Davra

What is Davra?

Davra is a full-stack application enablement platform for the industrial Internet of Things (IoT). It provides the tools and technologies to launch intelligent, connected solutions quickly, securely, and at scale.

Davra is a tool in the Platform as a Service category of a tech stack.

Key Features

Application Enablement, Device Management, Unified Data Platform, Anomaly Detection, Data Visualisation, Integrations, AI Agents, Predictive Modeling

Davra Pros & Cons

Pros of Davra

No pros listed yet.

Cons of Davra

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Davra Alternatives & Comparisons

What are some alternatives to Davra?

Amazon IoT

AWS IoT is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. AWS IoT can support billions of devices and trillions of messages, and can process and route those messages to AWS endpoints and to other devices reliably and securely. With AWS IoT, your applications can keep track of and communicate with all your devices, all the time, even when they aren’t connected.

Node-RED

It is a programming tool for wiring together hardware devices, APIs and online services in new and interesting ways.

Azure IoT Hub

Use device-to-cloud telemetry data to understand the state of your devices and define message routes to other Azure services without writing any code. In cloud-to-device messages, reliably send commands and notifications to your connected devices and track message delivery with acknowledgement receipts. Device messages are sent in a durable way to accommodate intermittently connected devices.

Power Virtual Agents

It empowers teams to easily create powerful bots using a guided, no-code graphical interface without the need for data scientists or developers. It addresses many of the major issues with bot building in the industry today. It eliminates the gap between the subject matter experts and the development teams building the bots, and the long latency between teams recognizing an issue and updating the bot to address it. It removes the complexity of exposing teams to the nuances of conversational AI and the need to write complex code. And, it minimizes the IT effort required to deploy and maintain a custom conversational solution.