CrowdSynthetic is live · free · last verified 8 Nov 2026 · viability monitor
CrowdSynthetic
Free MIT-licensed Python crowd simulation that turns a layout.json venue into a live density heatmap, zone risk scores and evacuation logic.
Got a specific question like "does moving this exit or capping this zone change the crush pattern?" CrowdSynthetic answers it for the price of a Python environment and one JSON edit. Expect to be running heatmaps and per-run CSVs within minutes. Keep expectations calibrated though: one contributor, six commits, no forks; nobody should present its output as a safety decision.
Verdict generatedVerified 5d ago · liveness 58/100 · cite: rightaichoice.com/tools/crowdsynthetic
- Event organizers running a free first-pass evacuation and exit-placement concept test
- Safety managers prototyping zone caps and exit layouts before commissioning a study
- Researchers and students exploring pedestrian dynamics with readable Python source
- Python developers who want a small MIT-licensed crowd simulation base to extend
- Live event crowd management or any safety-critical decision-making
- Real-time monitoring tied to cameras, turnstiles or sensors; there is no live ingestion
- Non-technical stakeholders who need a polished GUI or 3D visualization
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Skip CrowdSynthetic if you need live sensor or camera input feeding a real-time evacuation decision, or if you need validated, supported modelling for an actual event safety plan rather than a free Python proof of concept.
There is no pricing at all — CrowdSynthetic is MIT-licensed source published at $0, with no tiers, seats or usage metering. That puts it below every commercial pedestrian-dynamics suite on cost, and what you pay instead is time: setting up a Python 3.9+ environment, OpenCV dependencies and a layout.json by hand. Budget for a data-modelling suite when you need vendor-supported fidelity, validation and support.
In short
CrowdSynthetic — Free MIT-licensed Python crowd simulation that turns a layout.json venue into a live density heatmap, zone risk scores and evacuation logic. Best for Event organizers running a free first-pass evacuation and exit-placement concept test, Safety managers prototyping zone caps and exit layouts before commissioning a study, Researchers and students exploring pedestrian dynamics with readable Python source. Free to use.
What is CrowdSynthetic?
CrowdSynthetic — Free MIT-licensed Python crowd simulation that turns a layout.json venue into a live density heatmap, zone risk scores and evacuation logic. Best for Event organizers running a free first-pass evacuation and exit-placement concept test, Safety managers prototyping zone caps and exit layouts before commissioning a study, Researchers and students exploring pedestrian dynamics with readable Python source. Free to use.
CrowdSynthetic is a proof-of-concept Python crowd simulation for concert-style venues. You describe the space once in layout.json, zones, stage position and exits, then watch simulated agents move through it while per-zone risk builds and the run flips from NORMAL into EVACUATION when the threshold is crossed. Event organizers, safety managers, researchers and students get a zero-cost way to test whether moving an exit or capping a zone actually changes congestion. Runs open a real-time OpenCV window with custom avatars drawn over a crowd density heatmap and UI indicators for the current mode. Trend logic prints short predictions like "FRONT in X seconds" and "FRONT saturated", while recommendation text is generated from that run's own data. When evacuation completes, the final frame holds until you press a key so you can read the outcome. Setup is plain: pip install -r requirements.txt, then python -m src.main on Python 3.9+. The repo is a modularized src/ package restructured from the original single-script POC, and the README says it preserves layout-driven geometry, capacity-based risk, prediction, heatmap, EVAC and logging behavior. Every run writes concert_risk_log.csv and concert_risk_log.json, so numbers stay quotable after the window closes. Against commercial pedestrian-dynamics suites, CrowdSynthetic trades fidelity, support and scale for being free, readable and hackable. The repo shows 1 star, 0 forks and 6 commits, so treat it as a teaching and prototyping instrument rather than production safety software.
