Solarch is a backend-architecture tool that flips the traditional AI coding workflow on its head. Instead of generating code first and hoping the architecture holds up, it generates the architecture first, grounded in canonical patterns and validated by a strict Rules Engine. This tool belongs to the category of AI-assisted diagramming and code generation platforms, designed specifically for backend developers, software architects, and teams who demand architectural precision from the start. Its core value is ensuring that your architecture is always perfectly in sync with the code, eliminating the dreaded architectural drift that plagues most projects. The AI proposes changes, the rules verify them, and only correct graphs land on the canvas. This approach prevents blank-canvas paralysis and cuts through boilerplate, letting developers focus on the system they already had in mind. For anyone tired of diagrams that don't match the codebase, Solarch offers a revolutionary approach: make the diagram the single source of truth.
The concrete problem Solarch solves is the enduring disconnect between architecture and code that plagues software projects. Developers often start coding without a clear architectural plan, or they draw diagrams that quickly become outdated as the code evolves. This leads to architectural drift, where the implemented system diverges from the intended design, resulting in technical debt, difficult refactoring, and integration issues. For teams, this means wasted time in code reviews, alignment meetings, and rework. Solarch addresses this by making the diagram the living, validated blueprint: every connection is checked immediately as it is drawn, and code is generated directly from that validated graph. This matters because it saves weeks of debugging and alignment, allowing developers to ship with confidence that the system matches the design exactly. The self-correcting loop ensures that any violations are caught early, not three commits later.
The first major feature group is the Rules Engine with default-deny validation. The Rules Engine is a default-deny validator: every connection that is not explicitly whitelisted is forbidden. It enforces seven anti-patterns and three conditional checks—for example, a Controller cannot reach a Table directly; it must route through a Service or Repository. Illegal edges are rejected the moment you draw them, not three commits later. This guardrail prevents common architecture violations in real time, giving developers immediate feedback. When a violation occurs, the agent inserts the correct intermediate nodes (like a Service and a Repository) and re-applies the rules. Rejections feed back until the graph is clean—or it never commits. This ensures that only valid architectures persist, saving hours of debugging and preventing costly mistakes that would otherwise surface only in production.
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The second major feature group is the Hybrid Code Engine. Solarch uses a two-stage code generation process. Stage 1 is deterministic: a compiler turns the validated graph into a complete skeleton with zero tokens—including DTOs, entities, and constructor injection straight from the edges. Then Stage 2 uses surgical AI to fill only the empty function bodies, using about 300 tokens per function. This hybrid approach means that roughly 80% of the project ships as boilerplate, while the algorithmic logic stays the developer's responsibility. The result can be exported as actual code, a Mermaid diagram, or AI-readable memory for other tools. This gives developers a massive head start: they avoid writing repetitive structural code and can focus on business logic, all while ensuring the architecture remains correct because the graph is the single source of truth.
The third feature group encompasses the one-canvas approach with ghost references and canonical patterns. Solarch provides a single canvas where every part of the backend is represented—controllers, services, repositories, tables, DTOs, queues—connected by 16 semantic edges. To manage complexity, it organizes nodes into eight families: Data, Business, Access, Infra, Client, Security, Config, and Structure. Each node lives in exactly one tab, but other tabs can import it as a ghost reference, not a copy, ensuring a single source of truth without duplication. Additionally, Solarch uses GraphRAG and LangGraph to ground every plan in a vector-indexed library of canonical patterns such as rest-api, auth, cqrs, and graph. This makes the AI an architect rather than just autocomplete, providing proven architectural foundations that accelerate design and reduce errors.
Solarch's workflow begins with the Omni-bar, where the user can either type a sentence or sketch a box. The AI interprets the intent and generates an architecture graph, which is immediately validated by the Rules Engine. If a violation occurs, the system suggests corrections, and the graph is refined through a self-correcting loop until clean. The user can switch between two modes: AgentInstruct, an autonomous builder, and a conversational architect, providing flexibility for different working styles. From the validated graph, the Hybrid Code Engine generates code that matches exactly. The schema becomes an API contract, which becomes a typed client—every layer checked at compile time. Change a column in the database, and the frontend stops compiling until the fix is made. This end-to-end type safety ensures consistency across the entire stack.
Concrete use cases demonstrate Solarch's value. A team building a microservices backend can use Solarch to design a cart and checkout system with separate modules for orders, payments, auth, and more. The AI generates the architecture with proper service boundaries, and the Rules Engine prevents cross-boundary violations, resulting in a clean, deployable design. Another scenario: an individual developer prototyping a new feature can draw a quick sketch, have Solarch generate the skeleton code, then fill in the business logic. The outcome is a correct, testable codebase that matches the intended design. For teams onboarding new members, Solarch's canonical patterns provide consistent architectural references, reducing the learning curve. Enterprises can define custom rules matrices to enforce company-specific standards, ensuring every commit adheres to governance policies.
Target users include backend developers, software architects, full-stack engineers, and development teams working with TypeScript and Node.js. Solarch integrates with modern tools: it generates code compatible with Cursor and Claude, exports Mermaid diagrams, and produces vector memory for AI assistants. Pricing plans range from a free tier (2 projects) to $5/month for Draw (unlimited projects, rules validation), $20/month for Build (AI scaffolding), $100/month for Code (full code generation), $30/seat/month for Team (shared projects with ghost references), and custom Enterprise (self-host, SSO, audit logs). Every paid plan starts with a 7-day trial. In summary, Solarch transforms backend development by making architecture first-class, automated, and continuously verified, ensuring your code always reflects the system you designed, without drift or rework.
Backend developers, software architects, full-stack engineers, and development teams who work with TypeScript and Node.js. Solarch is ideal for startups needing rapid architecture validation, as well as enterprises requiring strict architectural governance. It serves individuals who want to eliminate boilerplate and teams that need a shared, verified single source of truth for their backend architecture. The tool is especially valuable for those tired of architectural drift and mismatches between diagrams and code.