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ML based collaborative SaaS platform for the construction sector

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Overview

AI-powered platform fostering construction and infrastructure collaboration for enhanced synergy among stakeholders.

At A Glance

industry
Industry
Real Estate
region
Region
Gulf
duration
Duration
1 Year

Technical Stack

Angular
PostgreSQL
AWS SageMaker
OpenSearch
Django
Logstash

Client Profile

The client is a major SaaS provider in the gulf countries with more than a decade of experience in the construction & infrastructure industry.

Challenge

  1. In infrastructure development, a lot of aspects are required for a single project, like plumbing, wiring, elevators, electricals, furniture, and many more. Gathering all in one umbrella platform was a difficult job due to their diversity in job nature.
  2. No platform allowed users to manage the entire process from tracking potential projects to bidding for proposals - from the design and engineering phase, pre-qualification, contracts issuing, project management, operational reporting, and end-to-end document management, till the handover.
  3. The client required a platform that would identify early-stage projects and track their progress by capturing intelligence from multiple sources. 
  4. The client wanted to track the award and sales cycle along with managing the budgetary quotation throughout the contract stage.
Interface of the ML-based collaborative SaaS platform for construction, highlighting intuitive design and powerful data visualization features in use

Solution

  1. Seaflux created a platform that would bring all the infrastructure development stakeholders under one platform, where they would be able to interact on the upcoming/ongoing projects referring to their business, like plumbing, electricals, wiring, and more. 
  2. The platform allows users to analyze and research the huge data of upcoming and ongoing projects. Users can bid for the proposals and manage their documents for the same.
  3. The projects can be tracked for the award, sales cycle, and budgetary quotations throughout the contract stage. They can be tagged according to the user's preference, allowing customization on an individual level for reminders and notifications on proposal progress.
  4. The searching functionality within the huge amount of dataset has been accomplished using AWS Opensearch, which gets updated in real-time using Logstash.
  5. The platform also recommends the projects and does sales forecasting for the end users based on their working skills and location. SageMaker was used to train this ML model.
  6. The dashboard of the platform is given a custom feature to arrange, add, or remove the widgets. This results in a hyper-personalized dashboard for each individual according to their preference of usage.
  7. Seaflux created a Calendar view that allows the user to view Interactions, Reminders, Schedules, and Events based on Day, Week, and Month along with customized reminders. This also has a map view that allows the user to cluster their projects based on the locations and plan their meetings accordingly.
  8. On the search result grid, users have the ability to change the order and number of columns to show in the search results based on their needs with the help of the AG grid.

Key Benefits

  1. The platform received a 37% growth in its annual subscription and a 43% increase in new user registrations.
  2. Sales opportunities and pipeline management was simplified, and thus data management became much easier.
  3. The client was able to perform sales forecasting using automatic sales reports and use them for effective communication and collaboration.
     

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