Key features
- Define venue geometry in layout.json: zones, stage position and exits
- Simulate agents moving through the venue while crowd risk builds
- Capacity-based risk scoring per zone
- Automatic NORMAL to EVACUATION mode switching on risk threshold
- Trend prediction output such as "FRONT in X seconds" and "FRONT saturated"
- Recommendation text generated from the simulated run's own data
- Real-time OpenCV rendering window with custom avatar drawing
- Heatmap overlay visualizing crowd density
- EVAC completion freeze-frame held until keypress
- Metrics logged to concert_risk_log.csv for spreadsheet analysis
- Metrics logged to concert_risk_log.json for programmatic analysis
- Modularized Python source package under src/
- Runs on Python 3.9+ via pip install -r requirements.txt and python -m src.main
- Keyboard control (Q quits the simulation)
- MIT licensed, forkable and extendable
Behind the verdict
Pick CrowdSynthetic when you want to poke at pedestrian dynamics by editing a JSON file rather than learning a simulation suite. Changing an exit position and re-running takes seconds, and because results land in concert_risk_log.csv and .json, you can diff two layouts side by side without screenshots. It's also a decent teaching aid. The src/ package is small enough for a class or a junior developer to read end to end, and the heatmap plus avatar overlay makes abstract density numbers visible in a way a spreadsheet doesn't. Where it bites is scope. This is a proof-of-concept for concert-style layouts, not a general pedestrian model, and the README's own framing makes that clear. There's no camera or turnstile ingestion, no 3D view, and nothing resembling a vendor behind it if something breaks. Non-technical stakeholders will bounce off the terminal and the OpenCV window. Anyone expecting a polished UI or saveable scenario editor should look elsewhere. Versus commercial pedestrian-dynamics tools, you're giving up calibrated behaviour models, support contracts and multi-venue scale in exchange for free, readable source. That trade is fine for a first-pass concept test and wrong for anything that informs a real evacuation plan. One practical caveat: the README flags an OpenCV install error (cv2.error) as the common failure, so budget time for dependency wrangling on fresh machines. And with zero forks, you are the maintainer of any fork you make.
Limitations
- CrowdSynthetic is a proof-of-concept Python demo, run locally with Python 3.9+ (pip install -r requirements.txt, then python -m src.main) rather than a hosted or cloud service.
- The simulation operates on a venue defined by a layout.json file and generates recommendation text from simulated run data, not from live event data.
- The public repository is small (MIT-licensed, roughly 1 star and 0 forks according to the page) and offers no vendor support channel.
- Outputs are logged locally to CSV/JSON files, and the project should not be relied on for real event-safety decisions.
as of 2026-10-09
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Is CrowdSynthetic still active?
CrowdSynthetic is live · free · last verified 8 Nov 2026 · viability monitor.
Viability score
How well maintained and how widely used is CrowdSynthetic? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: November 2026
How we score →What do users say about CrowdSynthetic?
What people actually say about CrowdSynthetic — is it worth it?
We scanned public community sources for CrowdSynthetic on Oct 21, 2026 and could not establish that the discussion we found is about this tool rather than something else sharing its name. Only 4 of the posts we fetched could be positively tied to CrowdSynthetic. Rather than publish a sentiment score built on the wrong subject, we publish nothing here and re-run the scan.
How we verified this
Every listed fact about CrowdSynthetic — pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 8 Nov 2026. Analysis is drafted with AI models and checked against our editorial standards before publishing; see how we verify.
Verification history
We have re-verified CrowdSynthetic 14 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed pricing page
- — changed who it suits, who should skip it, features, description, pricing tiers, our verdict
- — changed pricing tiers, summary, our verdict, description
- — changed limitations, pricing page
- — changed features, pricing tiers, who should skip it, description, our verdict
- — changed pricing page
Showing the 6 most recent of 14 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does CrowdSynthetic cost in 2026?
CrowdSynthetic: Free to use. Pricing last verified 8 Nov 2026.
Plans compared
Every published CrowdSynthetic tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Free (MIT license) | Free | — | — |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where CrowdSynthetic's pricing actually pencils out — and where peers do it cheaper.
There is no pricing at all — CrowdSynthetic is MIT-licensed source published at $0, with no tiers, seats or usage metering. That puts it below every commercial pedestrian-dynamics suite on cost, and what you pay instead is time: setting up a Python 3.9+ environment, OpenCV dependencies and a layout.json by hand. Budget for a data-modelling suite when you need vendor-supported fidelity, validation and support.
Has CrowdSynthetic's pricing changed?
No plan price for CrowdSynthetic has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick CrowdSynthetic?
Pick CrowdSynthetic if you are Event organizers running a free first-pass evacuation and exit-placement concept test, Safety managers prototyping zone caps and exit layouts before commissioning a study, Researchers and students exploring pedestrian dynamics with readable Python source, Python developers who want a small MIT-licensed crowd simulation base to extend.
Look elsewhere if you are Live event crowd management or any safety-critical decision-making, Real-time monitoring tied to cameras, turnstiles or sensors; there is no live ingestion, Non-technical stakeholders who need a polished GUI or 3D visualization, Large multi-venue or city-scale simulation work.
Skip it if Skip CrowdSynthetic if you need live sensor or camera input feeding a real-time evacuation decision, or if you need validated, supported modelling for an actual event safety plan rather than a free Python proof of concept.
GeneratedReal-world workflow fit
Concrete scenarios for the personas CrowdSynthetic actually fits — and what changes day-one when you adopt it.
Write the venue into layout.json with zones, stage position and exits, pip install -r requirements.txt and run python -m src.main, then watch the heatmap to see which zone saturates first.
Outcome: A concrete answer to "which zone goes first?" plus concert_risk_log.csv showing the zone risk that drove the NORMAL to EVACUATION switch.
