LCP
Overview

An AI-powered platform where Requests for Proposals are streamlined and automated so that agencies can submit their proposals. It reads and summarizes the RFPs.

At A Glance

industry
Industry
Marketing & Advertising
region
Region
USA
duration
Duration
4 Weeks

Technical Stack

docker
AWS VPC
AWS EC2
AWS S3
AWS Lambda
GitHub Actions
Node.js
ReactJS
Amazon Bedrock

Client Profile

The client is a US-based Saas provider offering a platform for handling the RFPs for the clients.  

Challenge

  1. The client is facing issues with their CI/CD architecture and automation.
    The client relied on a manual process for building, testing, and deploying applications, leading to frequent human errors, delays, and inconsistencies between environments. The client wanted automation in their architecture using the CI/CD pipeline.
  2. The client had a monolithic application, which became tightly coupled and too large with all the accumulating data, making it difficult to scale. The client wanted to rearchitect their infrastructure for better scalability, a small release cycle, and lower costs.
  3. The client had the issue of keeping track of the different versions or even sometimes deploying the wrong code to the production. The client wanted a pipeline that triggers according to the required code to be deployed and keeps track of them.
  4. The client wanted an AI automation wherein the document uploaded by the organization would be read and summarized by the platform and posted which would help agencies to decide where to bid.
AI-Powered Platform to Streamline RFPs For Agencies

Solution

  1. Seaflux improved the platform and set up a CI/CD pipeline with a Label tag. This automates the process of building, testing, and deploying applications and the label tags streamline version management, deployment, and tracking in the pipeline. The label-based pipeline triggers specific workflows based on the labels added to code branches (e.g., feature/, bugfix/, hotfix/). For example, pushing a tag like v1.0-release can trigger the deployment to production, while v1.0-beta deploys to a staging environment.
  2. The infrastructure was restructured into a microservice and dockerized from the monolithic architecture. The microservices were dockerized to ensure consistency across development, staging, and production environments.
  3. Seaflux set up the MongoDB Atlas from the older MongoDB, as it automates critical tasks like scaling, backups, and security, saving you time and reducing operational complexity. High availability, global distribution, and seamless integration with cloud services make it an optimum solution for modern applications.
  4. Seaflux implemented a fully automated CI/CD pipeline using Jenkins and GitHub Actions and implemented parallel job executions, automated testing, and environment consistency through containerization (Docker).
  5. We also implemented AWS Bedrock to read the text from the RFP documents uploaded by the organization and provide a short summary on the landing page of the particular RFP.

Key Benefits

  1. The development and deployment time has improved significantly, about 29% faster time to market.
  2. Microservices helped in the individual scaling of services, reducing the infrastructure cost. CI/CD pipelines automated the repetitive tasks further reducing the operational cost. This resulted in a total cost reduction of 27%, increasing the bottom line.
  3. Implementing the AWS Bedrock increased the number of bids on the RFPs by approximately 7%.

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