Intelligent Prescriptive Pricing and Tender Collaboration

Using Google’s Cloud AI, the solution assesses business contexts, price impacts, and customer scenarios to suggest ideal shipping contract bids.

Client Profile

A fintech firm based in the United States, specializing in providing a cloud-hosted customer success platform for companies in the logistics sector. Their unique solution simplifies the RFP (Request for Proposal) procedure, reduces delays, and nurtures widespread customer relationships in the logistics industry.


Generative AI

Project Overview

Using Google’s Cloud AI, this advanced pricing tool simplifies bid responses and freight pricing for third-party logistics companies. It acts as a shared platform, helping decision-makers assess bids and make informed choices using detailed analytical data. User-friendly dashboards enable tracking of past patterns and future projections in the logistics industry.

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Business Challenges

The client faced challenges in understanding variables impacting pricing and needed a sophisticated system to forecast suitable prices aligned with business objectives. Streamlining the existing RFP and pricing workflow was imperative

  • Challenges emerged in promptly establishing prices for specific shipping routes and evaluating bids for shipping contracts.
  • Dealing with vast quantities of data from internal and external sources proved to be a time-intensive process.
  • Their success rate in winning bids was notably lower.


This cloud-hosted solution guarantees consistent lane and pricing standards while automating eligibility checks. It incorporates predictive pricing, using dynamic scenarios to anticipate outcomes accurately.
The solution comprises three modules:

  • Processing of shipper files
  • Advisory services for pricing
  • Gathering and analysis of market intelligence

Users can upload the shipper’s RFP and customize various aspects like tender ID, dates, origin, destination, mode of transport, and services. The pricing advisory and market intelligence modules collaborate to simplify the pricing workflow by using AI/ML capabilities to confirm prices against global benchmarks, improving the entire pricing process.

  • The APIs are built using NodeJS. The user interface (UI) is stored in Amazon S3 and delivered through Cloudflare.
  • Small, independent services are packaged into Docker containers and managed via Kubernetes on AWS EKS.
  • Event-triggered tasks are managed through AWS services like SQS, SNS, Lambda, and RabbitMQ, the latter being hosted on dedicated EC2 instances from CloudAMQP.


Google AI
RDS Postgres
ReactJS, Node.js
React Native
Python Pandas
Naive Bayes – Probability classifier
TF-IDF based on mono, bi, and trigrams
Visualization – Histogram

Positive Outcomes for Business

  • Substantial rise of 43% in successfully securing bids.
  • Quoting becomes 95% speedier by implementing consistent pricing for all bids.
  • Precise pricing predictions guarantee timely and accurate market insights.
  • Customized stakeholder criteria seamlessly automate the allocation of lanes.

Key Features

  • Live display of latest bid amount and Request for Proposal (RFP) status, consolidating pricing and fluctuating elements for thorough evaluation.
  • Charts illustrating past rates and influential elements affecting pricing to aid analysts in assessing rates and profits swiftly.
  • Automated suggestions for pricing using market insights, client specifics, and established business strategies to enhance the chances of winning RFPs and maximizing profitability.
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