Expertise You Can Rely On for SCM
Expert data science team delivering specialized solutions for inventory allocation, demand forecasting, item grouping, and recommendation systems to optimize your supply chain operations.
Automation of Inventory Allocation
Automate inventory allocation to improve operational efficiency and mitigate stock‑out/overstock risks.
Key capabilities
Demand‑forecast–driven automatic inventory distribution algorithm
Priority rules by sales channel and region
Business impact
Reduced delivery delays
Higher inventory turnover
Optimization for Item‑Receiving
Optimize inbound operations at distribution centers.
Key capabilities
Inbound scheduling and worker route optimization
AI‑based throughput forecasting for receiving
Business impact
Faster logistics processing
More efficient workforce allocation
Grouping Highly Related Items
Group items with strong affinity to strengthen merchandising and marketing strategies.
Key capabilities
Association rules and market‑basket analysis
Grouping by category, brand, and usage patterns
Business impact
Effective bundle sales and shelf optimization
Higher relevance in recommendations
Forecasting Daily Item Demand
Predict day‑level demand and feed production and purchase planning.
Key capabilities
Time‑series models (ARIMA, Prophet, LSTM)
Seasonality and promotion effects incorporated
Business impact
Prevent stock‑outs and reduce carrying cost
Lower production and purchasing cost
SCM Network Design
Design and optimize the end‑to‑end supply network.
Key capabilities
Optimal routing across suppliers, DCs, and customers
Cost, lead‑time, and service‑level trade‑off analysis
Business impact
Reduced logistics cost
Improved service quality
Building Recommendation System
Deliver personalized product recommendations to each customer.
Key capabilities
Collaborative, content‑based, and hybrid filtering
Real‑time personalization and serving
Business impact
Increased revenue per session
Higher customer satisfaction
Solution Implementation Flow
We follow a pragmatic, outcome‑driven approach from discovery to production and continuous improvement.
- Discovery & scoping: align objectives, constraints, and success metrics
- Data onboarding & readiness: connect sources, validate quality, define business rules
- Prototyping & validation: iterate models and rules with real data and A/B checks
- Rollout & enablement: deploy pipelines/APIs, dashboards, and train users
- Continuous improvement: monitor KPIs, handle drift, and optimize operations
Target Outcomes
- Reduced delivery delays and inbound bottlenecks
- Higher inventory turnover with policy‑driven allocation
- Improved forecast accuracy and promotion planning
- Optimized network cost, lead time, and service level
- Increased revenue via relevant recommendations and bundles
Frequently Asked Questions
Quick answers on data requirements, deployment, MLOps, and integration.
QWhat data do we need to start?
What data do we need to start?
Transactional sales/orders, inventory levels and movements, receiving/inbound logs, product master, and (optionally) promotion calendars. We align to your schema and security policies.
QHow long does implementation take?
How long does implementation take?
Varies by scope: 4–6 weeks for a single use case; multi‑use‑case programs typically 2–3 months including integration and dashboards.
QDo you support real‑time decisions and MLOps?
Do you support real‑time decisions and MLOps?
Yes. We deploy APIs/batch jobs, implement monitoring and alerting, and manage model retraining and rollout with CI/CD.
QHow do you handle privacy and security?
How do you handle privacy and security?
We follow least‑privilege access, encrypt data in transit/at rest, and align with your compliance requirements. We can deploy within your VPC if needed.