Your business systems already hold the answers: ERP, CRM, ecommerce, and marketing platforms generating data every minute. Maayins builds the analytics capability on top of them, from dashboards and reporting to a modern data stack with machine learning and AI, matched to where your organization is on the analytics journey.
Business analytics is a progression. Each stage builds on the one before it, moving your organization from looking backward to acting forward. We meet you at your current stage and build the next one.
What happened?
The foundation: dashboards, reports, and KPIs that summarize what is going on across revenue, margin, inventory, pipeline, and cash. Most organizations live here, and most live here badly, with numbers scattered across exports and conflicting spreadsheets. We make this layer accurate, automated, and trusted first.
Why did it happen?
Drill-down, variance, and root cause analysis. Why did margin drop in March? Which channel, customer, or item drove it? We build the data relationships and analysis tools that turn "the number moved" into "here is exactly why."
What will happen?
Statistical models and machine learning trained on your history: demand forecasting for purchasing, payment behavior scoring for collections, churn risk for customer teams, and anomaly detection that flags problems before close.
What should we do?
The top of the pyramid: recommendations and triggered actions. Suggested reorder quantities, prioritized collection lists, dynamic pricing inputs, and alerts wired into the systems where your team already works, so insight becomes action without a meeting in between.
You cannot skip stages. Predictive models built on an untrusted descriptive layer just predict garbage faster. We sequence the work so each stage pays for the next.
Forward-looking shortage analysis comparing forecast, on-hand, on-order, and committed quantities per item and location, months before the problem hits a customer order.
Weekly cash flow forecasting built from live receivables, payables, payment history, and terms, so treasury decisions stop being guesses.
Profitability analysis joined across ERP, CRM, and ecommerce data, the cross-system question no single platform answers alone.
Variance and trend diagnostics that surface what changed and where, instead of leaving your team to eyeball two columns of numbers.
Forecasting models trained on your sales history, seasonality, and pipeline, feeding purchasing and production decisions.
Anomaly detection on transactions and balances that flags outliers worth investigating before they become month-end surprises.
Real analytics runs on real architecture. We design and build the modern data stack layer by layer, using proven tools and only the layers your stage of the journey requires.
Your systems of record: NetSuite, Salesforce, HubSpot, Shopify, banking platforms, and the rest of your operational stack. We know these schemas deeply, which is where most generic data consultancies fall down.
Automated extraction and loading using managed connectors like Fivetran and Airbyte where they fit, and custom Python pipelines where they do not. Scheduled batch for history, near-real-time where the business case justifies it, all monitored with retries and alerting.
A governed central store on Snowflake, BigQuery, Databricks, or Azure, sized for a mid-market budget. Full history beyond your ERP's practical retention, raw and modeled zones, and elastic compute you pay for only when querying.
Raw data becomes clean, documented, analytics-ready models using dbt: version controlled, tested, and traceable, so your data logic is engineering, not tribal knowledge in someone's SQL folder.
One agreed definition for every metric: revenue, margin, DSO, inventory turns, defined once and reused everywhere, ending the meeting where finance and sales argue about whose number is right.
Power BI, Tableau, or Looker dashboards for analysts and leadership, spreadsheets for finance and operations via NetXcel, scheduled delivery for stakeholders, and APIs feeding models and applications.
Already have pieces of this? We work with what exists and fill the gaps, not rip and replace.
Role-based dashboards in your BI tool or directly in your business systems, with KPI definitions agreed across departments so every number has one owner and one formula.
We do not start from a blank page. Our library includes battle-tested reports like the Item Shortage Report, Weekly Cash Flow Forecast, Inventory Roll Forward Suite with summary, location, category, and detail views, and Working Capital Metrics, tailored to your data in days, not months.
SuiteQL, SOQL, and SQL development that joins any record type and applies complex business logic, wherever standard reports run out of road.
Pipelines, warehouse builds, dbt transformation projects, and migrations, delivered with the same engineering discipline as our commercial software: versioned, tested, documented.
Python-based forecasting, segmentation, scoring, and anomaly detection models, scoped around a specific decision with measurable value, deployed into production rather than left in a notebook.
For teams that live in Excel and Google Sheets, NetXcel, a Maayins product, delivers live, refreshable data and one-click dashboards from your business systems, no exports, no stale numbers.
The next stage of business analytics is conversational. Using Model Context Protocol (MCP) and modern AI assistants, we connect AI directly and securely to your ERP, CRM, and data warehouse, so your team can ask questions in plain English and get answers grounded in live, governed data.
"What were our top ten customers by margin last quarter?" "Which open POs are at risk this week?" Questions answered conversationally from live data, with the AI working through your existing roles and permissions.
AI that helps your finance team investigate variances, trace unusual balances, and draft analysis during month-end close, compressing hours of digging into minutes of review.
Instead of waiting for someone to run a report, AI monitors your data and surfaces what matters: a customer trending toward late payment, an item trending toward stockout, a margin quietly eroding.
We architect AI access the right way: MCP connections that respect your platforms' roles and permissions, a clean modeled data layer for the AI to stand on, no copies of your data in someone else's model, and an audit trail of what was asked and answered.
AI readiness is the new test of a data stack. If your data is too inconsistent to feed a model, that is the first problem we fix.
Not every question needs a warehouse, and not every team needs another license. The ladder we walk with every client:
Saved searches, standard reports, and built-in dashboards in your ERP and CRM. Free and fast. We make sure this layer is exhausted before you pay for anything else.
SuiteQL, SOQL, and SQL development for questions that cross record types or need complex logic, still inside the platforms you already own.
When finance and operations live in spreadsheets, NetXcel brings live, refreshable data to them without a single export.
When you need long history, cross-system analytics, machine learning, or Power BI at scale, we build the data platform.
Most companies are paying for step four problems while their step one is broken. We start by fixing the step you are on.
Bring us the question your team keeps struggling to answer. In a 30-minute session, a Maayins engineer will show you exactly how we would answer it, and which layer of the stack it belongs in.
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