Agnidyne — Precision Edge Intelligence

What We Do

Six core practices.
One senior-led team.

Embedded Systems · Edge Software & Linux BSP · Edge AI/ML · Hardware Validation · IoT & Connectivity · Signal Processing & FPGA — the full embedded and edge stack, delivered as an extension of your team or as a dedicated partner.

Embedded Systems Engineering

Bare-metal and RTOS firmware across ARM Cortex-M/A, STM32, NXP, and custom SoC platforms. Safety-critical design for real-world industrial and field environments.

ARM Cortex-M/A STM32 / NXP FreeRTOS / Zephyr CAN / RS-485 UART / SPI / I2C IEC 62061 aware

Edge Software & Linux BSP

Linux BSP development, device drivers, GStreamer pipelines, Qt/GTK UI, and multi-camera video processing — for hardened embedded Linux platforms deployed in demanding environments.

Embedded Linux Yocto / Buildroot GStreamer / OpenCV GMSL / FPD-Link Qt / GTK+ FPGA VHDL

Edge AI & ML Solutions

Inference on NVIDIA Jetson, TensorRT, and TinyML on microcontrollers. Object detection, classification, and signal-based inference on edge hardware — AI deployed where cloud connectivity isn't guaranteed.

NVIDIA Jetson TensorRT DeepStream TinyML ONNX Runtime

Hardware Validation & Test Automation

End-to-end automated board validation frameworks — from prototype to production. Every unit tested, firmware provisioned, and cloud-enrolled before it ships.

ATE / Bed-of-Nails CAN / BLE / RS-485 TLS Provisioning Cloud Audit Trail Python / Pytest

IoT & Cloud Connectivity

4G/5G, LTE-M, BLE, and LoRaWAN connectivity stacks, with cloud IoT integration on AWS, Azure, and custom MQTT brokers. Secure device provisioning and OTA firmware update pipelines.

4G / 5G / LTE-M BLE / LoRaWAN MQTT / CoAP AWS IoT / Azure OTA Updates

Signal Processing & FPGA

FPGA design in VHDL/Verilog for low-latency signal processing, video pipelines, and hardware acceleration. DSP for sensor fusion, audio, and real-time data acquisition.

VHDL / Verilog Xilinx / Intel FPGA OpenGL / GLSL H.264 / H.265 HEVC Pipelines

Case Studies

Capabilities proven
in the field.

These capability overviews reflect real engineering programs our team has contributed to. Request the full document for technical depth, architecture context, and stack details.

Smart City & Transportation

Smart Traffic Management with Edge AI

NVIDIA Jetson-based edge AI inference platform for vehicle detection and traffic analytics. Solar-powered, field-deployable, geography-agnostic architecture — proven on highway intelligence programs. No cloud dependency required in-field.

NVIDIA Jetson TensorRT DeepStream 4G/5G IP67 LiFePO4

Electronics Manufacturing

Automated Board Validation at Production Scale

Custom automated test framework for IoT hardware — every board tested, firmware flashed, and cloud-enrolled before leaving the factory. Engineered to scale from prototype runs to high-volume production lines.

CAN / RS-485 BLE TLS Cloud Audit Qt / GTK+

Surveillance & Critical Infrastructure

Distributed Video Processing for Mission-Critical Systems

Multi-camera, multi-node video processing on hardened Linux — FPGA-accelerated H.264/H.265 pipelines with deterministic latency and zero-copy memory management. Engineered for environments where pipeline failure is operationally unacceptable.

GStreamer OpenCV FPGA VHDL GMSL FPD-Link OpenGL

Building Systems & Industrial IoT

Elevator Controller Firmware & Edge Monitoring

Two-track engagement: safety-certified STM32 controller firmware for OEMs, and a non-invasive edge monitoring module for building operators — edge inference for ride quality analytics and fleet health dashboards via LTE.

STM32 CAN / RS-485 TinyML LTE IEC 62061 aware Cloud IoT

Domain Engagement

Honest about
where we have depth.

We're a firmware engineering firm — not a standards certification body. Our domain engagement model is transparent about readiness: current depth, where we ramp up, and where we engage alongside domain specialists.

Smart Traffic & Edge AI

NVIDIA Jetson, TensorRT, DeepStream. Highway intelligence, fleet aggregators, port & airport systems. Firmware depth exists — no ramp-up required.

Building Automation & Lift Systems

STM32 controller firmware, non-invasive sensing, IEC 62061 safety stacks, LTE cloud monitoring for elevator and BMS applications.

Surveillance & Critical Video

Multi-camera GMSL/FPD-Link pipelines, FPGA-based H.264/H.265 encoding, hardened Linux, zero-copy video architectures for mission-critical deployments.

Hardware Validation & Board Provisioning

End-to-end automated board validation — custom wiring harnesses, GPIO/power/RTC testing, CAN/RS-485/BLE/Wi-Fi protocol coverage, NFS/TFTP firmware loading, TLS certificate injection, and cloud audit trail per unit. Production-scale from prototype to high-volume line. Firmware depth exists — no ramp-up required.

Industrial IoT & Automation

Embedded firmware for PLCs and sensor devices: current depth. SCADA protocols (Modbus, OPC-UA, DNP3): within scope. SCADA platform integration (Ignition, WinCC, InTouch): 4–8 weeks learning budget — engage with this context upfront.

Agriculture & Agritech

Sensor nodes, LoRaWAN connectivity, edge analytics for precision agriculture. 3–6 months to reach full proficiency — active ramp with learning budget.

