Success Story

From Paper to Power: Fuel Expansion with AI

Transformed complex station acquisition from a manual barrier into an intelligent, scalable system using AI-driven document analysis.

Vega

Operational Results at a Glance

10x
Monthly contract load capacity per employee
4x
Faster identification of contractual anomalies
100%
Verifiability of data sources

The ultimate goal was never just to build a document analysis tool. It was to build a growth engine. That's exactly what we've got. We achieved a system where users can instantly verify the source of data, turning skepticism into the confidence of having a new superpower.

Luigi MarzoratiIT Manager, Vega Carburanti
Scenario

A Complex Mandate for Market Leadership

Vega Carburanti operates a high-performance network with a turnover exceeding €700 million and over 120 stations across Northern Italy. The operational model is distinct: their stations dispense six times the national average value.

The vision is clear: rapid, strategic expansion. However, this growth strategy relies on the continuous acquisition of new stations and networks.

We are operators of service stations. Our speciality is efficiency. But imagine my general manager calls tomorrow and says 'we are acquiring 200 stations'—doubling our size. Personnel, IT tools, the whole company must be adequate.

The Challenge

A Race Against Complexity

The challenge was not finding assets, but integrating them. Each acquisition involved inheriting a mountain of unstructured documentation: leases, staff agreements, land purchases, construction permits, and technical blueprints.

Acquiring all the contracts and being able to extract accurate data quickly is fundamental to fast growth. Currently, it requires manually sifting through thousands of pages.

The Problem

  • Manual Data Entry

    Teams manually analyzed thousands of pages to extract critical data points (e.g., tank measurements, permit status).

  • Unstructured Fragmentation

    Information was locked in PDFs, Word files, Excel sheets, and scanned paper, often distributed across different formats.

  • Strategic Risk

    The inability to quickly answer complex questions—such as 'Which new stations have permits for EV chargers?'—threatened the speed of the growth strategy.

  • Scalability Bottlenecks

    The manual evaluation process was slow, prone to error, and could not scale to meet the target of doubling the network size.

The Solution

Intelligent Asset Platform: Intelligence Activating Knowledge

The project was built through co-creation. Working closely with Vega's legal, technical, and business development teams, the solution was designed to address specific domain needs rather than applying a generic tool.

We approached this not as a development project, but as a co-creation initiative. AI isn't an add-on; it's the core of the system.

Results

Efficiency, Control, and Strategic Transformation

From Passive Archive to Active System

The document archive has evolved from a storage problem into a source of untapped intelligence. Information that was previously locked in static files is now immediately accessible.

Simplification and Trust via Verification

The 'fact-checking' feature turned skepticism into adoption. By allowing users to click and instantly verify the source of data, the system bridged the gap between automation and human responsibility.

This is what users appreciate most: with one click, it opens the document and takes them to the paragraph from which the data point was taken.

Governance and Scalability

The platform acts as a strategic catalyst. By automating the ingestion and analysis phase, Vega transformed a manual barrier into an automated pipeline.

Tech Stack & Implementation

GenAIData ExtractionCloud ArchitectureOperations

Key Takeaways for Your Organization

1

Unlock Data Value

View document archives not as storage, but as a source of queryable intelligence that can drive decision-making.

2

Target High-Stakes Goals

Apply AI to solve critical, high-pressure bottlenecks. Fixing the acquisition pipeline created immediate, measurable value.

3

Build Trust as a Core Feature

Lasting solutions are built on confidence. Verifiability and 'fact-checking' capabilities are non-negotiable for user adoption.

4

Invest in Human-AI Dialogue

Technology is only half the equation. Training users on how to structure queries is essential to retrieving reliable results.

Ready to transform your document workflows?

See how KLens can help your organization achieve similar results.