AI based Predictive Analytics for Logistics

Business challenges

Inaccurate data: Logistics companies may struggle with inaccurate or incomplete data, making it difficult to predict delivery assurance accurately.

Human error: The manual processes involved in ensuring delivery assurance can be prone to human error, leading to incorrect predictions and missed deliveries.

Scalability: As a company's business grows, the volume of data and the number of deliveries can become overwhelming, making it difficult to ensure accurate delivery assurance predictions.

Time constraints: Logistics companies are under pressure to make quick decisions and ensure on-time delivery, which can be challenging without accurate and up-to-date information.

Competition: Logistics companies face intense competition, and ensuring delivery assurance is critical to staying ahead in the market and meeting customer demands.

Cost: The manual processes involved in ensuring delivery assurance can be time-consuming and expensive, leading to increased costs for logistics companies.

Solution Overview

Optisol teamed up with a well-known logistics company to develop a solution using AI-based predictive analytics to predict delivery assurances of products.

The solution helps ensure on-time delivery and eliminates the need for manual intervention tasks.

A machine learning model was built to predict delivery assurance based on historical data.

Feature extraction and selection was performed using geospatial data.

A large volume of data was collected from various sources to improve the accuracy of the predictive model.

Business Impact

Increased accuracy: AI-based predictive analytics can improve the accuracy of delivery assurance predictions, leading to more efficient and effective processes.

Improved customer satisfaction: Ensuring delivery assurance can improve customer satisfaction, leading to increased customer loyalty and positive word-of-mouth.

Increased efficiency: Automating the process of delivery assurance predictions can reduce manual errors and increase efficiency, leading to cost savings and improved operations.

Improved competitiveness: Ensuring delivery assurance can help logistics companies stay ahead in a competitive market, providing a competitive advantage and attracting new customers.

Improved scalability: AI-based predictive analytics can handle large volumes of data, making it easier for logistics companies to scale their operations and meet growing customer demands.

Compliance: Automating delivery assurance predictions can help logistics companies comply with industry standards and regulations, reducing the risk of legal or financial penalties.

Technology Stack

Impact

Speeds up the delivery process.

Reduces human intervention tasks

Trusted and Proven Engagement Model

Our engagement model defines the project size, project development plan, duration, concept, POC etc.
Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).

The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
This helps clarify the goals, and limitations, and deliver quality products & services.

A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
Our NDA-driven process is established to keep clients’ data and IP safe and secure.

The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.

On signing the SOW, an official project kick-off meeting shall be initiated.
Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.

Our Award-Winning Team

A seasoned AI & ML team of young, dynamic and curious minds recognized with global awards for making significant impact on making human lives better

Awarded Bronze Trophy at CII National competition on Digitization, Robotics & Automation (DRA) – Industry 4.0

5yrs

in AI & ML
Engineering

40+

AI & ML
Projects for
reputed Clients

50+

AI & ML
Engineers

Awarded as Winner among 1000 contestants at TechSHack Hackathon

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