KAPEX ships as a single Docker container. Inside: a memory engine built for the realities of production AI — salience scoring, processing-aware decay, multi-channel retrieval, a safety pipeline, and the governance to run it in regulated environments. The page below is the public overview. The technical reference lives behind NDA.
Every memory node receives a composite legitimacy score the moment it is ingested — not at query time, not after the fact. The scoring runs across multiple linguistic dimensions designed to separate enduring relevance from passing chatter.
Specific signals, signal counts, weight derivations, normalization scheme, and the legitimacy gap mechanism are shared under mutual NDA during pilot onboarding. The scoring engine is the protected core of KAPEX's IP.
The crown-jewel innovation. When a user actively processes, reflects on, or resolves a topic, that topic's prominence decreases over time. Unresolved topics persist. This is the mathematical inverse of every published memory system — and the reason context windows feel coherent over weeks instead of cluttered with stale repetition.
The decay model derivation, parameter ranges, and the specific mechanism behind processing modulation are shared only under mutual NDA. This is the patent-protected core of KAPEX.
Retrieval assembles a memory context block within a token budget. The mechanism balances salience, recency, and constraint-pinned content so no single topic monopolizes the model's working memory.
Most "memory" implementations dump a top-K vector match into the prompt and hope the LLM sorts it. KAPEX returns ordered, budgeted, qualified context — the model spends compute on responding, not on triaging stale recall.
Channel definitions, budget allocation logic, expansion strategy, and the multichannel-fusion mechanism (Scale+) are shared under mutual NDA.
An independent safety pipeline that cannot be overridden by memory state, user input, or operator configuration. It runs identically regardless of which LLM you call downstream — the same safety properties apply whether you're on Claude, GPT, Gemini, or your own fine-tune.
Specific module counts, sentinel architectures, fabrication-guard layer order, and the policy-enforcement mechanism are shared under mutual NDA.
KAPEX builds memory around real-world entities — people, places, projects, decisions — rather than flat vector embeddings. Different facets of the same entity score and decay independently.
Flat vector stores tag "Sarah told me about her divorce" and "Sarah and I went to dinner" with the same name and treat them as equal-weight memories. They're not. One is identity-level, one is logistical — and KAPEX scores, decays, and surfaces them independently.
The full entity hierarchy, facet-resolution rules, and the relational-profile tracking schema are shared under mutual NDA.
KAPEX ships as a Docker container with an annual license key. You run it in your AWS, GCP, or Azure account. Memory data lives in your database. Sandstone provides the container, the license, and the support — and never sees a single byte of user data.
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Sign up for the free KAPEX beta and see salience-scored memory in action — no NDA, no commitment.
Start the 30-day trial. Full feature set, founder support. Architecture deep-dive under mutual NDA.