01
Hardware and programmable runtimes
Controllers, communications and local displays: from BASIC and edge control logic to the Pascal compiler and independent threads in Phoenix Embedded. Project behavior is defined within the platform.
Company Profile — at a glance
Knowledge-Based Co. — Aram Ramz Gostaran (ARG)
ARG Electronics develops an integrated ecosystem for industrial automation and building management systems (BMS), connecting controllers and sensors with industrial IoT, digital twins, AI, machine vision and biometric security. These technologies serve industry, buildings and critical infrastructure. Fully domestic, passive-defense approved and sanction-independent.
20+ yrs
Years in operation
1,000+
Smartification projects
231
Documented key projects
48+
Industries served
First
Iranian face-recognition system
“From one sensor to a smart city” — one shared protocol, one platform, one company.
Full tech stack — in-house & integrated
Controllers & Hardware
BMS & SCADA Platforms
AI — ArgAI
Machine Vision — ArgVision
Biometric Security
Robotics, UAV, AMR
Headline honors & credentials
Patent Registration
Face recognition & identification system — Iran’s first and only, officially patented.
Harsh-Condition Operation
ARG PLC controllers passed the EPIL operating tests for industrial / harsh conditions.
Top Knowledge-Based Product
Top award at the 2nd Innovation Bazaar — Iran’s national showcase for innovative knowledge-based products.
Selected Knowledge-Based Product
Selected at the 5th national unveiling of successful knowledge-based products.
Knowledge-Based (SEMTA)Passive Defense ApprovedSanction-Independent SupplyISO Certified
From hardware design to complete smart systems
ARG is a family of platforms for building smart systems. Hardware engineering, programming languages, data models, control engines and applications connect across industry, energy, infrastructure, agriculture, services and enterprise.
02
A shared model for data and devices
ENID identifies each point, ACV carries its value and state, and Device Catalog turns device-model knowledge into protocol mappings and project points.
03
From logic and learning to user experience
Rules, scenarios, state machines, ML processing, LLM assistants and Digital Twin each have distinct roles. Services and APIs expose them through different products and applications.
Products & direct access
Architecture & connectionsARG automation products and platforms
Explore building management, IoT, digital twin and enterprise software solutions. Each product card brings together its guide, workspace, API and related resources.
19 products & resources · 25 of 25 entry points
ARG ATM
Platform & serviceCapabilities & technology
ARG ATM
Fleet visibility, 3D views, cash and maintenance workflows with an in-terminal XFS agent and environmental controls.
نوکسا
Super appCapabilities & technology
نوکسا
AI-native Life & Business OS — health, finance, education and a full ERP in one installable Persian PWA.
ارائهٔ نوکسا
Full Novexa product presentation with real screenshots, architecture, market and roadmap.
ArgBMS
Platform & serviceCapabilities & technology
ArgBMS
Comprehensive BMS with live dashboards, mobile app and 20 subsystems.
ArgBMS API
412 endpoints covering devices, ACV, energy, alarms and dashboard designer.
ArgIoT
Platform & serviceCapabilities & technology
ArgIoT
Unified sensor, gateway and ENID management with Modbus, SNMP, MQTT, BACnet.
ArgDCIM
Platform & serviceCapabilities & technology
ArgDCIM
Rack monitoring, UPS, cooling, energy and security for data centers on the BMS platform.
ArgAgro
Platform & serviceCapabilities & technology
ArgAgro
Climate, irrigation, fertigation and plant vision with a sci-fi HUD UI.
ArgAI
Platform & serviceCapabilities & technology
ArgAI
Manage providers, prompt templates, chatbot and industrial assistant.
ArgAI API
REST API for LLM, RAG, embeddings and agent orchestration on Java backend.
ARG ERP
Platform & serviceCapabilities & technology
ARG ERP
Sales, purchasing, inventory, finance, projects, production, HR and correspondence on one dataset, with virtual AI employees.
ARG ERP API
30+ sub-APIs covering HR, CRM, Sales, Accounting, AI Agents and Workflows.
ArgDevCat
Platform & serviceArgDevCat APILive
Spring Boot Backend + Swagger
API documentationdevcat.argsrv.com/swagger-ui/index.html
Capabilities & technology
ArgDevCat
Centralized catalog of 806+ devices, brands and models with their protocols.
