For SCM, inventory, demand planning, and control-tower platforms: built on your warehouse.
Multi-tenant supply chain dashboards built into your SCM platform, visibility tool, or inventory SaaS. White-labeled with your brand, shipped in 2–4 weeks, without hiring extra data engineers.
We cut down on 6 months of work for our data analysts and saved around $300k by maintaining a smaller, more efficient team, avoiding the need to hire extra analysts just to handle ad-hoc reports.
Ajay
Chief Technology Officer, Spendflo
Case studyWe now offer our customers extensive insights out of the box, sparing them the pain of creating their own metrics, all while ensuring they have a seamless experience.
Jaskaran .B
Product Manager, SpotDraft
Case studyDatabrain allowed us to create a fully custom analytics module. Anybody in the org was now able to create metrics and share data with their tool.
Swami
Chief Product Officer, Freightify
Case studySwitching to Databrain streamlined everything with better customizations, predictable pricing and AI features that let our mortgage brokers get insights through natural language.
Evan
Co-founder, EpochOS
Case study
.webp)
SCM and supply chain product teams consistently underestimate the multi-tenant security and compliance overhead on top of the engineering cost. Here's what the three paths actually look like, based on real in-house builds.
Connect your warehouse, define your metrics, and embed dashboards into your SCM product. Click a step or let it play through.
Connect your data
One read-only SQL connection to your warehouse. Your SAP, Oracle, WMS, and TMS data stays put.
Define your supply chain metrics
Define OTIF, inventory turnover, or any KPI with Visual Builder, Custom SQL, or AI Chat Mode against your own schema.
Embed into your SCM product
Drop in one embed snippet. Multi-tenant RBAC, white-label theming, and SOC 2 ship standard.
Most SCM and supply chain SaaS teams hit the same walls when adding analytics: data isolation, white-labeling, schema-specific metrics, and AI queries. DataBrain solves each one out of the box.
Row-level RBAC enforced at the query layer delivers true multi-tenant analytics. One DataBrain instance powers thousands of tenants. Every manufacturer, supplier, planner, and 3PL operator sees only their data. No custom RBAC code, no per-customer database forking.
Custom theming, your domain, your logo, your fonts and colors, down to the chart palette. Full white-label data visualization. End users never see DataBrain.
Define any supply chain KPI your customers care about (OTIF, inventory turnover, forecast accuracy, landed cost, days of supply, or fill rate) using Visual Builder, Custom SQL, or AI Chat Mode. Real-time, not nightly. Your schema, your metrics.
Natural-language query layer. Supply chain planners and ops leads type a question and get a dashboard. AI Copilot surfaces inventory exceptions, ranks supplier performance, and flags demand anomalies. Grounded in your warehouse data, not a generic model.
Define your metrics, embed the dashboards, multi-tenant isolation out of the box.
Days of supply, stockout rate, turnover, and on-hand levels by SKU, warehouse, and category — surfaced natively inside the platform your customers already log into. Each manufacturer sees their own stock, no one else's.
Forecast accuracy, bias, MAPE, and demand variability by SKU and region, embedded in the demand planning platform your supply chain planners use daily. Compare forecast vs. actuals, surface the worst-performing SKUs, and give each customer their own view.
OTIF rate, lead-time variability, quality score, and fill rate, scoped per supplier, embedded inside the procurement or SCM platform your ops teams use. Each supplier sees only their delivery data. Each customer sees only their supplier base.
Perfect order rate, fill rate, order cycle time, and backorder status from PO creation to delivery, embedded in the order management or WMS platform your customers rely on. Per-customer data isolation enforced at the query layer.
Shipment exceptions, OTIF breaches, lead-time spikes, and inventory coverage gaps, surfaced in real time inside the control-tower or visibility platform your customers use. Per-customer exception feeds, per-carrier scoping, and risk flags enforced at the query layer.
We cut down on 6 months of work for our data analysts and saved around $300k.
We now offer our customers extensive insights out of the box, sparing them pain.
Databrain allowed us to create a fully custom analytics module.
Switching to Databrain streamlined everything with better customizations and predictable pricing.
Your supply chain data already lives in your warehouse. DataBrain sits on top of it: no new ETL, no data copies, no rebuilding your data flow.
SAP, Oracle SCM, Blue Yonder, Manhattan WMS, and other supply chain sources feed your warehouse through the ETL or ELT pipelines you already run, like Fivetran, dbt, or Airbyte.
