How Synapify Works
Synapify
Requirements
Define Requirements
Describe your domain in plain English and let AI suggest an initial RIDDL structure — domains, contexts, entities, commands, events, and workflows. Start from what the system does, not technology choices.
Learn more →Template
Choose a Template
Pick an industry-specific starting point from riddl-models — healthcare, finance, commerce. Customize proven patterns rather than starting from scratch.
Learn more →Refine Validates Continuously
Author & Refine
Visual + text editing with bidirectional sync. Drag and drop domains, contexts, entities, and workflows, or write RIDDL directly. Validation runs continuously using the same engine as the riddlc compiler.
AI assists with pattern suggestions, error explanations, and completeness checks.
Learn more →Docs
Generate Documentation
Produce always-in-sync documentation from your RIDDL specification — architecture overviews, entity catalogs, event flows, and API references. Never maintain separate docs that drift from reality.
Learn more →Code
Generate Code
Produce entity classes, command handlers, event definitions, API endpoints, and test stubs from the specification. Developers implement business logic in placeholders, then compile, test, and deploy with their existing toolchain.
Code generation is in development. Targets: Akka/Scala, Quarkus/Java.
Learn more →Generator
The Synapify component that transforms your validated model into output artifacts — documentation, api specifications, code, etc.
Learn more ↓Simulate & Revise Cycle
Run your model through the Simulator to validate behavior, not just structure. When issues are found, revise the model in Author & Refine, then simulate again. This iterative cycle ensures your design is correct before generating code.
(Digital Twin)
Simulator (Digital Twin)
Creates a digital twin of your model — a running simulation that exercises entities, message flows, and state machines without implementation code. Validates behavior, not just structure.
Learn more ↓Start from
orGenerate
andFrom business idea to deployed system — Synapify's model-driven workflow keeps your design as the source of truth.
Why This Approach Matters
Shared Understanding
Business experts and developers work with the same artifact. No translation layer between “what we designed” and “what we built.”
Risk Reduction
Validate structure and simulate behavior before writing implementation code. Find design flaws when they cost minutes to fix, not weeks.
Living Documentation
The RIDDL specification is the source of truth from day one through production. It evolves with the system instead of decaying into outdated artifacts.
AI-Native Design
RIDDL models are structured data, not diagrams or prose. AI tools can read, generate, and reason about RIDDL directly — making your architecture a first-class input to code generation, validation, and simulation rather than a picture someone has to interpret.
Technology Independence
RIDDL describes what your system does, not how it’s built. Swap databases, messaging platforms, or cloud providers without rewriting your architecture. The model stays stable while implementations evolve.
Incremental Adoption
You don’t have to model your entire enterprise on day one. Start with a single bounded context, prove value, and expand. Each RIDDL model is self-contained and composable with others as your practice matures.
Compliance-Ready
RIDDL’s built-in briefly and described by
clauses, along with term definitions and author
metadata, produce models that double as living specification documents.
Auditors and stakeholders can read the model directly — no
separate documentation to keep in sync.
Onboarding Accelerator
New team members use Synapify to explore the system’s domains, contexts, and message flows through graphical views and guided navigation — grasping the architecture in hours instead of weeks. The model is the single source of truth, not a wiki, not tribal knowledge, not a stale diagram.
Simulation: Your Model’s Digital Twin
Synapify creates a running digital twin of your RIDDL model — exercising every entity, message flow, and state machine without a single line of implementation code.
(the spec)
(simulation)
Steer
(Synapify)
Five Simulation Layers
Each layer is opt-in with sensible defaults. Start with system model validation and add layers as your design matures.
System Model
Exercises entity state machines, command handlers, and message flows exactly as your RIDDL model defines them. Auto-generates tests from the model.
Timing
Models realistic latency — fast intra-context messaging versus slower cross-context network hops. Configurable profiles reveal timing-sensitive design issues.
Chaos
Injects failures — dropped messages, timeouts, partial outages — to test how your design handles the unexpected before production does it for you.
Infrastructure
Models hardware as general classes — compute, storage, networking — to validate capacity and persistence assumptions at the architecture level.
Cost
Estimates cloud resource consumption based on simulated load. Catch expensive design decisions at the whiteboard stage, not the invoice stage.
Epics Drive Scenarios
User journeys already in your RIDDL model become simulation scenarios. Define how many, when, and what mix — don’t re-describe the flows.
AI-Authored Scenarios
AI reads your model and your intentions to generate realistic test scenarios — including edge cases you might not think to write by hand.
No Code Required
The RIDDL model is the spec, the digital twin is the simulation, Synapify is the control plane. Validate your design before writing implementation code.
Generation: From Model to Artifacts
Synapify transforms your validated model into documentation, API specifications, production code, and implementation scaffolding — all derived from a single source of truth.
Hugo
AvailableGenerate Hugo-compatible documentation sites with domain maps, entity catalogs, and message flow diagrams.
AsciiDoc
AvailableGenerate AsciiDoc specification documents for publishing, review, or integration with existing doc pipelines.
OpenAPI
AvailableGenerate OpenAPI specifications from your model’s commands, queries, and data types for REST API documentation and client generation.
Smithy
AvailableGenerate AWS Smithy IDL from your model for service-oriented API definitions and AWS integration.
Production Code
Coming SoonGenerate implementation scaffolding — entity classes, handlers, API endpoints, and test stubs. Targets: Akka/Scala, Quarkus/Java.
See It in Action
Try the RIDDL language in your browser, explore the documentation, or see how it fits your team's needs.