ArgDevCat API
Search & sync API for the catalog, protocols, point templates and schemas.
ArgTwin Designer
Platform & serviceCapabilities & technology
ArgTwin Designer
Define BMS digital-twin types from real Modbus templates, validate, publish versioned types and generate runtime code.
AutoTrade
Platform & serviceCapabilities & technology
AutoTrade
Market analysis and signal management with independent strategy engines, account risk controls, ParsGold Bridge and MetaTrader EA, plus Persian and English catalogs.
ArgTradeAI API
Signal engine, 17+ ML models, backtesting, fundamentals and WebSocket feed for EAs — 340+ endpoints.
ArgTradeFX
Platform & serviceCapabilities & technology
ArgTradeFX
Standalone currency-pair system (EURUSD, GBPUSD, USDJPY, AUDUSD) with its own users and licensing, separate from gold.
ArgCrypto
Platform & serviceCapabilities & technology
ArgCrypto
Binance spot market ingestion, opportunity ranking and signals under a venue-risk policy — analysis only, no order execution.
IBN SINA
Platform & serviceCapabilities & technology
IBN SINA
ARG neural core: Persian voice assistant with LLM, speech recognition/synthesis and hooks into the ecosystem.
ArgFlashLoan
Platform & serviceCapabilities & technology
ArgFlashLoan
Control and monitoring panel for the DeFi flash-loan arbitrage bot — pool state, opportunities and logged executions.
ArgVision API
Platform & serviceCapabilities & technology
ArgVision API
Face recognition (SCRFD + MobileFaceNet), object detection (YOLOv8), liveness and RTSP processing.
ArgMap
Platform & serviceCapabilities & technology
ArgMap
Offline map tile server for industries, airports, metro and security.
ArgDocs
Resources & documentationCapabilities & technology
ArgDocs
47+ industries — documentation, system diagrams, RoI and technical comparison.
ArgBMS.com
Resources & documentationCapabilities & technology
ArgBMS.com
Official site of Aram Ramzgostaran (ARG), a knowledge-based company — services, projects and product showcase.
ARG CONNECTED ECOSYSTEMFrom the physical world
From the physical world
to intelligent experiences.
ARG software, intelligence and hardware each have a clear role. Explore what each system does, where it belongs and how it relates to the rest of the architecture.
One view. The whole structure.
Independent products, shared services and connected devices, with clear boundaries between experience, processing and physical control.
7architecture domains46systems, families & components
How does an observation become a decision and action?
An engineering example using pump-pressure monitoring. Select each stage to see its input, processing and output. Actual paths depend on project equipment and configuration.
Read the deviceDevice / Adapter
- Input
- A pressure-sensor message or device register
- Processing
- The adapter knows the address, data type and protocol format. The raw value is converted using the configured engineering unit and scale.
- Output
- Pressure value, communication state and observation time
Engineering valueProtocol differences stay in the connection layer, while application logic consumes pressure.
Key terms in plain engineering language
- ENID
- Point identity shared by observations, logic and commands.
- ACV
- The system’s point model, holding its value, state and processing information.
- Adapter
- The component that translates reads and writes into a device protocol.
- Runtime
- The environment in which configured logic and programs execute.
- Compiler
- The component that translates source text into a structure the runtime can execute.
- Thread
- An execution path within a program, with its context and execution controls.
- Binding
- A connection from a variable or model property to a particular data point.
- Feature
- A numerical or descriptive input feature consumed by an ML model.
- Prediction / Validation
- A prediction and the process of assessing it against suitable data or outcomes.
- RAG
- Retrieval of relevant knowledge to ground a language-model response.
- Agent
- A workflow that uses a model, context and tools to carry out a task.
- Receipt
- A progress report for a request; its reported stage determines how the result is interpreted.
Intelligence at the heart of ARG systems
Digital Twin combines ML analysis with an LLM assistant, RAG retrieval and project tools; Novexa connects AI to personal and business data and tasks. From on-controller learning and market analysis to knowledge retrieval and domain assistants, each path has its own data, models, tools and outputs, working alongside ENID, logic engines and product services.
Machine Learning
From data to measurable predictions
- 01Data & Features
Timestamped observations, features and input contracts
- 02Training
Fit the model; retain scalers, labels and versions
- 03Prediction
Classify a state or predict a future event
- 04Validation
Walk-forward evaluation and recorded forecast outcomes
- 05Model lifecycle
Evaluate a new model generation for runtime use
The market-analysis backend lifecycle is shown here; PLC learning has its own local lifecycle.