Your supply chain data already lives here. DataBrain connects to Snowflake, BigQuery, Redshift, Databricks, or Postgres in read-only mode, with no data copy and nothing leaving your warehouse.
Define any supply chain metric (OTIF, inventory turnover, forecast accuracy, landed cost / SKU, days of supply, fill rate) in Visual Builder, SQL, or AI Chat Mode, then embed via iframe, web component, or SDK. Multi-tenant RBAC runs at the query layer: every manufacturer, supplier, and planner sees only their data.
Customer-facing, white-label dashboards native to your SCM, inventory, demand-planning, or control-tower product — each tenant scoped to their own data automatically.
DataBrain does not replace your ETL or duplicate your warehouse. We sit on top of it, so your source of truth stays your source of truth. Don’t see your WMS, ERP, or SCM source? Talk to us about a custom connector →
Supply chain analytics is the practice of collecting, modeling, and visualizing data across procurement, inventory, demand planning, fulfillment, and logistics to measure performance and improve decisions. For embedded SaaS products, it means shipping analytics directly inside an SCM, inventory, or control-tower platform so end customers (suppliers, planners, ops leads) can see their own data without leaving the product.
Embedded supply chain analytics software renders customer-facing dashboards natively inside an SCM or logistics SaaS product with multi-tenant data isolation, so each customer sees only their own inventory, orders, and supplier data. DataBrain is purpose-built for this pattern: multi-tenant by default, white-label from day one, connected directly to the warehouse data your customers already generate.
The most tracked supply chain KPIs include OTIF (on-time in-full), inventory turnover, demand forecast accuracy, fill rate, perfect order rate, days of supply, supplier on-time delivery, lead-time variability, stockout rate, landed cost per SKU, and purchase price variance. With DataBrain, your team defines any of these against your own warehouse schema using Visual Builder, Custom SQL, or AI Chat Mode. No pre-built model required. Every KPI is specific to your data model and your customers.
DataBrain connects directly to your data warehouse via a read-only SQL connection: Snowflake, BigQuery, Redshift, and Databricks are all supported. Your SAP, Oracle SCM, Blue Yonder, Manhattan WMS, or TMS data lands in your warehouse first via your existing ETL or data pipeline, then DataBrain reads from it. There is no middleware, no ETL managed by DataBrain, and no data leaves your infrastructure.
Most SCM and supply chain SaaS teams ship their first live, customer-facing dashboard in two to four weeks. DataBrain connects to your warehouse in minutes over a read-only SQL connection. Your team then defines supply chain metrics using Visual Builder or Custom SQL, assembles dashboards in one to three days, and embedding takes a single script tag. There is no new data hire required.
The typical in-house embedded supply chain analytics build costs $150K to $340K in engineering in year one and takes 6 to 12 months to reach a production-grade surface. You need roughly 1.5 senior engineers covering data engineering, front-end, and multi-tenant security, plus ongoing maintenance, SOC 2 controls, and audit logging on top. DataBrain’s Growth plan starts at $999/month with multi-tenancy, unlimited seats, unlimited embeds, and one data source. See pricing.
Power BI and Tableau are standalone tools your internal team logs into separately. DataBrain renders dashboards inside your own product under your brand, with per-customer data isolation so each supplier, planner, or operator sees only their slice of data. Power BI embedding also carries per-tenant licensing costs that scale poorly at SaaS scale, which is why embedded-analytics teams replace it with DataBrain and go live in weeks, not months.
Yes. That is the foundation of DataBrain’s architecture. Row-level RBAC is enforced at the query layer, not in application code. A manufacturer sees their production orders only. A supplier sees their delivery performance only. A 3PL client sees their warehouse only. You configure the tenant model once and DataBrain enforces it on every query automatically, across thousands of tenants from a single DataBrain instance.
Yes. DataBrain reads live from your warehouse on query, so dashboards reflect the latest data your pipeline delivers. If your warehouse receives near-real-time events from an ERP, WMS, or IoT feed, your customers see that freshness directly in their embedded dashboards. No separate caching or refresh scheduling required beyond your warehouse’s own cadence.
Control-tower and visibility platforms use DataBrain to surface multi-tenant analytics dashboards for each of their customers, showing shipment exceptions, OTIF by lane, carrier scorecards, and risk flags, all scoped to each customer’s data. DataBrain’s multi-tenant RBAC means one DataBrain instance serves all your customers without forking databases or writing custom isolation code for each new customer you onboard.
