You will get a production-ready Firmware with TinyML integration
Project details
Turn your standard microcontroller into an intelligent edge device.
We are a team with Embedded Systems Engineers and AI Engineers specializing in TinyML and high-performance firmware. Unlike standard firmware developers who simply write logic loops, I implement intelligent decision-making directly on the hardware using Edge Impulse and TensorFlow Lite for Microcontrollers.
What We Deliver:
Optimized C++ Firmware: We write clean, non-blocking code that integrates seamlessly with your existing RTOS or bare-metal setup.
Real-Time Inference: We optimize models for latency and power consumption, ensuring your battery-powered devices last longer.
Hardware Expertise: Our primary focus is on STM32 (ARM Cortex-M) and ESP32 ecosystems, but we can adapt to nRF52 and RP2040.
Why Work With Us?
Our background involves rigorous research in motor control and embedded systems at a top-tier university level. We don't just "make it work"; We engineer it to be robust, scalable, and ready for deployment. Whether you need predictive maintenance, gesture recognition, or audio classification, We can fit the AI into your chip constraints.
We are a team with Embedded Systems Engineers and AI Engineers specializing in TinyML and high-performance firmware. Unlike standard firmware developers who simply write logic loops, I implement intelligent decision-making directly on the hardware using Edge Impulse and TensorFlow Lite for Microcontrollers.
What We Deliver:
Optimized C++ Firmware: We write clean, non-blocking code that integrates seamlessly with your existing RTOS or bare-metal setup.
Real-Time Inference: We optimize models for latency and power consumption, ensuring your battery-powered devices last longer.
Hardware Expertise: Our primary focus is on STM32 (ARM Cortex-M) and ESP32 ecosystems, but we can adapt to nRF52 and RP2040.
Why Work With Us?
Our background involves rigorous research in motor control and embedded systems at a top-tier university level. We don't just "make it work"; We engineer it to be robust, scalable, and ready for deployment. Whether you need predictive maintenance, gesture recognition, or audio classification, We can fit the AI into your chip constraints.
AI Development Type
Model Tuning, Software MaintenanceAI Tools
MATLAB, PyTorch, TensorFlowAI Development Language
C++What's included
| Service Tiers |
Starter
$30
|
Standard
$150
|
Advanced
$450
|
|---|---|---|---|
| Delivery Time | 2 days | 7 days | 14 days |
Number of Revisions | 0 | 2 | 3 |
AI Model Integration | |||
Detailed Code Comments | - | ||
Knowledge Graph | - | - | - |
Model Documentation | - | - | |
Ontology | - | - | - |
Source Code | - | ||
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$50 - $200
Additional Revision
+$20Frequently asked questions
About Rajinthan
R&D Engineer | Hardware Prototyping & Industrial Automation
West Coast Village, Singapore - 6:34 pm local time
The Problem:
You have a great idea for a smart device, but you're stuck. Maybe your current firmware crashes, your battery dies too fast, or you need to fit complex AI onto a $5 chip. You don't just need a "coder"; you need an engineering partner who understands physics, electronics, and software.
The Solution:
I am a Systems Architect based in Singapore, leading a specialized engineering team (WX) focused on Edge AI and Industrial IoT. We bridge the gap between "dumb" hardware and modern AI.
Unlike generic freelancers who only write code, we handle the full stack:
*Hardware Design: Custom PCBs (Altium/KiCad) optimized for size and power.
*Firmware: RTOS-based C/C++ (ESP32, STM32, nRF52) that is crash-proof.
*Edge AI: Running Neural Networks locally on the chip (TinyML) for voice/vibration analysis without cloud costs.
Why Clients Trust Us:
*Deep Tech Specialists: My team includes dedicated experts in FPGA (Verilog), Analog Circuit Design, and Computer Vision. We don't guess; we calculate.
*Rapid Prototyping: We move from "Napkin Sketch" to "Working Prototype" in weeks, not months.
Core Tech Stack:
*MCU: ESP32, STM32, Nordic nRF52, Raspberry Pi.
*AI/ML: TensorFlow Lite Micro, Edge Impulse, PyTorch.
*FPGA: Xilinx, Verilog/VHDL, High-Speed Verification.
*Design: Altium Designer, KiCad, Fusion360.
Recent Project:
Smart Satellite Component: High-torque BLDC motor controller for reaction wheels.
Stop wasting time with freelancers who can't read a schematic. Let's build something production-ready.
Click "Invite" to discuss your project.
Steps for completing your project
After purchasing the project, send requirements so Rajinthan can start the project.
Delivery time starts when Rajinthan receives requirements from you.
Rajinthan works on your project following the steps below.
Revisions may occur after the delivery date.
Feasibility & Data Review
We analyze your hardware specs and sensor data to confirm the specific TinyML model will run effectively within your device's memory constraints.
Model Training & Optimization
We preprocess your data, train the neural network (using Edge Impulse or TensorFlow Lite), and optimize it to balance accuracy vs. latency.