LLM, RAG & Agents
From knowledge and context to answers and actions
- 01Context
The request, user data and task scope
- 02Retrieval / RAG
Retrieve relevant knowledge in RAG-enabled workflows
- 03LLM & Agent
Use context and select tools appropriate to the request
- 04Tools & Services
Call tools through the system’s service and permission boundary
- 05Result & Memory
Return the answer and retain task history or results
Digital Twin’s RAG connects project knowledge to its assistant. EKOS has its own retrieval path; Operator and product assistants consume context in their respective workflows.
What do these technologies do in each system?
Digital Twin + ARG AIML · RAG · LLM · Tools
ML for analysis; LLM and RAG for understanding and action
The twin connects equipment identity, observations, data quality, history and scenes. In one path, ARG AI trains models and analyzes equipment data. In the other, an LLM assistant uses RAG retrieval, conversation memory and project tools to investigate conditions and turn engineering requests into actionable proposals.
- Inputs
Project data and alarms, sensor history and technical documents; training data for the selected model.
- Analysis & reasoning
ML for anomalies, consumption forecasts and maintenance; RAG for catalog, protocol and project-document knowledge; an LLM for multi-step investigation using state, alarm and history tools.
- User outcome
Forecasts and model metrics, explanations grounded in data and knowledge, and proposed project structures, dashboards, 3D scenes, rules and scenarios. Changes pass through the user confirmation workflow.
Example: “Investigate this equipment’s alarms and propose a monitoring dashboard.” The assistant gathers relevant data and knowledge, then presents a creation proposal for approval. In the ML path, equipment history supports numerical analysis; live site-data connections are defined during deployment.
NovexaLLM · Voice · Domain tools
AI assistance for everyday life and business
The assistant uses selected context and account-scoped UDS data. Text and voice connect to domain tools; ERP, IoT and PC bridges carry explicit request-and-result workflows.
- Inputs
Text or voice requests, conversation history and relevant information selected from the user’s account.
- Understanding & tools
An LLM builds answers from domain context and history; the voice workflow turns speech into text and tool commands. Image analysis extracts document or product information.
- User outcome
A personalized answer, recommendation or plan; connected workflows can execute a tool and return the service result to the conversation.
Examples: a spoken command is routed to a registered tool; an invoice image becomes reviewable structured fields; the business assistant uses the connected organization’s ERP context.
Market RegimeML
Market states and transition forecasting
GMM, HMM and supervised model paths analyze market states; XGBoost forecasts transition destinations. Feature contracts, versioned models, walk-forward evaluation and episode tracking connect training to outcome validation.
Price ExhaustionML
Price-move exhaustion
Timestamped features and labels describe market moves. Training and prediction connect to an outcome ledger, preserving the first bar forecast for later evaluation against observed events.
Super AI PLCEdge ML
Learning beside physical I/O
ANOM learns an adaptive signal baseline with EWMA on the MCU and returns a BASIC variable. Warmup, consecutive-event confirmation, save/load and freeze define its local learning lifecycle.
EKOSRAG
Retrievable document and code knowledge
Chunking, embeddings and a vector index combine with lexical search. Hybrid retrieval and RRF provide relevant context with source identity; document and embedding-model changes have an explicit lifecycle.
ARG OperatorLLM / Agent
From engineering request to traceable execution
Prepared context and versioned memory connect to work orders and task-scoped tools. Candidate creation, validation, build, activation and restart have distinct stages, checkpoints and operation history.
ArgAgroAssistant
Agricultural assistance with domain context
Application profiles, crop knowledge and cultivation calendars provide assistant context. Recommendations remain in session history, while cost and revenue calculations support reviewable economic scenarios.
Connecting intelligence to data and control
ENID and ACV carry point identity and state into runtime. Digital Twin connects these observations to equipment, scenes and history. Services, control logic and project adapters define command execution paths and connect analysis to visualization.
Inside the systems: from contract to execution
Smart-system platforms for industry, infrastructure, services and enterprise. Explore identity, local logic, learning, engineering operations and products through their processing and feedback boundaries.
16technical systems29technical diagramsENIDprotocol-independent identityEdge ↔ Backendexplicit processing boundaries
ENID / ACV
Product overviewIdentity & protocol translation
What does this system do in practice?
