About Doctor Droid

Doctor Droid is an AI-assisted Site Reliability Engineering (SRE) platform that automates incident investigations by querying data from your observability tools. It reduces Mean Time To Investigate by 85% and enhances on-call developer efficiency by 6.5 times, minimizing escalations and ticket re-assignments.

```xml <problem> Modern IT environments generate a high volume of alerts from various observability tools, overwhelming on-call engineers and leading to delayed incident resolution. Investigating these alerts requires manually querying data across multiple systems, resulting in prolonged mean time to investigate (MTTI) and increased operational costs. This complexity often leads to escalations and ticket reassignments, further hindering efficiency. </problem> <solution> Doctor Droid is an AI-assisted Site Reliability Engineering (SRE) platform designed to automate incident investigations and accelerate remediation. The platform integrates with existing observability tools, leveraging AI to analyze alerts and surface relevant data for faster root cause identification. By automating the data querying process, Doctor Droid significantly reduces MTTI, enhances on-call developer efficiency, and minimizes escalations. The platform is trained on an organization's specific context to provide accurate and actionable insights. </solution> <features> - Automated querying of data from observability tools in response to alerts - AI-driven root cause analysis and identification of remediation steps - Customizable runbooks for automated execution of common troubleshooting tasks - Alert analytics to identify and reduce alert fatigue - Integration with Slack for real-time notifications and collaboration - Single pane of glass for managing and triaging alerts from multiple sources - Automated postmortems and RCAs </features> <target_audience> The primary target audience includes Site Reliability Engineers (SREs), DevOps engineers, and platform engineers responsible for maintaining the reliability and performance of complex IT systems. </target_audience> ```

What does Doctor Droid do?

Where is Doctor Droid located?

Doctor Droid is based in San Francisco, United States.

When was Doctor Droid founded?

Doctor Droid was founded in 2022.

How much funding has Doctor Droid raised?

Doctor Droid has raised 500000.

Location

San Francisco, United States

Founded

2022

Funding

500000

Employees

7 employees

Major Investors

Y Combinator, Accel

Find Investable Startups and Competitors

Search thousands of startups using natural language

AI voice (2021+)underground pipe robots energy flexibility software

Start Searching

Doctor Droid

⚠️ AI-generated overview based on web search data – may contain errors, please verify information yourself! You can claim this account with your email domain to make edits.

Executive Summary

drdroid.io 2K+

Crunchbase

Founded 2022 – San Francisco, United States

Funding

Estimated Funding

$500K+

Major Investors

Y Combinator, Accel

Team (5+)

No team information available.

Company Description

Problem

Modern IT environments generate a high volume of alerts from various observability tools, overwhelming on-call engineers and leading to delayed incident resolution. Investigating these alerts requires manually querying data across multiple systems, resulting in prolonged mean time to investigate (MTTI) and increased operational costs. This complexity often leads to escalations and ticket reassignments, further hindering efficiency.

Solution

Doctor Droid is an AI-assisted Site Reliability Engineering (SRE) platform designed to automate incident investigations and accelerate remediation. The platform integrates with existing observability tools, leveraging AI to analyze alerts and surface relevant data for faster root cause identification. By automating the data querying process, Doctor Droid significantly reduces MTTI, enhances on-call developer efficiency, and minimizes escalations. The platform is trained on an organization's specific context to provide accurate and actionable insights.

Features

Automated querying of data from observability tools in response to alerts

AI-driven root cause analysis and identification of remediation steps

Customizable runbooks for automated execution of common troubleshooting tasks

Alert analytics to identify and reduce alert fatigue

Integration with Slack for real-time notifications and collaboration

Single pane of glass for managing and triaging alerts from multiple sources

Automated postmortems and RCAs

Target Audience

The primary target audience includes Site Reliability Engineers (SREs), DevOps engineers, and platform engineers responsible for maintaining the reliability and performance of complex IT systems.