IoT · Industrial Automation · Edge AI

We automate
what matters.

From sensor to cloud. From legacy hardware to real-time intelligence.
We design, build, and deploy complete automation systems
that work in the field — not just in demos.

See Our Work Get in Touch
0+ Systems Deployed
0 Industries Served
0% Hardware to Cloud
// what we do

Full-stack automation.
Not just a piece of the puzzle.

Most companies do firmware OR cloud OR dashboards. We do the entire vertical — and we own every layer.

Embedded Systems

Custom firmware on ESP32, nRF52, STM32. Sensor integration, motor control, wireless protocols. Production-grade, not prototype-grade.

ESP-IDFArduinoBLELTEModbus

Cloud & IoT Infrastructure

AWS IoT Core, Lambda, DynamoDB, AppSync. Multi-tenant architectures with real-time data pipelines. Infrastructure as code, not click-ops.

AWS IoTMQTTCDKGraphQLDynamoDB

Dashboards & Interfaces

Real-time monitoring UIs that operators actually use. Live data, historical trending, fleet views. React, Next.js, deployed fast.

ReactNext.jsTypeScriptWebSocket

Edge AI & Vision

TensorFlow Lite models running on microcontrollers. Sub-200ms inference. On-device intelligence where cloud latency isn't an option.

TFLiteESP32-S3Computer VisionINT8
// how we work

Sensor to dashboard.
One team. One pipeline.

01

Discover

Understand the physical system, the constraints, the data that matters. We visit the site, read the datasheets, map the signals.

02

Design

Hardware selection, communication architecture, cloud topology. We spec everything before writing a single line of code.

03

Build

Firmware, cloud backend, and frontend developed in parallel. Phased delivery so you see progress early and often.

04

Deploy

Field installation, validation, monitoring. We don't hand off a ZIP file — we deploy, verify, and support the system in production.

// selected work

Real systems solving
real problems.

These aren't demos. These are deployed systems handling live data in production environments.

01
Energy · HVAC SaaS Platform + Hardware Integration

EnerCo — Industrial Chiller Monitoring

A 320-ton Carrier chiller system was being monitored with manual readings and spreadsheets. Energy waste was invisible. Maintenance was reactive.

We built a multi-tenant SaaS platform that ingests data from Modbus power meters, LoRaWAN sensors, and flow meters in real-time. The system calculates Energy Efficiency Ratio using ASHRAE psychrometric formulas and surfaces it on live dashboards with 1/7/30-day trending.

Real-time EER Thermodynamic efficiency calculated live from 6+ sensor types
Auto-detection Unified ingestion pipeline normalizes fragmented MQTT payloads from any device type
Multi-tenant One platform serves multiple facilities with isolated data and access control
AWS IoT CoreLambdaDynamoDBAppSyncNext.jsModbusLoRaWANMQTT 
// Live sensor ingestion
topic: enerco/sensors/chiller-01
payload: {
  "supply_temp": 7.2,
  "return_temp": 12.8,
  "flow_rate": 45.3,
  "power_kw": 89.4,
  "eer": 14.2
}
// → Dashboard updated in 10s
02
Retail · Fleet Management Full-Stack IoT Platform

VendBnB — Smart Vending Fleet Platform

Traditional vending machines are black boxes. Operators drive routes to check stock levels. Downtime goes unnoticed for days. Revenue leaks through stale inventory and broken units.

We built the entire stack: custom ESP32 firmware that reports inventory, health, and transactions over MQTT — a serverless AWS backend that processes events in real-time — and an admin dashboard where operators manage their entire fleet from one screen. Stripe-integrated payments, WiFi provisioning, and a device simulator for testing without hardware.

Legacy to Connected Dumb vending machines became real-time reporting IoT devices
Full Stack Ownership Firmware + AWS CDK infrastructure + React dashboard + Stripe payments
Fleet Intelligence Live monitoring, predictive restocking, and revenue tracking across all machines
ESP32AWS CDKIoT CoreLambdaDynamoDBReactStripeMQTT 
// Fleet status — real-time
machines_online: 47 / 52
alerts: [
  { "id": "VM-031", "type": "low_stock" },
  { "id": "VM-009", "type": "offline" }
]
revenue_today: $1,247.80
// → Operator dispatched in 12min
03
Agriculture · Smart Farming Embedded IoT + Autonomous Control

AutoGrow — Autonomous Hydroponic Station

Hydroponic farms require constant monitoring of pH, electrical conductivity, and nutrient levels. Manual dosing is error-prone and doesn't scale. A pH swing of 0.5 can kill a crop overnight.

