05 / Services

Models and software for decisions that cannot stay vague.

I help research, biotechnology, and manufacturing teams turn complex processes into transparent models, decision tools, and laboratory software.

The starting point is always the decision: what needs to become clearer before you commit to a process, facility, workflow, or investment?

Discuss your project See relevant work
01Process-wide scopeFrom unit operation to facility
02Inspectable assumptionsTransparent, testable, traceable
03Decision-led outputBuilt around the choice ahead
What I build

Three ways to make a complex system usable.

01
Industrial systems

Industrial process and facility modeling

Connect unit operations into one quantitative view of how material, energy, equipment, utilities, time, and economics interact across the process.

Explore the plant-wide model
  • Mass and energy balances
  • Equipment and utility requirements
  • Scheduling, throughput, and bottlenecks
  • Scenario, sensitivity, and uncertainty analysis
  • Interfaces for TEA and LCA
02
Scale-up decisions

Bioprocess scale-up and decision support

Translate biology, transport, equipment, and operating strategy into models that expose trade-offs before they become expensive at the next scale.

Explore the bioreactor workflow
  • Bioreactor strategy and operating modes
  • Batch, fed-batch, and perfusion comparisons
  • Scale-dependent constraints and bottlenecks
  • Mechanistic and data-supported models
  • Decision dashboards and digital-twin foundations
03
Custom tools · From €5,000

Laboratory software built around your workflow

Replace disconnected steps and generic interfaces with a focused browser-based tool shaped around your experiments, data, instruments, and decisions.

Open Lane Studio
  • Experiment planning and guided workflows
  • Structured data capture and validation
  • Dashboards, calculations, and visualizations
  • Models, simulators, and decision tools
  • Instrument and data-system integrations
When it helps

Bring structure to the point where the process becomes uncertain.

01

Before scale-up

When a promising laboratory process needs a credible route toward pilot or industrial operation.

02

Before a facility decision

When equipment, utilities, timing, throughput, and cost must be evaluated as one connected system.

03

When assumptions are scattered

When evidence lives across papers, spreadsheets, expert knowledge, and incomplete datasets.

04

When the workflow no longer fits

When generic software or manual steps obscure data quality, slow the team, or make decisions harder to reproduce.

How the work moves

Decision → model → test → usable system.

  1. 01Frame the decision

    Define the choice, uncertainty, boundaries, and evidence that matter.

  2. 02Build the transparent core

    Connect equations, assumptions, data, and process logic in an inspectable model.

  3. 03Test what changes

    Compare scenarios, sensitivities, constraints, and consequences.

  4. 04Deliver something reusable

    Turn the analysis into a clear model, interface, workflow, or decision tool.

Selected workSee process models and tools Peer-reviewed researchInspect the scientific foundation Open sourceExplore the implementation
Common questions

A clear starting point.

What types of processes can you model?

I focus on industrial and bioprocess systems where unit operations, equipment, utilities, time, economics, and uncertainty interact. The model can cover one critical decision or connect an entire facility.

Can a project begin with incomplete data?

Yes. A useful first model makes missing data explicit, separates evidence from assumptions, and shows which uncertainty is important enough to resolve next.

What can custom laboratory software include?

Typical components include guided experiment workflows, structured data capture, calculations, dashboards, visualizations, models, simulators, exports, and integrations with existing data or instruments.

What should I send to start a conversation?

Share what you are building, the decision that is currently blocked, the scale you are working at, and any data, diagrams, spreadsheets, or assumptions already available.

Start with the decision

What needs to become clearer before you scale?

Describe the process, the uncertainty, and the decision ahead. I’ll help turn that question into a model or tool your team can use.

Discuss your project