Hardware
Drop-in modules
Pre-certified silicon modules with connectivity built in. Solder them on, flash the firmware, and ship.
AirTrik brings AI agents to your IoT devices and keeps the smart part on the device itself. You get four building blocks: an edge AI module, a protocol that connects devices to agents, a cloud agent runtime, and a white-label app. No AI team required.
It senses what is happening and decides on the device, in milliseconds.
It acts on its own, with no round trip to a server to wait on.
It learns over time. Only the hard problems go up to a cloud agent.
They assume the cloud does the thinking. That was fine when a device only had to report data. It falls apart when you want the device to sense, decide, and act on its own.
When every decision travels to a server and back, you wait 200 milliseconds or more before anything happens. That is too slow for a device that has to react in real time.
Cloud-first designs collect sensitive data in one place. Newer data rules, and a lot of customers, would rather it stayed on the device.
Expiring keys, deprecated local APIs, and restrictive licenses turn a hardware project into a subscription you cannot leave.
Each part is useful on its own. Used together, they take a device from raw sensor readings to something a person can talk to.
Every device runs the same loop. It senses what is happening, decides what to do, acts, and remembers the result.
The on-device NPU reads its sensors continuously: voltage, temperature, motion, sound. That builds a live picture of what is happening around it.
A small model on the device, or a larger one in the cloud, looks at that picture, spots patterns, and plans what to do next.
The agent carries out physical actions, like adjusting a thermostat or cutting power to a circuit, through MCP tool calls over MQTT.
The system remembers what happened. Over weeks it picks up a home's patterns and starts acting before it is asked.
The edge AI module comes in two tiers. Pick the one that fits the product. Both run models on the device; they differ in how much they can take on.
For bulbs, plugs, switches, and simple sensors. Low power, low cost, with enough room for TinyML.
For hubs, energy gateways, and higher-end appliances. Enough headroom to run a small language model on the device.
When software can switch a relay or unlock a door, a wrong or hijacked instruction has physical consequences. We plan for that from the start.
Instruction hierarchies and scoped boundaries keep a crafted prompt from talking the agent past its safety limits.
Hardware-backed X.509 certificates mean only an authorized agent can trigger a physical action.
Disabling a security system or pushing firmware needs explicit sign-off before it runs.
Everything needed to ship an AI-enabled product without standing up an AI team of your own.
Pre-certified silicon modules with connectivity built in. Solder them on, flash the firmware, and ship.
Set colors, logo, voice, and the metrics you care about in a portal, then publish to the app stores.
Live monitoring, energy insight, maintenance alerts, and device health across your whole product line.
Edge voltage monitoring rides out wide grid swings and can cut power before a surge damages an appliance.
Produced in the Noida and Ghaziabad clusters, with local manufacturing partners to scale.
Because devices speak MCP, they work with Home Assistant and other orchestrators. No vendor lock-in.
Official SDKs for Node.js, Python, React, and Arduino, with documentation to match.
npm i airtrik
pip install airtrik
npm i airtrik-react
airtrik-arduino
We will walk you through the parts that fit your product, from the on-device AI to the app, and where to start.