EvaCortex Lab explores wave-based semantic memory and phase-aware retrieval for AI systems that require meaning stability under composition, operator-sensitive semantics, and inspectable semantic interaction — beyond ranking by scalar similarity alone.
The ψ-stack reframes retrieval as semantic interaction — alignment, interference, and phase organization — rather than metric proximity. This architectural perspective addresses brittleness observed in embedding-centric pipelines, where negation, modality, and composition can collapse into scalar similarity.
This repository serves as a conceptual index into the EvaCortex Lab ecosystem: a family of architectures and tools for non-metric semantic retrieval, wave-structured memory, and phase-aware reasoning.
When retrieval becomes the semantic memory substrate for RAG systems, agents, or decision workflows, small semantic distortions can compound:
- negation and modality may flatten under metric similarity
- operator composition can drift or behave unexpectedly
- scalar ranking provides limited structural transparency
Wave-based semantic memory models patterns using amplitude + phase, enabling structured interaction instead of pure geometric proximity. This supports:
- operator-sensitive retrieval
- semantic stability under composition
- inspectable interaction structure
- high-precision semantic workflows
The goal is not to replace existing infrastructure, but to expand semantic control where structural correctness matters.
EvaCortex Lab components form a modular ecosystem for phase-aware semantic systems.
Wave-native semantic memory storage and retrieval engine organized around phase-aware interaction and interference-structured similarity.
Open research implementation:
https://github.com/LexProfi/ResonanceDB
Projection layer mapping language and other modalities into wave-structured semantic patterns compatible with ResonanceDB.
Includes Domain Packs — structured semantic overlays encoding operator behavior and contextual topology for high-precision domains.
More info:
https://www.evacortex.ai/echothesis
Domain Packs introduce domain-specific semantic scaffolding without retraining base models. They capture operator and relational structure such as:
- polarity and modality distinctions
- conditional and exception logic
- domain-specific semantic anchors
- structured constraints
Representative domains include pharma, genetics, and finance — environments where operator semantics materially affect retrieval behavior.
More info:
https://www.evacortex.ai/domain-packs
Hybrid semantic retrieval and reasoning mesh combining wave memory with graph or structured reasoning layers.
More info:
https://www.evacortex.ai/sensemesh
Trace-oriented orchestration layer for building cognitive workflows and agent systems atop wave-based semantic primitives.
More info:
https://www.evacortex.ai/reasoning-core
A typical adoption pattern:
- retain existing embedding infrastructure where appropriate
- introduce a wave memory layer for operator-sensitive retrieval
- route high-risk or governance-critical queries through phase-aware memory
This architecture supports gradual coexistence in production systems.
EvaCortex Lab publishes conceptual preprints that establish the architectural framing of wave-based semantic memory and phase-aware retrieval.
These works are intentionally high-level and focus on theoretical and architectural perspectives. They do not describe operational procedures or implementation specifications.
Primary reference:
Wave-Based Semantic Memory with Resonance-Based Retrieval
https://arxiv.org/abs/2509.09691
Additional conceptual materials explore topics such as phase-sharded routing, resonance-based explainability, and semantic interference beyond metric embeddings.
A broader collection of conceptual whitepapers — reflecting exploratory research, architectural thinking, and adjacent ideas — is available here:
These documents are provided for intellectual and conceptual context. They are not implementation guides and should not be interpreted as formal specifications of the ψ-stack architecture.
Research index:
https://www.evacortex.ai/blog
- Licensing is defined per repository or artifact. Always consult applicable
LICENSEfiles and companion notices. - Certain ψ-stack architectural concepts may be subject to pending patent applications. Public materials intentionally limit disclosure to conceptual framing.
- Training or usage policies may apply depending on artifact.
Nothing in this repository or its conceptual materials constitutes an implementation specification or alters the licensing terms of any separate code repositories or artifacts.
Rights to software components are governed exclusively by their respective licenses.
Website:
https://www.evacortex.ai/
Research & partnerships:
hello@evacortex.ai
When evaluating EvaCortex Lab systems, include domain constraints, semantic risk tolerance, and auditability requirements.
Keywords: wave-based semantic memory, phase-aware retrieval, non-metric semantic search, semantic interference, resonance-based similarity, explainable retrieval, operator semantics, domain packs, structured semantic interaction, RAG memory architecture.