Overview
Solaris Zarya Engine is an autonomous developer agent built from first principles with a deterministic engineering spine. It enforces strict memory hierarchy, confidence-gated retrieval, host-side AST security validation, crash-resilience, and human-in-the-loop permission tiers rather than relying on unstructured conversational loops or unverified tool execution. The system includes a 4-tier persistent SQLite memory with WAL mode, covering episodic, semantic, procedural, and project memory. It uses local BAAI/bge-small-en-v1.5 384-dimensional ONNX embeddings with deterministic offline fallback. The engine synthesizes pure Python skills with dedicated unit test suites and validates them through an AST allowlist sandbox. It also provides a crash-resilient task FSM and Goal DAG planner that decomposes complex instructions into sub-goals with prerequisite resolution and depth caps. Additional capabilities include domain validation and game engine synthesis for Unity and Blender, plus metacognitive reasoning, DPO dataset building, and QLoRA fine-tuning.
Pricing
Free
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Use Cases
- Teams use Solaris Zarya Engine to query memory with confidence-gated refusal.
- Teams use Solaris Zarya Engine to synthesize, sandboxed-validate, and persist a Python tool.
- Teams use Solaris Zarya Engine to decompose objectives into Goal DAGs with prerequisites.
- Teams use Solaris Zarya Engine to scan, hash, summarize, and embed workspace files into Tier 4.
- Teams use Solaris Zarya Engine to synthesize and test C# scripts inside isolated Unity worktrees.
- Teams use Solaris Zarya Engine to synthesize Python scripts and export 3D assets in Blender.
- Teams use Solaris Zarya Engine to build DPO pairs from verified reasoning episodes.
Features
AI assistant
Natural language interface
Workflow automation
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