things drive it:
A single dashboard on clean data costs far less than a multi-tenant analytics layer for your customers. Within 14 days of our first call, we’ll send you a scoped, phased estimate. That way you can launch a first version and grow it later.
Anywhere from a few weeks for a first version to several months for a full data platform. The biggest factor is how ready your data is. A dashboard on an existing warehouse moves fastest, while new pipelines, closed systems, and strict compliance add time. For example, we delivered the first phase of an automated data pipeline for a US childcare operator in under two months, including an integration with a platform that had no public API. We release in phases, so your team works with real dashboards early.
Yes. Almost every dashboard project we take on connects to CRM, ERP, billing, marketing, or IoT systems. We link sources through official APIs, database replication, or file feeds, then normalize fields and remove duplicates so totals match. If a platform has no public API, we build a custom integration within the vendor’s terms of service. We did this for a closed childcare management platform, moving its data into BigQuery and a GoHighLevel CRM. Every load runs quality checks and sends an alert if something breaks.
Yes. We build embedded dashboards that live inside your product and follow your user model. Multi-tenant isolation and row-level security make sure each customer sees only its own data, and the interface matches your brand. Custom embedded dashboards also skip per-viewer BI licenses, which add up fast when thousands of customers need access. If you already use a BI tool, we’ll first check whether its embedding options fit your pricing and permissions.
We fix the data layer first and keep checking it. All KPI definitions live in one versioned metric layer, so every view calculates revenue or churn the same way. Our pipelines run validation rules, deduplication, and reconciliation against source systems, and they alert the team when a load fails or a value looks off. Before launch, QA compares every metric against the source systems. After launch, automated tests run with each change.
Yes, for operations where minutes matter, like transaction monitoring, device fleets, and live inventory. Streaming pipelines and WebSockets push updates to the screen as events come in. Plenty of business dashboards work just as well with refreshes every few minutes or hours, and they cost less to run. We agree on how fresh each metric needs to be during discovery. On one project, we replaced overnight ETL jobs with real-time analytics, and procurement teams got instant access to current prices and stock.
We build data protection into the architecture from the first sprint. Relevant Software is ISO 27001:2022 certified, and we design for GDPR and HIPAA whenever personal or health data is involved. Typical controls include:
AI features follow the same permissions, so nobody can query data they aren’t allowed to see.
Yes. We start by auditing the data sources, queries, and architecture, because the bottleneck usually sits in the data layer. Common fixes include moving analytics off production databases, precomputing heavy aggregates, adding caching, and putting metric logic into a shared API. When an Austrian healthtech platform’s dashboards froze during peak bidding windows, we audited the system, designed a new architecture, and added real-time analytics with natural-language queries. Tell us about your current setup through the contact form, and we’ll scope the audit.
Show us your current reports and data sources. We’ll tell you what one dashboard can replace and what it’ll cost.
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