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Radar
Monitors market and regulatory signals and prepares candidates for evaluation.
Back to RAUNEM RAUNEM / CASE STUDY
AMS — Autonomous Marketing System
An AI-native marketing operating system designed to turn market signals into grounded content, controlled publication, conversations and measurable learning — with durable state, human control and deterministic safeguards.
01 / THE PROBLEM
Marketing automation usually stops too early.
A trigger starts a workflow. An LLM generates content. Another service publishes it. But the system rarely knows what happened next — or whether an external action actually completed as intended.
AMS was designed around a different idea: marketing should behave as a controlled operating loop, not a collection of disconnected automations. State, evidence, approvals and outcomes have to survive between steps.
02 / THE SYSTEM
From signal to learning.
The model is not the system. AMS combines deterministic logic, durable state, orchestration and model reasoning, with human authority preserved where decisions matter.
Source / Topic→Content→Platform→Response→Conversation→Qualification→Client→Business outcome→Learning
03 / HOW IT WORKS
A controlled editorial pipeline.
02
Topic selection
Prioritises topics by relevance, audience fit and expected business value.
03
Evidence
Collects reliable sources and preserves provenance before generation begins.
04
Writer
Uses LLM reasoning to turn grounded evidence into channel-ready content.
05
Cover & assets
Produces supporting media and publication assets for the selected format.
06
Review package
Bundles content, sources, metadata and channel variants for inspection.
07
Approval
Keeps consequential external action behind explicit human boundaries where required.
08
Publication
Delivers approved material through channel-specific workflows and records the result.
04 / RELIABILITY
Autonomy without blind trust.
The difficult part of an autonomous system is not generating text. It is controlling what happens when reality differs from the expected path.
STATE & MEMORY
Durable context
- Durable workflow state
- Evidence and provenance
- Explicit approval states
DETERMINISTIC CONTROL
Rules before action
- Deterministic validation
- Duplicate protection
- Operation IDs and receipts
FAILURE HANDLING
Uncertainty stays visible
- Reconciliation of external actions
- Explicit UNCERTAIN states
- No blind retry for high-impact actions
The goal is not maximum autonomy at any cost.
The goal is dependable autonomy.05 / REAL OPERATING ENVIRONMENT
Built around a real business.
AMS is being developed around Fintehplus, an operating accounting and business-services company. That means real content, real publication channels, real operational constraints and real commercial context to measure against — not a laboratory-only demo.
Fintehplus website / RSS / VK
Website content surfaces and the RSS-driven VK path are active.
Telegram
Controlled public publication has been exercised in production.
MAX
Controlled public publication has been exercised in production.
Dzen
Publication remains a controlled operator-assisted path.
06 / ARCHITECTURE
Control, reasoning and execution stay separate.
CONTROL
Durable truth
- Workflow state
- Policies and approvals
- Operation identity
- Receipts and reconciliation
REASONING
LLM inside boundaries
- Analysis and classification
- Grounded generation
- Decision support
- Evaluation
EXECUTION
Orchestration and adapters
- n8n workflows
- Triggers and delivery
- Channel-specific execution
- External action receipts
This separation lets models reason without allowing model output itself to become operational truth.
07 / EVOLUTION
From content automation to a marketing operating system.
AMS already has controlled publication paths and durable operational state. The next layer connects audience response, conversations, qualification and business outcomes back into the decision cycle.
The target is a measurable loop in which the system can observe what happened, preserve evidence and improve the next decision — without turning uncertain external outcomes into confident automation.
Response→Conversation→Qualification→Business outcome→Learning↺
RAUNEM / APPLIED AI SYSTEMS