Use Case | Public Tender Management with Segmentation and Semantic Searches

Use Case: Public Tender Management with Segmentation and Semantic Searches

General Description:

Public tender management involves analyzing multiple proposals that contain detailed information about costs, scope, and timelines. A model that segments, organizes, and uses vector databases for semantic searches allows for quick comparisons and specific searches for key information. This approach improves efficiency in evaluating proposals and transparency in selection processes, making it ideal for public organizations, consulting firms, and companies involved in tendering processes.

How It Works:

1. Upload of Proposals in PDF: Users upload proposals in PDF format, which may include details about costs, methodologies, timelines, and technical specifications.
2. Automatic Segmentation by Topics: The model automatically organizes proposals into key categories, such as:
   • Cost: Financial details, proposed budgets, anticipated adjustments.
   • Scope: Objectives, deliverables, and coverage of the proposal.
   • Timeline: Key dates, milestones, and delivery deadlines.
   • Methodology: Techniques and approaches outlined for the project.
3. Semantic Searches: Users perform specific queries such as:
   • “Proposals with the lowest cost and shortest timelines.”
   • “Which proposals include external audits as part of the scope?”
   • “Timelines that meet the project deadline.”
4. Generation of Comparative Summaries: The model generates summaries highlighting:
   • Key features of each proposal.
   • Differences in costs, timelines, and scope.
   • Recommendations based on evaluation criteria.
5. Storage in Vector Database: Segmented proposals are stored for future searches and audits.

Practical Example: Scenario: A government agency needs to evaluate 50 proposals for the construction of a new water treatment plant.

Process with the Model:

1. Upload of Proposals: The 50 proposals are uploaded to the system in PDF format.
2. Model Segmentation: The system organizes the information into:
   • Cost: Proposed budgets, financial breakdown, possible adjustments.
   • Scope: Specific objectives, applied technologies, coverage.
   • Timeline: Project duration, key milestones, partial deliveries.
3. Semantic Search: Evaluators query:
   • “Proposals with the lowest cost and timeline under 12 months.” The system responds with:
   • Proposal 1: Cost $1.2M, duration 10 months, includes full coverage.
   • Proposal 2: Cost $1.5M, duration 11 months, uses advanced technology.
4. Generation of Comparative Summaries: For each proposal, the system generates a summary that includes:
   • Proposal 1: Tight budget, standard technology, competitive timeline.
   • Proposal 2: Higher cost, but greater technological innovation.
5. Report Output: Evaluators receive a consolidated analysis that helps prioritize the most viable proposals according to established criteria.

Benefits of the Model in Public Tender Management:

1. Clear and Efficient Organization:
   • Automatically segments proposals into key categories, improving accessibility and analysis.
2. Contextual and Relevant Searches:
   • Allows information to be found based on meaning, providing precise results aligned with search criteria.
3. Quick Comparisons:
   • Highlights differences in costs, scope, and timelines for more efficient evaluation.
4. Report Generation:
   • Provides clear, concise summaries that facilitate data-driven decision-making.
5. Transparency and Easy Audits:
   • Stores segmented and organized proposals, facilitating future audits and reviews.

Additional Applications:

1. Tender Process Audits:
   • Verifies that decisions align with established selection criteria.
2. Evaluation of Associated Contracts:
   • Relates selected proposals to contract terms to ensure compliance.
3. Optimization of Internal Processes:
   • Improves proposal review efficiency through segmentation and fast searches.
4. Post-Project Management:
   • Facilitates tracking compliance with commitments made in winning proposals.
5. Multilingual Management:
   • Translates and organizes proposals in different languages for international tendering processes.

Practical Example: Additional Scenario: A consulting firm advises a local government in evaluating tenders for a road infrastructure project.

Without the model:

• The evaluation team spends weeks manually reviewing hundreds of pages, comparing costs, scope, and timelines.

With the model:

• The system automatically segments the proposals and generates a report that highlights:
  • Proposal 1: Lowest cost, standard technology, tight timeline.
  • Proposal 2: Moderate cost, innovative approach, extended timeline but with additional benefits.
  • Recommendation: Prioritize Proposal 2 for its balance between innovation and feasibility.

Conclusion: Automated public tender management through segmentation, semantic searches, and summary generation transforms a traditionally manual and complex process into an efficient, transparent, and data-driven task. This model is ideal for governments, public organizations, and companies involved in tendering processes, enabling quick and precise decisions while ensuring transparency and regulatory compliance.