- What it receives
- A device message with a protocol address, value and communication state.
- What it produces
- An ENID-identified point with value, state and time in the ACV model. The command path uses the same point identity.
- Why the architecture matters
- Logic and dashboards work with “this pump’s pressure”; the adapter handles the device-specific protocol reads and writes.
Technical mechanismENID connects field messages, point models, logic and outputs. Point identity, device identity and command identity remain distinct.
Device data is decoded into ENID and the ACV model. Data consumption, hardware commands and internal value changes are separate paths. Device feedback re-enters ingestion only when a new report arrives; sending a command alone does not confirm execution.
Select a component to inspect its role and connections below. Scroll horizontally to explore the diagram.
Data & stateCommand requestReport / feedbackInternal updateArrowheads show transfer direction; numbers identify components.
Selected component
Incoming device message
A measurement or status report arrives from a device or gateway in the ingress protocol format.
- Input
- Address / channel, value and report metadata
- Output
- Message for ingestion
Connected paths
All 11 connections and contracts
Technical mechanisms and their architectural effect
01Reconstructible point identity
Device serial and local point identity use explicit formatting and local/canonical conversions.
System effect
The same point can be addressed inside a device and across the system.
02Stable discovery identity
Decoder output is copied into a stable identity; category, direction, datatype and port select the point template.
System effect
Reusing a decoder does not replace the identity of an existing point.
03Bidirectional representation
Frame → ENID → ACV → rule → ENID → output frame separates engineering values from wire formats.
System effect
Adding an adapter does not require every consumer to parse a new protocol.
04Command identity beyond point identity
Project-scoped envelopes and idempotency keys bind the requested device, point and value.
System effect
A destination point and a particular change request are tracked separately.
05Staged delivery state
A durable outbox tracks attempts and receipt progress with explicit retry limits.
System effect
Dispatch, device acknowledgement and observed state are distinguishable.
Ecosystem directory & product relationships
01
Architecture map
All components are visible. Select a system to inspect its role and connections.
02
Connections in context
Choose a use case and follow its path.
A building-monitoring path; sensor and gateway compatibility is specified per project.
ARG SensorsARG GatewaysData or events through a compatible interface
ARG GatewaysArgMainBackEndDevice data through compatible project interfaces
ArgMainBackEndArgBMSPoint state and events
03
Explore each system
Role, output and relationships at a glance
46 systems, families & components
Data & eventsCommands & controlDefinitions & design filesCoordination & architecture
Technology Core
ARG System Architecture
Four processing domains, from sensor to dashboard, with distinct local-control, communication and central-processing responsibilities. Project needs determine the deployed layers and protocols.
Control platforms: hardware, languages and logic together
These families provide ways to define behavior on site. Each model’s processor, runtime and interfaces determine how work is divided between controller and backend.
Phoenix Embedded
Pascal · Threads · ENIDEngineering programs compile on the system and execute in separate threads. Typed bindings connect program variables to ENID points, while conditions, expressions and scenarios use the same point model.
Phoenix Micro
3 MCUs · BASIC · ENIDThe three-MCU arrangement separates main processing, RF/RS485 communication and LCD processing. Local BASIC execution with variables, conditions and loops works alongside expressions, limits, scenarios, schedules and timers to define physical I/O behavior.
Super AI PLC
BASIC · Scan · Edge MLBASIC is tokenized on the device. Program context survives execution slices, and changed outputs are applied at defined boundaries. ANOM turns learned signal behavior into a variable the same program can use.
Local control, backend analysis and user visualization are distinct responsibilities. Protocol support, execution location and feedback paths are specified for each project and device model.
Cyan is the telemetry path, amber the command path; both cross the same five columns.
LEVEL 4
Platform & SCADA
Collects, stores, alarms, displays and analyses every site
- Backend · 412+ APIs
- Database & history
- Web app · 2D & 3D dashboards
- Mobile app
- ArgAI · analytics & prediction
WebSocket and REST over TLS · MQTT
LEVEL 3
Phoenix Pro — industrial computer
Control, logic and display on site
- DCS
- Logic & scenarios
- Edge AI
- Local HMI
Ethernet · Modbus TCP · BACnet/IP · OPC-UA
LEVEL 2
Controllers
Sample the I/O and run the control logic locally
- Phoenix Micro · smart controller
- Super PLC · modular PLC
- ABM · building module
RS-485 · Modbus RTU · BACnet MS/TP · KNX · DALI
LEVEL 1
Field & I/O
Sensors, meters and actuators
- DI · digital input
- DO · digital output
- AI · analog input
- AO · analog output
- Relay
Data path
How a value goes up and a command comes down
In this control pattern, ENID connects observations and commands to a point. Direct protocol connections and on-controller logic can keep parts of the path local or shorter.
