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Ammonix

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Press release · September 22, 2026Ammonix Launches Its Architecture for Specialist AI AgentsRead ↗Dark Vector Cognition · September 23, 2026Who actually decides? An independent first look at the control-room agentWatch ↗

Agents For
High-Stakes Applications

How Ammonix Agents Combine Fast Decisions With Intelligent Understanding

Architecture: (i) system one decision model trained on defined rules and user-defined data and (ii) system two model (LLM) providing the agentic intelligence connected to the former by a trained skills layer.

System One Model = fast Expert (0.15s)
Raw observation
Signals, records, requests
Mechanistic world model
Features
Classifier swarm
RLCD
Knowledge Universe
States, Actions, Parameters
Trained Skills
RLVR-trained skill layer
Rules + local evidence rank permitted responses
System Two Model = LLM Intelligence
Frozen local LLM
Rationale, coordination and dialogue
Operator / system
Approves, edits or executes

The local LLM stays frozen during use. Customer fine-tuning precedes a tested release.

New outcomes → verifiable evaluation → approved skill updates

Why Ammonix?

01 / 08
01

Agentic systems generate high cost by re-reasoning even repeatedly occurring tasks

Ammonix separates expertise from intelligence: the expertise is created once, and standard tasks reuse it. Our claims agent matched the strongest GPT-6 configuration with 4.7 times fewer GPT-6 tokens.

02

Frontier models hallucinate because they answer even when they do not know

Every Ammonix answer is generalized from recorded examples. When a situation falls outside them, it will inform you.

03

Other AI agents ask you to trust a black box

Ammonix is transparent: it gives you all the relevant examples and features behind a response.

04

An LLM can be talked out of its guardrails

Ammonix deletes a forbidden action from the list before it chooses. It cannot pick what it cannot see.

05

Frontier models live in datacenters you cannot even locate

Ammonix provides local superintelligence even when using local models, which guarantees data safety and cybersecurity.

06

Language models learn from huge pretraining datasets you cannot control

Ammonix acquires its expertise from your data, your rules, or strategies you designed.

07

Most AI has low sample efficiency and needs millions of training examples

Ammonix reaches expert level from a few hundred examples, and its episodic memory allows it to learn and retrain from new examples to keep it up to date.

08

Frontier models have vision and text, but cannot understand time series

Ammonix natively aligns time-series data, sensor feeds, waveforms, unstructured documents, and structured records within a shared decision state.

How It Works