Energy & Power Systems

Grid-edge controllers, inverter firmware, MPPT algorithms, battery management systems. Standards awareness growing — engage with compliance context.

Consumer Electronics

High-volume embedded firmware, BLE/Wi-Fi stacks, low-power optimization, OTA pipelines. Strong technical base; learning product certification workflows.

Connected Mobility & Fleet

Telematics, CAN bus data loggers, OBD integrations, fleet health monitoring. Automotive-adjacent — ISO 26262 awareness in progress.

Medical & MedTech

Agnidyne provides firmware engineering; we co-engage with a domain specialist for IEC 62304 / FDA 510(k) compliance guidance. Both scope and audit trail are jointly managed.

Aerospace, Defense & UAV/Drones

RTOS firmware, DO-178C awareness, safety-critical embedded design — current capability. UAV/drone firmware: flight controller integration, sensor fusion, telemetry stacks, and edge AI for autonomy are within technical scope. Airworthiness certification (DO-178C, AS9100) and regulatory approval require domain compliance specialist co-engagement. Engage early on standards context.

Automotive (ISO 26262)

Embedded firmware and AUTOSAR layers available; ASIL-B/C certification requires functional safety specialist co-engagement for formal compliance work.

How We Work

Scoped proof-of-concept first.
Scale after validation.

Most engagements start with a scoped proof-of-concept. We handle firmware and sensing modules — a design specialist handles formal standards compliance sign-off.

Discovery Call

We understand your hardware stack, deployment environment, connectivity requirements, and timeline. No NDA required for the first call.

Scoped PoC

A fixed-scope proof-of-concept validates the critical engineering unknowns. You get a working artifact — not a slide deck — before committing to full scope.

Delivery

Iterative delivery with embedded code review, documentation, and test coverage. We integrate with your existing workflows — GitLab, Jira, or your stack.

Handoff & Support

Full source, documentation, and optional support retainer. We can stay on for production ramp, maintenance releases, or next-phase features.

Why Agnidyne

Engineering depth.
No overhead.

Experienced engineers, hired to fit the engagement

We staff engagements with engineers who have relevant domain experience — full-time or contracted as needed. Quality without overhead.
Full stack, from bare metal to cloud

We cover firmware, Linux BSP, edge AI, connectivity, and test automation — so you don't manage four vendors for one product.
Transparent domain positioning

We are explicit about where we have depth and where we don't — and how we engage in the latter. No surprises mid-program.
India HQ, global delivery

Headquartered in Pune/Mumbai — competitive rates without sacrificing engineering quality. Time-zone overlap with EU, ME, and SEA clients.

Technology Fluency

ARM Cortex-M0 through Cortex-A72

NVIDIA Jetson Nano / Orin / AGX

STM32, NXP i.MX, ESP32

FreeRTOS, Zephyr RTOS

Yocto / Buildroot Linux BSP

GStreamer, OpenCV, DeepStream

Xilinx / Intel FPGA (VHDL/Verilog)

AWS IoT, Azure IoT Hub, MQTT

4G / 5G / LTE-M / BLE / LoRaWAN

CAN, RS-485, Modbus, EtherCAT

A Genuine Question Worth Addressing

Can't AI just
do this now?

It is a fair question. AI coding tools are genuinely impressive, and the pace of progress is real. Here is our honest answer.

AI can write code. It cannot take responsibility for it.

In embedded and edge systems, the consequences of firmware failure are physical — a production line stops, a safety system misfires, a field deployment fails at 2am with no cellular fallback. AI tools accelerate our engineers. They do not replace the judgment, accountability, and hands-on hardware experience that embedded work requires. The engineer who debugs your board at 2am, signs off on the firmware, and shows up on your NDA is a person — not a model.

AI cannot hold a soldering iron

Real embedded work involves oscilloscopes, logic analyzers, hardware bring-up, signal integrity debugging, and power rail analysis. A language model produces plausible-looking register configurations. An engineer validates them on actual silicon.

AI cannot be your named vendor

Your procurement, legal, and compliance teams need a counterparty — a company that signs an NDA, accepts liability, carries PI insurance, and can be held accountable if something goes wrong. AI cannot do that.

AI does not know your hardware

LLMs have training cutoffs and no physical context. They have not seen your schematic, your PCB layout, your sensor variant, or your field conditions. Engineers who have spent time with your hardware produce dramatically better firmware than AI generating from generic documentation.

AI accelerates engineers — we use it too

We use AI coding tools in our workflow. They make our engineers faster at boilerplate, documentation, and code review. The judgment layer — architecture decisions, safety tradeoffs, debugging physical failures — remains with the engineer. That is not changing in any near-term horizon that matters for your project.

Regulatory accountability requires humans

ISO 26262, IEC 62304, DO-178C, and similar standards require human engineers to sign traceability documents, participate in reviews, and accept engineering responsibility. No AI tool is a named engineer on a safety case. Compliance always ends with a person's name.

We welcome the question

Any client who asks "why not just use AI?" is thinking clearly about cost and efficiency — which is exactly the mindset we want in an engagement. Ask us this in the first call. We will walk through exactly where AI helps and where it doesn't in your specific project context.

Get in Touch

Start with a
discovery call.

Precision Edge Intelligence · Pune / Mumbai

Tell us about your hardware, your deployment environment, and what you're trying to ship. The first conversation is always free and no-NDA.

contact@agnidyne.io

Pune / Mumbai, Maharashtra, India

IST (UTC+5:30) — overlap with EU, ME & SEA

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Engineering the Intelligent Edge — from silicon to system

Six core practices.One senior-led team.