From Data to Autonomous Replenishment in 30 Days
A structured 4-step process to implement AI demand planning. No ERP replacement. No expensive consultants. No operational disruption.
Data Ingestion
We connect all your data systems into a single platform. ERPs, sales channels, 3PLs, WMS, and data warehouses are integrated via secure APIs. Our team performs a complete data quality audit to identify missing records, duplicates, and anomalies.
System Connection
API integration with ERPs (SAP, NetSuite, QuickBooks), sales channels (Shopify, Amazon, WooCommerce), 3PLs (ShipBob, ShipStation), and data warehouses (Snowflake, BigQuery).
Data Audit
Exhaustive analysis of data quality, completeness, and consistency. We identify gaps in sales history, SKU errors, and discrepancies between systems.
API Validation
End-to-end testing of each integration. We verify that data flows correctly, syncs are real-time, and data pipelines are robust.
Ontology Mapping
We transform your raw data into a structured semantic model. Each SKU is linked to its suppliers, lead times, warehouse locations, MOQ constraints, and substitution relationships. We build a complete graph of your supply chain.
Semantic Model
Raw data from multiple sources is structured into a unified model with clear relationships between entities: products, suppliers, locations, channels, and customers.
SKU Linking
Each SKU is connected to its suppliers with specific lead times, MOQs, negotiated prices, and storage locations. Variants and substitutes are linked automatically.
Supply Chain Graph
A complete graph is built mapping the flow of products from suppliers to end customers, including intermediate nodes like warehouses, distribution centers, and stores.
Model Calibration
AI models analyze 24 months of historical sales data to identify seasonal patterns, trends, and anomalies at the SKU level. Safety stock parameters, demand forecasts, and replenishment rules are calibrated. Each forecast is validated against actual sales to ensure accuracy before go-live.
Historical Analysis
Machine learning analyzes 24 months of sales history. Identifies seasonal cycles, promotion impact, growth trends, and anomalies like supply chain disruptions or atypical events.
Replenishment Parameters
Safety stock levels, reorder points, optimal order quantities, and replenishment timing are automatically calibrated for each SKU based on actual demand variability and lead times.
Validation Against Actual Sales
Model forecasts are compared against actual historical sales using backtesting. Accuracy, bias, and error are measured to ensure models meet quality standards before activating them in production.
Go-Live
The first automated purchase orders and transfers are generated based on calibrated forecasts. Your operations team receives comprehensive training on the platform. By day 30, your team has full autonomy over the AI demand planning system.
Automated Orders
First automated purchase orders and warehouse transfers are generated. The system respects MOQs, lead times, supplier constraints, and configured replenishment policies.
Team Training
Live training sessions for your operations, purchasing, and supply chain team. Includes comprehensive documentation, training videos, and access to priority support.
Full Autonomy
By day 30, your team operates the platform independently. Forecasts are generated automatically, purchase orders are created without manual intervention, and alerts notify about exceptions that need attention.
What Happens After Go-Live
Soberan is not a set-it-and-forget-it implementation. It is a system that continuously learns and improves.
Continuous Learning
AI models incorporate every new sale, every lead time change, and every demand variation. The system becomes smarter with each transaction, adapting to market changes without manual intervention.
Daily Recalibration
Every day, forecasts are recalibrated with fresh sales data. Safety stock parameters and reorder points are automatically adjusted based on updated trends and real market conditions.
Improving Accuracy
Forecast accuracy improves with each data cycle. Customers see 40% improvements over previous methods in the first 90 days, with continuous incremental improvements thereafter. Monthly performance reports measure progress.
Integrations
Soberan connects with 50+ systems via API. It integrates on top of your existing stack without replacing anything.
Sales Channels
Shopify, Amazon, WooCommerce, BigCommerce, Mercado Libre, B2B
ERPs
SAP, NetSuite, QuickBooks, Odoo, Microsoft Dynamics
3PLs & WMS
ShipBob, ShipStation, Flexport, Deliverr, Custom WMS
Data Warehouses
Snowflake, BigQuery, Redshift, PostgreSQL, Custom APIs
Implementation FAQ
How long does the full implementation take?
Soberan's full implementation takes 30 days, divided into 4 phases: data ingestion (days 1-7), ontology mapping (days 8-15), AI model calibration (days 16-23), and go-live with team training (days 24-30). No ERP replacement or external consultants required.
What data do I need to have ready before starting?
Ideally, you need 24 months of sales history, a SKU catalog with supplier information and lead times, and access to your current systems (ERP, sales channels, WMS). If you don't have 24 months, we can work with a minimum of 12 months. Our team performs a data audit in the first week to identify and resolve any gaps.
Do I need to replace my current ERP?
No. Soberan integrates on top of your existing ERP without replacing it. We connect via API with SAP, NetSuite, QuickBooks, Odoo, and other ERPs. Soberan acts as an intelligence layer that reads data from your ERP and writes purchase orders and transfers back.
What happens if my historical data is not clean?
The data ingestion phase (days 1-7) includes a complete data quality audit. We identify missing records, duplicates, anomalies, and inconsistencies. Our team works with yours to clean and normalize data before the AI begins analyzing it. Imperfect data is not a blocker to getting started.
How much training does my team need?
During the go-live phase (days 24-30), we provide comprehensive training for your operations team. The platform is designed to be intuitive: most teams are autonomous after 2-3 training sessions. We also provide documentation, training videos, and ongoing post-implementation support.
What happens after go-live?
After go-live, Soberan continues learning and improving automatically. AI models recalibrate daily with new sales data. Forecast accuracy improves with each cycle. Your team receives automatic alerts about anomalies, demand changes, and replenishment recommendations. We include ongoing support and periodic performance reviews.
Ready to Implement in 30 Days?
From fragmented data to autonomous replenishment. No ERP replacement. No expensive consultants.
Request a Demo