Computational research

SRE · HAM

Semantic Resonance Engine and Holographic Associative Memory: research into wave/tensor representations, search and associative retrieval.

Semantic memory and search · Python / Rust / TypeScript SDK / FastAPI / Semantic search

The product problem

Test an alternative semantic-representation model through usable programming interfaces.

Stage

A research engine with integration interfaces. Retrieval quality and scaling need reproducible comparisons.

Concept illustration: SRE · HAM
A concept illustration, not a screenshot of a running product.

Record relations → search → retrieve

An illustrative intended journey, not a demonstration of the current live release.

  1. Represent data as semantic relations.
  2. Separate engine operations from memory storage.
  3. Call retrieval through an adapter or SDK.
  4. Compare results with quality references.

System components

  • Engine model: representations and search operations.
  • Store and associative memory: a separate write/retrieval layer.
  • Server adapters: REST, a chat-completions-style interface and RESP.
  • Python/TypeScript SDKs, experimental Rust modules and explicit QA groups.

Architecture & ownership

Core and store are distinct from server adapters and SDKs. RESP does not establish full Redis compatibility; Rust modules do not prove their use in every path.

How can an alternative representation be measured without calling it a universal search replacement?

What to validate before use

No ready database replacement, proven O(1), Zero-RAM, speedup or AGI claim is made.

This describes the development scope. This page does not run the product, process payments or verify real-time availability.

Related products, distinct problems

Next step

Discuss a SRE · HAM workflow

Describe the problem, current system, constraints and desired outcome. We agree scope and deliverables before cost and launch.

Discuss the task on Telegram ↗

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