Custom BI Dashboards & Analytics Development
We build the data pipelines, predictive models, and custom dashboards that make deciding from current data routine instead of quarterly. Scoped from an operations audit, built in-house by our US team, and handed over as code you own.
From Data Pipelines to Decisions
Most reporting problems are pipeline and data-modeling problems, not dashboard problems. We build the integrations, the model layer, and the reporting on top of it for your systems, so the question in the Monday meeting can be 'what will happen next?' rather than 'what happened last month?'.
One platform answers different questions. Finance gets forecasting it can defend and a clear view of what drives cost. Operations gets anomaly detection on the metrics that matter day to day, fed by pipelines that update as work happens. People teams get attrition risk scoring and a factual picture of where skills are thin. Governance and access control are built into the pipeline rather than added afterward.
Data pipelines and integrations
API and database integrations into the CRM, ERP, finance, and operational systems you already run, with the cleaning rules and metric definitions written for your data rather than approximated in a generic connector.
Warehouse and data model
A warehouse or model layer that gives every metric one definition, so finance, operations, and sales stop arguing about whose number is right and reporting reflects the whole business instead of one department's view.
Custom dashboards
Reporting built around the decisions each team actually makes and opens each morning, not a generic BI canvas that somebody has to configure on the side.
Predictive models with monitoring
Demand and revenue forecasting, anomaly detection on operational metrics, retention and attrition risk scoring, and classification models that route work automatically. Every model ships with monitoring, so accuracy is tracked over time rather than assumed.
Governance and data quality
Access control and quality checks built into the pipeline rather than bolted on afterward, so a number on a dashboard can be traced back to the records it came from and is only visible to the people who should see it.
Handover and support
Documentation and training for your team, or an ongoing support arrangement with Nutron if you would rather we keep running it. Either way the pipelines, models, and dashboards are handed over as code you own.
How It Fits the Way We Work
Scoped from the audit
The two-week operations audit, from $1,500, finds where reporting is slow, manual, or not trusted before anything gets built. It can end with us recommending nothing be built.
Fixed quote before work starts
Custom builds start at $15,000, scoped from the audit findings, with the quote fixed before work starts. The scoping risk sits with us, not with you.
Built in-house, owned by you
A US-based team, nothing subcontracted or offshored. Pipelines, models, and dashboards are handed over as code you own, with the documentation to run them.
Analytics & Data Engineering FAQs
What gets built, how it connects to your systems, and who owns it afterward.
What does custom analytics software development involve?
It covers the full path from raw data to a decision: building the data pipelines that collect and clean your data, the warehouse or model layer that structures it, the machine learning models that predict from it, and the dashboards your team actually opens each morning. Nutron builds all four rather than handing over a generic BI license.
How is this different from buying a BI tool?
A BI tool gives you a canvas; it does not solve the hard part, which is getting trustworthy data into it. Most reporting problems are pipeline and data-modeling problems. Custom development means the integrations, data cleaning, and metric definitions are built for your systems rather than approximated in a generic connector.
Can you connect analytics to the systems we already run?
Yes. Nutron builds API and database integrations into existing CRM, ERP, finance, and operational systems, then unifies that data so reporting reflects the whole business instead of one department's view.
What kinds of predictive models do you build?
Common builds include demand and revenue forecasting, anomaly detection on operational metrics, retention and attrition risk scoring, and classification models that route work automatically. Models are deployed with monitoring so accuracy is tracked over time, not assumed.
Who maintains the analytics platform after launch?
Your team, with documentation and training from Nutron, or Nutron under an ongoing support arrangement. Either way the pipelines, models, and dashboards are handed over as code you own.
Start with the problem, not the pitch.
Tell us what is slowing you down and we will tell you whether the two-week operations audit is worth it for you, and what we would look at first.