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AI platform for public tenders and funding calls (Wonderlab, Italy)

Bitvision

A platform that helps companies find, assess and bid for public tenders: automated screening against the company profile, an AI agent, auto-generated paperwork and market reports.

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  • AI agent
  • Document automation
  • Analytics
  • R&D project

Overview

Bitvision is a research and development project funded under the POR Campania FESR 2014–2020 programme and built by Wonderlab with DB Seret and Proto Design. Public procurement is huge and complex, and for small and medium businesses finding, screening and responding to tenders takes a lot of time and money. Bitvision is a digital platform that supports companies through searching, selecting and evaluating tenders and funding opportunities, and then preparing the paperwork to take part.

How it works

  1. 1Tenders published
  2. 2Automated screening
  3. 3AI agent matches profile
  4. 4Shortlist + alerts
  5. 5Auto-generated documents
  6. 6Reports & insights

What I built

Automated tender screening

Each company configures how tenders are screened against its own characteristics; analysis and classification algorithms filter and flag the most relevant opportunities.

Purpose-built AI agent

An AI agent compares tender requirements with the company's profile and highlights the opportunities that best match its capabilities and goals.

Automatic bid documentation

Generates the administrative forms and declarations needed to take part in a tender from company data already entered or extracted from digital documents.

Market reporting

Collects and analyses historical tenders and awards to produce reports and visualisations on how the procurement market behaves.

Real-time notifications

Alerts users as soon as new tenders relevant to their profile are published.

Simple workspace

One interface to browse tenders, manage the company profile, track shortlisted opportunities and use document generation and analytics.

Engineering decisions

  • Let each company define its own screening criteria rather than relying on generic keyword search.
  • Reuse company data across bids so repetitive forms are filled automatically and consistently.
  • Start with a research phase on tender data and dynamics before building the commercial product.

Stack

Capabilities
Tender analysis and classification, AI agent, automated document generation, reporting, notifications
Project
POR Campania FESR 2014–2020; Wonderlab with DB Seret and Proto Design; 2025 – ongoing

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