Scattered Data Leads to Slow Decisions
Manual processes and disconnected systems create a cycle of outdated reporting that puts your profitability and competitive edge at risk.
You need dozens of integrations across Shopify, Amazon, NetSuite, ad platforms, 3PLs, and payroll, all of which break and require constant maintenance. Iris' connectors are natively built, pre-configured for CPG data models, and maintained by our team so you never touch a broken pipeline again.
Manual Data Pipelines
Most brands spend months and tens of thousands of dollars building custom ETL pipelines just to get data into a usable format. Iris normalizes, transforms, and aggregates raw data from every source into a clean CPG-specific schema automatically, saving you months of engineering hours and eliminating data cleaning entirely.
Analytics Native Storage
Traditional warehouses like Snowflake and BigQuery store your data but leave the analysis to you. Iris' warehouse is AI-native from the ground up, with a DuckDB implementation that loads billions of records sub-second and a pre-built CPG data model that powers forecasting, margin tracking, and reporting out of the box.
The Complete Data Infrastructure Platform
Manual processes and disconnected systems create a cycle of outdated reporting that puts your profitability and competitive edge at risk.
Auto-Generated ML Forecasts
Iris generates machine learning forecasts using features specific to your business — seasonality, channel mix, promotional calendars, and inventory cycles. No data science team needed. Models update continuously as new sales and operations data flows into your warehouse.
Stop relying on static spreadsheet projections. Iris' ML models learn from your actual performance data and adapt to your brand's unique pattern.
Out-of-the-box ML forecasting for CPG brands
Models trained on your specific business data
Continuous learning that improves over time
Auto Normalization
Every data source you connect to Iris is automatically cleaned, normalized, and mapped to a CPG-specific schema. No manual data prep, no broken CSV imports, no waiting on data engineers to fix things. Shopify orders, Amazon settlements, and NetSuite journals all land in one unified queryable format.
Your team can start building reports the moment data lands in Iris, not weeks later after cleanup and transformation.
Pre-cleaned data for all supported connectors
Unified schema across Shopify, Amazon, and ERP
Zero manual data preparation or mapping
No-Code Configurations
Create custom metrics, views, and reports without writing a single line of code. Iris lets your finance and ops teams query and manipulate warehouse data directly - no SQL, no engineering tickets, no two-week waits for a report change.
Define your own margin formulas, adjust channel groupings, or build a custom P&L view in minutes using natural language or drag-and-drop tools. Your data, your way, on your timeline.
No-code metric and report configuration
Natural language data queries with Fin AI agent
Custom views without engineering dependencies
Performance
Iris' DuckDB-powered warehouse loads billions of records sub-second. Your dashboards, reports, and AI agents stay fast, even while querying years of transaction data across every SKU and channel. No timeouts, no slow queries, no compromise on data depth.
Traditional cloud warehouses charge by compute and penalize heavy queries. Iris delivers the same power at a fraction of the cost with no usage-based billing surprise.
Sub-second queries across billions of records
DuckDB-powered analytical processing engine
No usage-based compute costs or query limits
Replace your Fivetran-to-Snowflake stack with one tool. Iris ingests your Shopify, Amazon, and ad data into a CPG schema so your team gets clean financial data instantly. No pipelines to build or maintain.
Omnichannel Retail Brands
Consolidate DTC, wholesale, and retail financials into one warehouse without hiring a data engineer. Iris maps revenue, deductions, and inventory across every channel so your P&L reflects reality in real time.
Scaling Brands
Stop duct-taping spreadsheets, QuickBooks exports, and agency reports together. Iris gives growing brands an enterprise-grade data warehouse from day one so your team can make confident data-backed decisions.
"I’m obsessed with Iris Finance . In a matter of a week, it went from "I'll try it out" to "How did I ever live without this?" Iris has become an essential tool in the stack at Allermi, giving me a crystal-clear, real-time read on our entire financial picture."
CEO, Allermi
"Iris' data warehousing capabilities allow us to input all of our financial data to get a clear picture of our Company's financial health in real-time. It is also great that we can export this data, as their platform consolidates several items."
CMO, LivFresh
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How does Iris' DuckDB warehouse compare to Snowflake or BigQuery?
Iris' DuckDB implementation delivers sub-second query performance across billions of records, comparable to enterprise cloud warehouses, but without usage-based compute pricing. You won't pay more when your team runs complex queries or when data volume grows. For CPG brands, this means warehouse-grade analytical power without the unpredictable costs that come with traditional cloud data platforms.
How long does it take to set up Iris' data warehouse?
Most brands are fully set up within 30 minutes. Iris' pre-configured connectors and CPG-specific data schema mean you can connect Shopify, Amazon, your accounting system, and other data sources and start querying clean, normalized data the same day — no data engineering, no implementation consultants, and no multi-month onboarding process.
What data sources does Iris integrate with?
Iris connects to ecommerce platforms (Shopify, Amazon), accounting systems (QuickBooks, NetSuite), payroll providers, 3PL and fulfillment systems, and advertising platforms (Google Ads, Meta, TikTok). All connectors are natively built and maintained by Iris, so there are no third-party middleware tools to manage. Visit our integrations page for the full list of supported connectors.
Do I need a data engineer to use Iris?
No. Iris is designed so that finance and operations teams can connect data sources, build custom reports, create new metrics, and query the warehouse without writing SQL or submitting engineering tickets. Iris' AI agent Fin also supports natural language queries, so you can ask questions about your data in plain English.
Is my financial data secure in Iris' warehouse?
Yes. Iris is built with enterprise-grade security from the ground up, including encryption at rest and in transit, role-based access controls, and compliance with industry-standard data privacy requirements. Your financial data is never shared across customers, and Iris' architecture ensures that sensitive information from platforms like Shopify, Amazon, and your accounting system is handled with the same level of care required by institutional finance teams and private equity portfolio operators. You can review our full security and data handling practices on our privacy policy page.