ENID — the 16-digit address of every point
Every sensor, output, variable, person or protocol point has an ENID. Controllers and the backend share this contract, so a point keeps one name from the field to the dashboard.
1001
Controller serial
Controller 1001
0000–9999
6120
Base type
Chiller
167 types
030
Category
Temperature
501 categories
0
Direction
Input
0 · 1
2
Data type
Double
0–4
001
Port
Point 1
000–999
The record that travels under this address
state10016120030020017.4 °Ctime
The five states of a point
DisabledNormalCautionDangerError
Telemetry — field to screen
A sensor value, all the way to the live dashboard
- 1L1
Measure
A sensor or meter drives an I/O input; protocol devices (Modbus, BACnet, SNMP, KNX, OPC-UA, MQTT) are read through their own mapping.
- 2L2
Sample
The controller reads and scales it and runs the local logic.
- 3L2 → L4
ENID record
Each value is a four-part record: state, ENID, value, time — sent on the controller link or in bulk over HTTP.
- 4L4
Live point, history, alarm
The backend updates that point, writes history and evaluates its conditions and limits.
- 5L4
Live view
The same record is pushed over WebSocket to open dashboards (2D, the 3D twin, mobile) and lands in reports and energy.
Control — screen to field
A command, down to the output and back as a confirmation
- 1L4
Origin
A user on a dashboard, or a scenario with one of four triggers: manual, schedule, rule, or a condition on a point.
- 2L4
Access control
The project key sets the access level; role, permission and time slot are checked and the event is logged.
- 3L4 → L2
Routing by ENID
In the illustrated 16-digit format, the first four ENID digits identify the device serial; the controller link or protocol adapter routes "ENID + value" to its destination.
- 4L2 → L1
Execute
The controller applies it to that port (DO, AO or relay) or to the protocol device.
- 5L1 → L4
Confirm
The next device observation returns as telemetry. Command receipts and observed values are distinct; confirmation of physical effect depends on the device feedback available.
What the backend does with the data
Six processing domains consume points and project context, producing calculated values, state changes, command requests, alarms, consumption reports or access decisions.
Conditions & limits
An expression per point; crossing a limit changes the point state and raises an alarm.
Scenarios
A list of actions triggered manually, on schedule, by rule or by a point condition.
Rules, state machines, scripts
Three logic engines for behaviour beyond a single condition.
Alerts & notifications
Active alarms, operator acknowledgement and notifications.
Energy & tariffs
Meters, readings and tariffs for consumption and cost reports.
Access
Project keys, roles and permissions, access rules and time slots.
Communications
Supported Protocols
Full compatibility with all industrial and building standards
Modbus
RTU / TCP
BACnet
IP / MS/TP
KNX
TP / IP
DALI
-2
MQTT
v5
OPC-UA
IEC 62541
IEC 61850
GOOSE/MMS
SNMP
v2c / v3
DMX512
Art-Net
Dante
AoIP
LoRaWAN
Class A/B/C
NB-IoT
LTE Cat-NB
Why ARG?
Competitive Advantages
Local solutions with international quality at affordable prices
90%
Cost Savings
Lower cost compared to foreign competitors like Siemens and Honeywell
100%
Customization
Full flexibility to adapt to specific requirements of each project
15+
Protocols
Support for all industrial and building protocols
24/7
Support
Expert technical support team with quick response
85B
Intellectual Property
85 billion Tomans registered intellectual property assets
Local
Iranian Made
Designed and manufactured in Iran using world-class knowledge
Standards
Certifications & Standards
ISO 9001
Quality Management
IEC 62443
Industrial Security
CE
European Standard
SIL 2/3
Functional Safety
ATEX
Explosive Environment
ASHRAE
HVAC Standard
LEED
Green Building
GMP
Pharma Production
Contact
Contact Us
Contact us for free consultation and quote