Use Insight Maker to create rich pictures and causal loop diagrams.
Then make shareable simulation models. All right in your browser,
for free. Just sign up for a free
account and start modeling now.
Create an Insight Maker account to start building
models.
Insight Maker is completely free.
Start Now
Insight Maker runs in your web-browser. No downloads or plugins are
needed. Start converting your ideas into your rich pictures,
simulation models and Insights now. Features
Simulate
Explore powerful simulation algorithms for System Dynamics and Agent
Based Modeling. Use System Dynamics to gain insights into your
system and Agent Based Modeling to dig into the details. Types of Modeling
Collaborate
Sharing models has never been this easy. Send a link, embed in a
blog, or collaborate with others. It couldn't be simpler. More
Free & Open
Build your models for free. Share them with others for free. Harness
the power of Insight Maker for free. Open code mean security and
transparency. More
Explore What Others Are Building
Here is a sample of public Insights made by Insight Maker users. This list is auto-generated and updated daily.
Example from book "Complex System Research in Psychology" by Han van der Maas (https://santafeinstitute.github.io/ComplexPsych/)
Extremely basic stock-flow diagram of compound interest with table and graph output in interest and savings development per year. Initial deposit, interest rate, yearly deposit and withdrawal can all be modified in Dutch.
Stock-Flow diagram of savings account - compound interest
The limits to growth structure is based on the basic growth structure. And, as should be obvious, nothing grows forever as growth requires resources. Those required resources become a limits to growth. See also Archetypes.
This model simulates the tradeoff between AI costs in resources and the benefits of increased efficiency and effectiveness over time, using adaptive learning principles. It demonstrates how AI development evolves through different stages early, growth, and mature -with changing rates of investment, efficiency gains, and resource utilization.
The model tracks how AI systems stabilize over time as efficiency gains become harder to achieve, leading to a more mature and balanced system of investment and performance. It aims to provide insights into real-world AI dynamics, showing how resources translate into efficiency improvements and how diminishing returns, learning saturation, and reinforcement learning affect long-term growth.