Overview
The Sirma AI team is a cross-functional group of machine learning engineers, data scientists, LLM specialists, NLP researchers, data engineers, and solution architects with deep domain knowledge and hands-on experience delivering end-to-end AI solutions across industries. They brought extensive expertise in developing adaptive AI algorithms and implementing them in real-world commercial environments to optimize complex pricing and bidding decisions.
Our AI expertise received high praise from a leading US commercial building company, for which Sirma developed an innovative AI system designed to enhance the evaluation of construction bids. The solution analyses approximately 10,000 historical bids, both accepted and rejected, to extract insights that enhance pricing strategies. This initiative addresses the critical need to improve bid pricing accuracy in a highly competitive construction market. This showcased the effectiveness of continuous learning models and customized technology solutions.
The Challenge
The commercial building company faced challenges in consistently evaluating bid submissions for competitiveness and profitability. Traditional static models and manual evaluation processes were insufficient for handling the volume and complexity of financial bid data. The company needed a dynamic and adaptive AI-driven tool that could classify and assess bids, determining whether they were overpriced or underpriced, to ensure better decision-making while continuously learning from new bidding data.
The Project Scope
Sirma was tasked with designing and implementing a machine learning (ML) system capable of: • Ingesting and analysing large volumes of quantitative financial bid data; • Classifying bid submissions in real time as over- or under-priced; • Providing continuous improvement through self-learning capabilities rather than static model deployment; • Integrating seamlessly with the client’s existing bid management workflow to enhance pricing strategy decisions.
The Solution
Sirma developed a custom ML solution utilising a self-learning model that evolves with new data inputs, allowing the client to remain adaptable to market changes. Unlike traditional static classification models, this AI solution continuously refines its predictive accuracy, improving bid evaluation outcomes over time. The system is tailored specifically for classification tasks centred on complex quantitative financial data, leveraging proprietary algorithms from Sirma’s ML library designed under human expert guidance. Real-time data ingestion feeds the model, empowering the client with timely, data-driven insights for strategic bidding.
Results
Sirma integrated the machine learning system into the client’s workflows by embedding the AI bid evaluation tool seamlessly within the existing bid management processes. As we delivered the solution, the implementation has brought significant benefits to the construction company:
- Real-time bid evaluation allowed immediate identification of mispriced bids, reducing potential losses and opportunities missed due to inaccurate pricing;
- The continuous learning model ensured that the system improved autonomously as it processed more bid data, enhancing pricing precision over time;
- The client achieved a competitive edge with an adaptive AI-driven bidding strategy, differentiating them in the construction industry;
- Overall bidding efficiency and profitability improved, directly impacting the company’s bottom line.
This approach created a technology ecosystem where AI augmented human decision-making, streamlined bid pricing processes, and continuously adapted to market changes without requiring drastic workflow changes. The seamless integration helped the client realize measurable improvements in bid competitiveness and pricing accuracy while maintaining operational efficiency and control.
Technologies
- Custom proprietary ML library developed by Sirma’s internal AI experts;
- Advanced classification algorithms focusing on financial quantitative data analysis;
- Real-time data ingestion pipelines for continuous learning and model updates;
- Integration tools to embed AI evaluation seamlessly into existing bid management systems;
- Robust computational infrastructure to support scalable ML model training and inference.
Sirma’s Partnership with the client
This practical approach significantly impacts the crucial process of optimising bid pricing. It has created a technology ecosystem where AI supports human decision-making, enhances bid pricing, and adapts to market changes with minimal disruption to the workflow. This integration enables clients to enhance the competitiveness of their bids, improve pricing accuracy, and maintain operational efficiency.
