Solution

Investment Landscape Analysis

Investment Landscape Analysis

Bringing Clarity to Private Market Opportunities
Bringing Clarity to Private Market Opportunities
Screenshot of computer simulation
Screenshot of computer simulation

From scattered data to a transparent market view — helping investors screen opportunities, compare companies, and uncover hidden growth potential with confidence.

Client(s)

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Sector

Financial Services

Challenge

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Decision lens

Investment Planning

Product

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Geography

Europe

The challenge

The challenge

For investment funds, identifying attractive opportunities in private markets is often slow and incomplete. Public data is scattered across sources, metrics are inconsistent, and analysts spend significant time building ad hoc spreadsheets that risk missing key signals.


For a mid-size fund in Belgium, the challenge was clear: how to systematically screen growing companies, compare performance, and identify opportunities - without relying solely on personal networks or fragmented market intelligence.

For investment funds, identifying attractive opportunities in private markets is often slow and incomplete. Public data is scattered across sources, metrics are inconsistent, and analysts spend significant time building ad hoc spreadsheets that risk missing key signals.


For a mid-size fund in Belgium, the challenge was clear: how to systematically screen growing companies, compare performance, and identify opportunities - without relying solely on personal networks or fragmented market intelligence.

Solution

Dashboard showing financial performance of TotalEnergies (Brussels, Belgium). • Top left: Scatter plot of Sales (mln EUR) vs EBITDA actual (mln EUR) for visible companies. TotalEnergies is highlighted in blue, with sales of ~7523.92 mln EUR and EBITDA actual ~31.52 mln EUR. • Top right: Company details: • Activities: Wholesale trade in solid, liquid, and gaseous fuels; manufacturing of refined petroleum products. • EBITDA actual: 31.52 mln EUR • EBIT actual: 15.23 mln EUR • EBITDA growth: -0.65 • Sales: 7523.92 mln EUR • Bottom: Line chart of EBITDA (mln EUR) over time (2005–2027). From 2005–2022, EBITDA fluctuated between 80–150 mln EUR, peaking in 2008 (~145 mln EUR). From 2023 onwards, sharp decline, with projections (shaded area) dropping to negative values by 2026.
Scatter plot titled “Visible companies with sales from 200k: 171830”. • X-axis: Sales (mln EUR), ranging from approx. -400 to 800. • Y-axis: EBITDA actual (mln EUR), ranging from approx. -46 to 155. • Each point represents a company, with many clustered between 0–400 mln EUR in sales and 0–60 mln EUR in EBITDA. • Data density is highest in the central region, where crosses (+) mark overlapping points. • A few outliers appear with higher EBITDA (above 100 mln EUR) and higher sales (~600–800 mln EUR).
Dashboard showing financial performance of TotalEnergies (Brussels, Belgium). • Top left: Scatter plot of Sales (mln EUR) vs EBITDA actual (mln EUR) for visible companies. TotalEnergies is highlighted in blue, with sales of ~7523.92 mln EUR and EBITDA actual ~31.52 mln EUR. • Top right: Company details: • Activities: Wholesale trade in solid, liquid, and gaseous fuels; manufacturing of refined petroleum products. • EBITDA actual: 31.52 mln EUR • EBIT actual: 15.23 mln EUR • EBITDA growth: -0.65 • Sales: 7523.92 mln EUR • Bottom: Line chart of EBITDA (mln EUR) over time (2005–2027). From 2005–2022, EBITDA fluctuated between 80–150 mln EUR, peaking in 2008 (~145 mln EUR). From 2023 onwards, sharp decline, with projections (shaded area) dropping to negative values by 2026.
Scatter plot titled “Visible companies with sales from 200k: 171830”. • X-axis: Sales (mln EUR), ranging from approx. -400 to 800. • Y-axis: EBITDA actual (mln EUR), ranging from approx. -46 to 155. • Each point represents a company, with many clustered between 0–400 mln EUR in sales and 0–60 mln EUR in EBITDA. • Data density is highest in the central region, where crosses (+) mark overlapping points. • A few outliers appear with higher EBITDA (above 100 mln EUR) and higher sales (~600–800 mln EUR).
Dashboard showing financial performance of TotalEnergies (Brussels, Belgium). • Top left: Scatter plot of Sales (mln EUR) vs EBITDA actual (mln EUR) for visible companies. TotalEnergies is highlighted in blue, with sales of ~7523.92 mln EUR and EBITDA actual ~31.52 mln EUR. • Top right: Company details: • Activities: Wholesale trade in solid, liquid, and gaseous fuels; manufacturing of refined petroleum products. • EBITDA actual: 31.52 mln EUR • EBIT actual: 15.23 mln EUR • EBITDA growth: -0.65 • Sales: 7523.92 mln EUR • Bottom: Line chart of EBITDA (mln EUR) over time (2005–2027). From 2005–2022, EBITDA fluctuated between 80–150 mln EUR, peaking in 2008 (~145 mln EUR). From 2023 onwards, sharp decline, with projections (shaded area) dropping to negative values by 2026.
Scatter plot titled “Visible companies with sales from 200k: 171830”. • X-axis: Sales (mln EUR), ranging from approx. -400 to 800. • Y-axis: EBITDA actual (mln EUR), ranging from approx. -46 to 155. • Each point represents a company, with many clustered between 0–400 mln EUR in sales and 0–60 mln EUR in EBITDA. • Data density is highest in the central region, where crosses (+) mark overlapping points. • A few outliers appear with higher EBITDA (above 100 mln EUR) and higher sales (~600–800 mln EUR).

We developed an AI-assisted tool that consolidates and structures the Belgian investment landscape.


The tool scrapes data from multiple public sources and financial institutions, integrates it into a single platform, and presents a full overview of the market - including key metrics, historical performance, and forecast ranges.


Users can:


  • Filter companies on metrics most relevant to their strategy.

  • Identify promising investment opportunities based on consistent, transparent data.

  • Use a nearest-match algorithm to surface companies with similar profiles, uncovering opportunities that might otherwise be overlooked.


By turning scattered data into a living market view, the tool gave the fund a scalable way to discover, compare, and shortlist investments.

Results

Faster opportunity identification

from manual, ad hoc searches to systematic market screening.

Deeper insight

transparent, comparable company metrics across the Belgian private market.

Smarter discovery

“nearest match” surfaced hidden opportunities with similar profiles to proven performers.

Results

Faster opportunity identification

from manual, ad hoc searches to systematic market screening.

Deeper insight

transparent, comparable company metrics across the Belgian private market.

Smarter discovery

“nearest match” surfaced hidden opportunities with similar profiles to proven performers.

Results

Faster opportunity identification

from manual, ad hoc searches to systematic market screening.

Deeper insight

transparent, comparable company metrics across the Belgian private market.

Smarter discovery

“nearest match” surfaced hidden opportunities with similar profiles to proven performers.

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