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Deterministic · Reproducible · Auditable

The decision layer
for agentic AI

Memintel compiles natural language intent into deterministic execution graphs. Same input. Same decision. Every time.

IntentYou describe what to monitor
Concept ψSystem computes the signal
Condition φMemintel decides if it matters
Action αYour system executes

Why Memintel

⚙️

Deterministic by design

Same input, same guardrails, same decision — every execution. No probabilistic drift, no LLM on the hot path.

🔍

Fully auditable

Every decision is traceable: which primitives were fetched, which concept was computed, which strategy fired and why.

📐

Strategy-driven conditions

Conditions evaluate meaning through structured strategies — threshold, percentile, z-score, change, composite — not prompt heuristics.

🔄

Calibration without mutation

Feedback drives parameter recommendations. Applying calibration creates a new immutable version. Historical decisions stay reproducible.

🏗️

Guardrails system

Admin-defined policy layer constrains LLM output at task creation time. Strategy registry, type-compatibility, parameter priors, bias rules.

🧩

Composable primitives

Concepts compose from versioned primitives. Features derive intermediate signals. The entire graph is typed, validated, and version-pinned.