Doctor Droid is launching a AIOps Platform for Engineering Teams.

What is the Doctor Droid AIOps Platform?

tl;dr The Doctor Droid AIOps Platform builds a knowledge graph using company data to give investigation & remediation recommendations during on-call issues & incidents.

Industry Adoption

Fun Fact: Microsoft claims to be able to predict root cause of an issue with upto ~76% accuracy. Meta claims to have reduced debugging effort by upto 70%.

Currently, we see a few challenges to getting Engineering teams access to advanced Machine Learning & AI techniques:

• Requires company level adoption.
• Gated behind Enterprise contracts & investments from day-0.

Due to this, the only teams with strong AIOps capabilities are Big Techs that are able to build their own AI / ML team focused on engineering productivity from Day-0. (Read about ML innovations for on-call productivity improvement at Microsoft, Meta and Salesforce).

Our vision is to change this and make it easy for teams to make decisions at their team level by giving them value from day-0 without any enterprise wide constraints.

What are the situations where Doctor Droid AIOps Platform will be helpful for Engineering teams?

1. Real time use-cases:

Faster Investigation:

• Automated Investigation of alerts with context of the application (more on it below).
• See correlation map of their topology and get visibility on all components that are failing / failed.

Faster remediation:

• Get recommendations for remediations & fix.