traffic microprobe, cloud traffic microprobe, cloud native traffic microprobe

Our Insight

if you are an enterprise customer, are you confused by various commercial products and open source projects in the field of security and monitoring? They are not only similar in function, but even similar in structure.

Most of them are front-end probes. Combined with back-end data analysis

platforms, there may be another AI agent now;

Due to the fact that each product or project has some desired features, you may want to deploy multiple probes, but there are too many risks, costs. You may want to deploy multiple servers, but they seem to be similar;

Unfortunately, you don't have a large development team to deal with these products that are not fully compatible with each other, or even open source projects with open source code but no common interface, which is probably the so-called product barriers, data silos, and technical hegemony.

Confusion about the status quo of the industry

We want to change this dilemma. We believe that future security and monitoring products should have a typical three-layer structure, including front-end data collection layer, intermediate data management and analysis layer, and back-end AI algorithm layer. Each layer should have open and universal program interfaces and data structures, allowing everyone to fully utilize the value of data and excellent technology;

Why is this structure like this?

> The narrow, dynamic, and sensitive workload of the front-end cannot accommodate more probes, so only by maximizing the open data structure can the data value of probes be better utilized;

> The middle layer of data management and analysis, or data center, is already mature and powerful, and most security and monitoring products in this layer do not have much essential innovation;

> Although AI agents in the backend have developed rapidly, there are still technical difficulties. Therefore, the industry needs continuous innovation and open capability output to facilitate algorithm training based on data scale.

Our understanding

Goal 1: To provide probe capability providers with open interfaces and universal data for various data analysis platforms; Therefore, we first focus on the traffic data probes that have not yet been fully resolved in the industry, and have released the TiFlow Microprobe, which may be the smallest and best performing in the industry and can provide high-quality data support for many security and monitoring scenarios;

Goal 2: Provide AI agents for general scenarios for mainstream analysis platforms; To this end, in October 2023, we completed an open universal AI agent alpha version for security and operations scenarios, and plan to release a beta version in mid-2024;

Our Position

Ok, that's all. Through our understanding of demand and technological development trends, we can break down product barriers, data silos, and technological hegemony. That's what we want to do.