Any model.
Bring a cloud model or run one locally. Choose providers for each task through compatible APIs, and add your own provider plugin.
Your sim.
Wide open.
Any model. Any sim. Any vendor.
End-to-end simulation management with an open-source core. Fully extensible, so you can build the platform your reality needs.
Mac · Windows · LinuxLocal engine. Fast by design.
Your scenario, connected to your room.
BAY 03 · ACUTE ASTHMA
SIMULATIONArrival from triage
SpO₂ %89
Pulse bpm118
Resp. /min28
Simulated patient observations
Explore the patient journey
00:00
Session begins. The patient arrives breathless.
Try it: choose a state, then flag a moment. Interactive preview · illustrative data
Everyone has
a unique reality.
Your lab has its own equipment, constraints and ways of teaching. i2l Sim gives you an open foundation to build around all of it.
Extend any layer, from a device interface to the simulation engine. Replace a provider. Create a screen. Make the platform yours.
See how you can contributeApache 2.0 core planned at launch. Innov2Learn’s product bundles are licensed separately.
Any sim.
Author the patient journey your teaching needs. Use the built-in scenario runner, or build a different simulation engine behind the same interface.
Any vendor.
Connect the equipment you own. Map its messages or write an adapter, and keep your scenarios portable between rooms.
Any protocol.
Use standard transports or bring your own. An extensible interface layer connects your devices to the session.
HTTPWebSocketTCP / UDPMQTTBLESerialFilesYour adapter
Device support depends on its mapping or adapter. BLE and serial use configured bridges.
Mac. Windows. Linux.
The same platform, on the machine that fits your team.
A local engine built for speed.
Run the session, database and interface on your machine. Keep the session moving locally; use the cloud when your chosen AI provider needs it.
One workflow.
End to end.
Prepare the scenario, configure the room, run the session and debrief with the full story. i2l Sim carries the context from the first draft to the next teaching moment.
Start with the work
you’ve already done.
Bring a Word document, PDF, Markdown file or pasted text. AI turns the material into patient states and learning outcomes, with the source beside every extracted detail.
You review and approve the scenario before it runs.
.DOCX.PDF.MDTEXT
Acute asthmaFacilitator guide.docx
SOURCEPATIENT PRESENTATION
A 29-year-old with known asthma arrives breathless and hypoxic on room air.
“Learners assess, apply oxygen, escalate with SBAR and give a nebuliser.”
Patient journeyReady for your review
Shape every
turning point.
Review the extracted patient journey. Adjust states, set the expected actions and choose what happens when learners respond, wait or change course.
Source-backed fields and AI suggestions stay distinguishable until you approve them.
Patient journeyREVIEW
ENTRY POINTAcute asthmaSpO₂ 89% · pulse 118 bpm
Oxygen applied
RespondingSpO₂ 94% · pulse 112 bpm
Time elapses
DeterioratingFacilitator can intervene
Keep your attention
in the room.
Guide the session from one console. Route the patient’s values to a monitor, send lines to a standardized patient, and capture learner actions as the story unfolds.
Pause a session, hold a state or take manual control whenever the teaching moment calls for it.
Try the interactive previewBay 03EXAMPLE ROUTING
One patient stateVitalsBedside monitor
Patient dialogueRoom speaker
Actor cuesConfederate’s phone
ObservationsLearner record
Return to the
moments that matter.
Follow the path learners took through the scenario. Bring together recorded actions, patient observations and flagged moments to guide a focused debrief.
Quotes and captured media add context when those capabilities are configured for your session.
Session debriefEXAMPLE
00:00
Arrival from triage
Baseline observations established
02:14
Oxygen applied
Patient enters the responding state
05:32
Patient improving
Reassessment becomes the teaching focus
Flag a moment in the preview to add it here.
Your room.
Your equipment.
Connected.
Every lab has its own setup. Keep your scenario focused on the patient, and map its outputs to the screens, speakers and interfaces you use.
Talk through your setupSIMULATION LABEXAMPLE CONFIGURATION
DISPLAYBedside
monitorPatient observations
monitorPatient observations
AUDIOThe patient’s
voiceRouted dialogue
voiceRouted dialogue
i2l SimThe scenario connects the room.TABLETLearner
patient recordCharted observations
patient recordCharted observations
INTERFACEConnected
lab equipmentMapped inputs & outputs
lab equipmentMapped inputs & outputs
Your site profile defines what connects.
A familiar screen becomes part of the sim.
Pair browser-based displays and actor views with the session. Give each person the information their role needs.
The scenario travels with you.
Define channels such as patient voice and bedside monitor once. Each room routes them to its own equipment.
The session runs locally.
The runtime, database and interface live on your machine. Cloud AI is used when your chosen import or voice provider requires it.
Device connectivity depends on the interface or adapter configured for your equipment.
Build your own.
Bring your agent.
You know what your lab needs. i2l Sim ships with agent skills so you can describe the change and let a coding agent build it. Anyone can contribute, including people who don’t write code.
From a need to an integrationEXAMPLE WORKFLOW
“Connect our monitor. Here are three messages it sends.”
The device-mapping skill guides your agent through creating the mapping, testing the sample messages and configuring your room’s routes.
Device mappingTestsSite configuration
Build and test in a development profile. Review before installing in your lab.
Connect a device
Turn sample messages into a tested mapping.
Create a plugin
Build a custom panel, interface or workflow with the SDK and testkits.
Add your scoring
Translate a local score table into tested rules for clinical review.
Set up your site
Describe the room. Configure its outputs and routes.
Skills use the open Agent Skills format, so your team can choose any coding agent that supports it.
Explore the repository Private during development · access requiredBuilt in your lab.
Shared through
the plugin store.
That integration you needed could help another team. Publish your plugins through the store, discover what others have built and adapt it to your own setup.
Bring your integration ideaA few practical
questions.
Send an overview to a colleague Who is i2l Sim for?
Simulation educators, facilitators and lab technicians who want to connect scenario preparation, the live session and the debrief. Learner and confederate views give participants the information they need for their roles.
Can I use the scenarios I already have?
The workflow starts with Word, PDF, Markdown or pasted text. AI extracts a structured scenario, and an educator reviews the source, resolves gaps and approves the patient journey before the session.
Will it work with our equipment?
Browser-based outputs and a configurable interface layer let a lab route inputs and outputs to different endpoints. Hardware needs a compatible adapter or mapping. Bring your equipment list to the demo so we can discuss the interfaces your setup needs.
What is open source?
The core is planned for Apache 2.0 at launch: the kernel, base services, interfaces, shared types, SDK, testkits, plugin scaffold, agent skills and wire protocol. Innov2Learn’s product bundles are licensed separately. The development repository is currently private.
Can we use our own AI model?
Yes. Choose a compatible cloud endpoint or a local model server, and configure providers by task. The open provider interface also supports custom plugins. A provider must support the capabilities its task needs, such as structured output or transcription timestamps.
Do I need to code to contribute?
The included agent skills guide a compatible coding agent through device mappings, plugins, score tables and site setup. Describe what you need and provide examples. The agent builds and tests in a development profile; your team reviews the result before installing it. Score tables still need clinical sign-off.
Does the session need the internet?
The session runtime and database are designed to run locally. Paired devices need access to the local network. Cloud-based AI providers need an internet connection for the features that use them.
How do we get started?
Request a demo with Innov2Learn. Tell us about your scenarios, rooms and equipment, and we’ll discuss the workflow and deployment options with you. The interactive example on this page illustrates the product experience; it is not a connected lab session.
Your next sim.
Your way.
Bring your scenarios, equipment and ideas.
Let’s explore what your team could build.