We designed a fully autonomous growing station that reads sensors in real-time, calculates dosing requirements, and operates pumps with built-in safety limits. The system runs its own web server for local control, syncs to the cloud via MQTT, and displays live readings on an onboard OLED — all on a single ESP32.

Autonomous Dosing pH and EC corrections with max-dose limits, post-dose wait, and safety cutoffs
Self-Contained Web UI, OLED display, cloud sync, and calibration — all on one microcontroller
Field-Proven Runs 24/7 with watchdog timers, sensor timeouts, and graceful error recovery
ESP32DS18B20pH ProbeEC ProbeMQTTLittleFSAsyncWebServer 
// AutoGrow — live readings
water_temp:  22.4°C
pH:         5.92  ✓ (target: 5.8-6.2)
EC:         1.84 mS/cm
dose_pump:  standby
uptime:     14d 7h 32m
// → Next check in 30s
04
Remote Monitoring · Vision LTE Camera System

AirCam — LTE-Connected Vision System

Remote sites need eyes on the ground — but WiFi doesn't reach, power is limited, and cellular bandwidth is expensive. Existing solutions are either too dumb (basic IP cameras) or too heavy (full edge servers).

We built a compact vision unit on ESP32-S3 with a 5MP OV5640 camera and SIM7670G LTE modem. The firmware chunks 80KB+ images into MQTT packets for reliable transmission over cellular, with circuit breaker retry logic and dual-mode connectivity (LTE in the field, WiFi in the office). A hardware simulation mode lets us develop and test without physical cameras.

Cellular-First Full LTE Cat-1 connectivity via SIM7670G with automatic failover to WiFi
Chunked Transport Large images transmitted reliably over constrained MQTT without buffer overflows
Field-Ready Circuit breaker patterns, exponential backoff, and simulation mode for zero-hardware testing
ESP32-S3ESP-IDFOV5640SIM7670GLTEMQTTC 
// AirCam — capture + transmit
mode:       LTE (SIM7670G)
resolution: 2592x1944 (5MP)
jpeg_size:  82,441 bytes
chunks:    17 / 17  ✓
latency:   3.2s
signal:    -71 dBm (good)
// → Cloud received, stored to S3
// our stack

Built on what works.
Not what's trending.

Hardware

  • ESP32 / ESP32-S3
  • nRF52832 (Nordic)
  • STM32U5
  • SIM7670G (LTE)
  • OV5640 (Vision)

Protocols

  • MQTT
  • Modbus RTU/TCP
  • BLE 5.0
  • LTE Cat-1
  • LoRaWAN

Cloud

  • AWS IoT Core
  • Lambda + CDK
  • DynamoDB
  • AppSync (GraphQL)
  • Cognito + S3

Software

  • React / Next.js
  • TypeScript
  • ESP-IDF / Arduino
  • TensorFlow Lite
  • Node.js
// the team

Three engineers.
Zero handoffs.

We're small by design. Every project gets senior-level attention from start to deployment. No account managers, no outsourced layers — you talk to the people building your system.

MS

Muhammad Sufian

Co-Founder

Embedded systems and firmware architecture. Designs the hardware-software interface and owns the device layer — from sensor wiring to production firmware.

AM

Ahmed Mohi U Din

Co-Founder

Cloud infrastructure and backend systems. Architects the AWS pipelines, data models, and APIs that turn raw device data into actionable intelligence.

MA

Muhammad Bin Asif

Co-Founder

Frontend, integrations, and system delivery. Builds the dashboards and interfaces operators use daily, and ensures everything works end-to-end in production.

// let's talk

Have a system that needs
to get smarter?

Whether you're modernizing legacy equipment, building a new IoT product, or need a team that can go from schematic to cloud — we should talk.

soviotechsolutions@gmail.com
Based in Pakistan · Working globally