Streamlining Tender Selection with AI-Driven Scoring
The Issue:
Monitoring and evaluating tenders across multiple platforms is time-consuming and prone to human error. Identifying opportunities that align with a company’s strengths can be challenging, leading to missed prospects or wasted effort on unsuitable tenders.
Our Solution:
We implemented an AI-driven workflow that aggregates tenders from various sources and evaluates them against predefined criteria. The system assigns a relevance score to each tender, enabling the team to prioritise reviews and focus on the most promising opportunities.
The Tech:
Utilising natural language processing (NLP) and machine learning algorithms, our system analyses tender documents to assess alignment with company capabilities. The AI model is trained on historical data to improve accuracy over time, ensuring that the scoring reflects the company’s evolving strengths and strategic goals.
