AI-Driven Insights & Solutions to Modernize Logistics Operations

CHALLENGES IN MODERN LOGISTICS & WAREHOUSING

Navigating routes as well as data inconsistencies

Demand volatility

Customer behavior is unpredictable; And, there are seasonality and trends, which challenge them to maintain ideal inventory levels, while catering to unforeseen demands.

Real-time data integration

Need to go eco-friendly

Cost management

Inaccurate forecasting

End-to-end logistics analytics solutions

Optimize everything - batch, fleet & logistics operations

Warehouse slotting

Maintain your warehouse slots like well-organized wardrobes. Receive real-time slotting & re-slotting instructions on what to keep, where, and how much for optimized storage and efficient labor movement. An optimized placement suggestion for your warehouse goods, based on order frequency, storage requirements, and other product constraints.

We can help you design AI-based slotting models that suit your picking policies, handle any capacity or product ranges, and cater to special storage requirements. This solution could reduce labor movement up to 15%, creating a direct impact on worker productivity and pick and pack speed.

CUSTOMER SPOTLIGHT

Success stories from businesses like you

Optimizing the picking process using an AI-based slotting engine

15%

Reduction in physical labor

Identifying a near-optimal way to slot SKUs in a warehouse to minimize the picking process and labor movement and thereby costs.

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Enhancing business intelligence for a logistics company

10x

Fast database performance & data availability

15%

High employee efficiency & productivity

Enabling near real-time data analysis, automating the ETL process with audit and error tracking, and providing a detailed dashboard.

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Tire distributors roll out data-driven operations with data warehousing

30%

Faster access to data

Centralizing and visualizing transactional data using Snowflake and Power BI

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FAQS

Got questions? We got you covered.

What is logistics planning in AI?

Logistics planning in AI is used to make the packing, storage, and fleet management processes better with the help of AI-driven inferences. Example: Optimizing delivery routes for fast delivery and cost savings. Or stocking inventory based on future demands - few logistics use cases where AI can help.

How to use AI in supply chain?

AI in supply chain is used to bring real-time visibility into shipments, enable smart fleet management, and make other process optimization. This helps logistics companies save time and money, while reaching destinations faster.

What is route optimization in logistics?

Route optimization in logistics with AI can be done to create better itineraries for fleet operators - helping them find the best routes between two destinations that’s fuel-efficient, facilitates fast movement, and allows multiple delivery to happen concurrently.

CLIENT VOICES

Take our customers word for it

They were flexible and adaptive to the client's changing requirements. The team executed a smooth workflow to ensure the project's success. Their flexibility and adaptiveness were notable in the partnership.

Bhargav Raghavendra

Senior IT Director, Cyient

The team at datakulture are inspiring to work with. Their drive for excellence and the values they share from the top down are impressive. The result is top quality work and a partner you are proud to work with.

Liran Lahav

COO, Q Report

I just wanted to say a big thank you for all the support you've given us. Your expertise in Data and Analytics is really helping us make better data-driven decisions. The way you're assisting us with MS Fabric is fantastic, and we're excited about gradually migrating to it to boost collaboration across our organization.

Fisayo Oduyemi

IT Business Analyst, Saluda Medical

We were really impressed with their service orientation and understanding of our business. Showcasing expertise in data engineering, datakulture was successful in implementing the dashboard, allowing the client to track their KPIs and make data-driven decisions. The team's solid understanding of the client's business and their needs was critical to the project's success.