Dredge Analytics™: Making Dredging Smarter with AI
Dredge Analytics™, a San Francisco-based startup, has become the first platform to use AI to help improve sea transport foundation. It uses a combination of Digital Twin technology and AI to give instant, smart advice to people in the dredging industry. Dredge Analytics’ journey began when they figured out two main challenges in the industry; Dredging companies compete for projects by bidding in government auctions, where they have to estimate project costs manually to present their bids. One of the big challenges was that these cost estimates were made by someone in the company manually, and the other challenge was that there was nowhere to easily store all the data and paperwork involved in the work process. So dredging companies needed a platform that gathers live data from dredging projects, looks at it together with past data, and uses AI to find ways to make dredging work better, faster, and more cost-effective.
Services
- Custom Software Development
- Web Development
- Team Building Consultancy
- Digital Strategy Consultancy
- AI Development
- Custom Software Development
- Web Development
- Team Building Consultancy
- Digital Strategy Consultancy
- AI Development
Client
Period
Project Overview
Dredge Analytics™ wanted to lead the digital revolution in the dredging industry. They planned to create a platform that uses AI to make managing and improving sea projects much easier. Their idea was to use this platform to look carefully at new and old project data, giving companies useful tips to help them work more smoothly. By bringing in new technology to an industry that usually did things manually, Dredge Analytics™ aimed to make operations more efficient, save money, and base decisions on solid data.
Challenges
Doing a Feasibility Study Without a CTO
Without a Chief Technology Officer (CTO) on board full-time, their startup struggled to carry out feasibility studies and build early versions of the product to present to potential clients. This role would have helped them understand if their ideas were technically possible and how they could turn them into real, working solutions.
Building Software and a Team from Scratch
In the beginning phases of their startup, setting up the basic software needed for the project (Minimum Viable Product, or MVP) and putting together a development team were big challenges. Starting from zero meant they had to figure out both the technical foundation of the product and build a team capable of bringing it to life.
Creating an AI Model for Smarter Operations
Dredge Analytics needed to develop an artificial intelligence (AI) model that could analyze data and provide recommendations to improve production rates while reducing costs. The challenge was to create a smart system that could take in information and suggest ways to make operations more efficient and cost-effective.
01
MVP Definition, Development, and Launch
We started with a basic yet appealing version of the platform (an MVP) that could read, transform, and visualize past data in a way that’s useful for top managers at dredging companies to make important decisions. This strategy worked well, attracting attention and helpful feedback from industry leaders.
02
Expert Guidance Like a CTO
We designed the system to grow easily, using Spring Boot and Java for the main technical parts to make sure it’s strong and flexible. For the website front, we used Angular because it’s great for creating dynamic sites and easy to keep up. For mobile apps, we chose React Native, which let us use the same code for both Android and iOS, making things quicker and more efficient. So we took on all the tasks a CTO would have handled for them.
03
Full Support for Building a Tech Team
With our help in developing the MVP and launching it, we took on the big job of putting together a software development team and setting everything up. Later, we helped the client hire developers, get them working together, and eventually move to having their own tech team, with us still giving advice when needed.