COSINIA / DETERMINISTIC MEMORY FOR AI

Memory That Returns Truth

Cosinia gives AI systems deterministic memory. No hallucination. No similarity guessing.

observe(JSON) → recall(JSON)
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What this replaces

Today’s stack

  • Embed text → store vectors
  • Chunking pipelines
  • LangChain / RAG
  • Prompt tuning loops
  • Unreliable retrieval

With Cosinia

  • Send structured events
  • Deterministic storage
  • Direct recall
  • No prompt engineering
  • Exact answers

Core idea

Cosinia does not store text or embeddings. It stores identity-bound events.

That means:

  • No hallucinated recall
  • No similarity search
  • No prompt engineering loops
  • Just deterministic memory

observe

Store structured events

→

compute

Cosinia builds memory state

→

recall

Return exact structured answers

Developer Workflow

SDK (Recommended)

Use a unified interface to observe and recall using either natural language or structured input.

Text → parsed automatically • JSON → full control

Direct JSON API

Interact with Cosinia using the deterministic semantic protocol for full control.

Best for infrastructure, pipelines, and advanced use cases

Example


// observe (natural language input)

POST /observe

{
  "text": "John gave Mary a book"
}


// parsed semantic event (Cosinia output)

{
  "mode": "observe",
  "events": [
    {
      "process": "directional_transfer",
      "process_family": "DIRECTIONAL_TRANSFER",
      "roles": {
        "role_sender": ["john"],
        "role_receiver": ["mary"],
        "role_object": ["book"]
      }
    }
  ]
}


// recall

POST /recall

{
  "mode": "recall",
  "extensions": {
    "process_family": "DIRECTIONAL_TRANSFER",
    "query_roles": {
      "role_receiver": ["mary"]
    },
    "target_role": "role_object"
  }
}

What you get

  • Deterministic recall — No guessing. Same input → same answer.
  • Structured output — Return data, not text blobs.
  • Condition-aware — Query time, location, values directly.
  • No LLM dependency — Runs without language models.
  • Secure by design — Enclave-executed deterministic execution.

Why current systems break

  • Vector similarity ≠ truth
  • Context windows drop information
  • RAG pipelines are fragile
  • Memory is not persistent

Cosinia replaces approximation with exact recall.

Build AI that remembers correctly, not approximately.

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