Overview

Svevia, one of Sweden's largest road infrastructure operators, runs a high-volume, high-stakes tender process. Each public procurement required teams to comb through thousands of internal documents, prior bids, and requirement matrices — a time-consuming bottleneck that limited how many opportunities the business could pursue.

Challenge

• Public procurement responses required manual assembly of answers from thousands of historical documents
• Each tender locked up specialists for days, capping the volume of bids the company could pursue
• Knowledge from past bids was hard to find and reuse, leading to inconsistent quality across submissions
• Employees lacked a single point of access to internal policy and project documentation

Solution

We delivered an AI assistant that automated the tender response process end-to-end, paired with a chatbot trained on Svevia's internal document base.

• Built an AI-powered tender assistant that drafts responses by combining live requirements with past winning bids
• Trained the system on requirement matrices, prior procurements, and internal documentation
• Deployed a complementary chatbot for instant answers across thousands of internal documents
• Implemented retrieval-augmented generation (RAG) backed by a vector database for accurate, source-grounded responses
• Architected the platform on Azure for security, scalability, and seamless integration with existing workflows

Impact

• An estimated 80% reduction in time spent producing tender responses
• Significantly improved quality and consistency of submitted bids
• Freed specialists to focus on strategy and high-value review rather than document assembly
• Increased effective bid capacity without adding headcount
• Established a reusable AI foundation for further document-intensive workflows