Re-run the identical layout with a moved or added exit, then line up the two concert_risk_log.csv files side by side and compare when each run printed "FRONT saturated".
Outcome: A defensible before/after comparison of exit placement that you can take into a planning meeting without spending anything.
Have students edit zones and exits in layout.json, predict the outcome, then run the simulation and inspect the freeze-frame after evacuation completes.
Outcome: A live heatmap and per-run JSON logs that make crowd risk tangible and give students something quotable to write up.
Use cases
- Model a concert layout in layout.json to see which zones saturate first before committing to a floor plan.
- Re-run the same layout with different exit configurations and compare the logged risk CSVs to test evacuation strategies.
- Read zone-level risk scores to decide where to place staff and signage.
- Use the logged CSV/JSON run data as a dataset for coursework or downstream modeling experiments.
- Teach pedestrian dynamics and evacuation logic by having students edit the layout and predict the outcome.
- Fork the src/ modules as a starting skeleton for a custom crowd-simulation experiment.
Setup time & first value
How long it actually takes to get something useful out of CrowdSynthetic — broken out by persona, not the marketing-page minute.
Python developers: roughly 10 minutes — pip install -r requirements.txt, edit layout.json, run python -m src.main. Analysts comfortable with JSON but not Python: closer to an hour if you need to install Python 3.9+ and fix an OpenCV install (a cv2.error usually means OpenCV isn't installed correctly).
Switching to or from CrowdSynthetic
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From a commercial pedestrian-dynamics or evacuation-modelling suite: export your zone layout and re-enter zones, stage position and exits by hand into layout.json, then compare the logged CSV against the suite's output
- →From a notebook or spreadsheet hand-model: move the geometry out of formulas and into layout.json, then use concert_risk_log.json as the structured dataset your notebook reads after each run.
- →From the original single-script CrowdSynthetic POC: switch to the modularized src/ package — same layout-driven geometry, zone risk, prediction, heatmap, EVAC and logging behaviour, easier to extend.
- ↗To a commercial pedestrian-dynamics suite: your layout.json geometry and the risk thresholds you tuned transfer as configuration, and the logged CSVs give the vendor a baseline to validate against.
- ↗To a custom in-house simulator: fork the src/ modules as a skeleton, keep the heatmap and CSV/JSON logging, and replace the agent-movement logic with your own model.
- ↗To a research codebase: export concert_risk_log.json as the run dataset and cite the MIT-licensed source you started from.
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “CrowdSynthetic”, and we withheld 6: 6 could not be judged, because “CrowdSynthetic” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about CrowdSynthetic.
Official links
What are the best CrowdSynthetic alternatives?
The closest alternatives to CrowdSynthetic we list are RD Agent, Weather Lab and Gigasheet. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| RD Agent | Free | Free | — |
| Weather Lab | Free | Free | — |
| Gigasheet | Contact Sales | Custom pricing | — |
Alternatives to CrowdSynthetic
View all
RD Agent
Open-source, MIT-licensed framework that runs LLM-driven generate-evaluate-rewrite loops for quantitative factor mining and ML experimentation.
Weather Lab
Explore experimental AI models for cyclone forecasting from Google, now with live lightning and storm cell tracking.
Tools that pair well with CrowdSynthetic
Common stack mates teams adopt alongside CrowdSynthetic, with the specific reason each pairing earns its keep.
RD Agent
Open-source, MIT-licensed framework that runs LLM-driven generate-evaluate-rewrite loops for quantitative factor mining and ML experimentation.
Weather Lab
Explore experimental AI models for cyclone forecasting from Google, now with live lightning and storm cell tracking.
Gigasheet
Healthcare price transparency data turns into negotiable rate benchmarks, provider rate scores, and traceable answers for US payer and
CrowdSynthetic vs its closest rival
CrowdSynthetic's closest head-to-head is with Isomorphic Labs.
Our CrowdSynthetic vs Isomorphic Labs verdict written Jul 3, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
Head-to-head comparisons
Crowdsynthetic vs Isomorphic Labs
Verdict being re-reviewed against current pricing and data.
Crowdsynthetic vs Codametrix
These aren't competitors, so there's no either/or call to make: CodaMetrix is an enterprise platform a hospital revenue cycle team buys, and CrowdSynthetic is a free Python proof-of-concept you'd clone from source. If you run a large health system on Epic or Cerner and want autonomous coding at scale, CodaMetrix is the serious option — it carries 2026 Best in KLAS recognition for autonomous medical coding and a documented quality framework, though you'll need a sales conversation to learn cost. If you're modeling crowd density at a concert to sanity-check exits and zone risk, CrowdSynthetic does that for free today, but it's explicitly not for live safety-critical deployment. Buy CodaMetrix; download CrowdSynthetic.
GeneratedCrowdsynthetic vs Screenplayiq
Verdict being re-reviewed against current pricing and data.
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