Investor deck - 2026

Marple Data Analytics

Marple is the AI-ready data platform for hardware engineering teams.

Investor Deck
Antwerp, Belgiummarpledata.com
The Problem01 / 10
95% of data is never used
High-performance hardware teams capture enormous datasets, but current tools make them too slow to search, analyze and reuse.
01

Hardware has outgrown the software stack

More sensors, higher frequencies and distributed test benches create massive time-series datasets.

02

Current tools cannot manage the volume

Files, scripts and legacy databases break down when engineers need fast access to everything.

03

Insights still come from tedious manual work

Engineers spend hours searching, plotting and checking instead of acting on the result.

Engineering data is breaking old tooling
The Platform02 / 10

Store every signal. Turn it into engineer-ready insight.

Data sources
Vehiclestrack, dyno and road tests
Aircraftflight, ground and rig data
Machinessensors, PLCs and test benches
Data foundation

Store and unify every signal.

High-frequency data becomes reusable engineering data.

Fast ingestion
Unified namespace
Engineer workspace

Analyze, automate and surface AI insights.

Engineers get answers without rebuilding the workflow.

Interactive analysis
AI-assisted insights
Find anomaliesmoments that matter
Compare testswhat changed and why
Share contextone source of truth
Prepare AItrusted data layer
Measure - store - connect - analyse
The AI Layer03 / 10

Engineering AI needs engineering data.

Marple turns trusted test data into a context layer for automated analysis, KPI generation and anomaly detection.
Test data
Requirements
Engineer prompts
generate KPI: braking stability
link to requirement REQ-42
flag anomalies across test runs
Marple
Engineering
Insights
AI insightsSummaries directly on high-frequency data
Prompt KPIsMetrics and calculations from natural language
Requirement traceDocuments linked to tests and evidence
Auto workspacesProjects, calculations and visualisations set up by LLMs
Anomaly radarOutliers surfaced before engineers go hunting
Marple is where engineering AI becomes real: a powerful data lake with the context to turn raw test data into action.
From visualisation to autonomous analysis
Customer Proof04 / 10
EUR 0.5-1M
cost saving
Vehicle testing data analysis time reduced after Marple adoption.
Bugatti Tourbillon

Bugatti-Rimac

Performance technical lead - customer case
  • EUR 0.5-1M annual cost saving in current workflows.
  • Marple makes complex test data available, searchable and actionable for engineering teams.
  • The AI layer turns a proven ROI case into a larger automation opportunity.
Measured value before the AI upside
Business Model05 / 10

Yearly licences scale with customer usage.

Marple contracts grow with the customer data footprint and the intensity of analysis across Marple DB and Marple Insight.
Data storageAnnual licence expands with the amount of engineering data stored.
Ingestion volumePricing reflects how much new high-frequency data flows into Marple DB.
Query volumeMarple DB scales with the number and intensity of searches and retrievals.
Insight usageMarple Insight grows with active analysis, automation and AI-assisted workflows.
Deal Value
Typical contracts land around EUR 50k, with enterprise deployments expanding materially.
EUR 50k
Small customerEUR 25k Average customerEUR 50k Large customerEUR 250k
Year two expansion
+50%
Customers typically grow their deal size by around 50% in the second year.
Traction06 / 10

Worldwide presence across high-performance engineering.

EUR 0.5MARR
+180%year-on-year ARR growth
300+engineers using Marple daily
Marple customers across automotive, aerospace and advanced engineering
Automotive - aerospace - advanced engineering
Market Timing07 / 10
US competitors are raising serious capital, validating the size and urgency of the market.
Europe needs its own leader
SiftLegacy tooling replacement
$42M
NominalHardware teams AI-ready
$200M
Revel.ioR&D software
$150M
Aerospace - automotive - manufacturing
Growth Target08 / 10
EUR 0.5M
ARR today
Raising EUR 2M to scale Marple toward EUR 4M ARR in 2028.
EUR 0.5M2026
Scale-up2027
EUR 4M2028 target
Less detail now, more in diligence
Team09 / 10
Matthias Baert

Matthias Baert

Co-founder
F1 background, aerospace engineer

Nero Vanbiervliet

Nero Vanbiervliet

Co-founder
Software expert, cybersecurity background

A technical founding team built from deep engineering and software experience.
We understand both sides of the problem: the realities of hardware engineering and the software systems needed to make data useful.
Built from inside the problem

Engineering data is becoming the next AI platform.

Marple is building the European data layer for teams developing high-performance hardware.

Round
EUR 2M
2028 target
EUR 4M ARR
Next step
Let's talk
Investor deck