OpenWeb: Combatting Online Hate Speech and Violence Through Advanced Content Moderation

OpenWeb, a social engagement platform that builds online communities around better conversations, needed a way to scale their expanding data science team’s efforts and show immediate value.

About OpenWeb

OpenWeb is constructing the healthy, social layer of the internet, partnering with publishers and brands to enhance audience relationships and improve online conversations, fostering an internet where content creators of every kind can independently own and thrive with their audience relationships.

Industry

Internet, Social Networks, Publishing, Spam Detection

Use Case

Content discussion moderation

Model Frameworks

Pytorch

People ask me how I managed to deploy so many models while onboarding a new team within a year. My answer is: Qwak.

OpenWeb
<50ms

Real-Time Inference

Centralized

Model Repository

5

New Models Introduced in no time

Challenges

As OpenWeb's data science team expanded, there was a pressing need to demonstrate immediate value to stakeholders. Their challenges included:

  • The team's rapid growth meant they required engineering solutions that enabled them to swiftly move forward without the burdens of server maintenance and infrastructure configurations.
  • Previous solutions tested presented intricate change management and basic configurations that hindered smooth execution.
  • The team had a crucial need for real-time inference responses, necessitating the processing through multiple models in under 50 ms.
  • Instantaneous model deployment was a non-negotiable requirement.

Implementation

Solutions

Seamless Integration: Integration with existing models using Qwak was streamlined and intuitive. By leveraging Qwak’s Python SDK, even data scientists without extensive engineering backgrounds found it effortless to run integrations with just a line of code.

Efficient Inference: When compared to other platforms, such as Sagemaker, Qwak's NLP-based inferences were more user-friendly and efficient. The platform enabled OpenWeb to achieve real-time results while maintaining minimal latency.

Robust Monitoring Capabilities: Qwak's out-of-the-box infrastructure monitoring, coupled with alerting and log features, ensured that OpenWeb's team was promptly notified of any issues. This allowed for rapid troubleshooting and problem resolution.

Comprehensive Analytics: OpenWeb could easily query model data and monitor prediction data, ensuring transparency and performance monitoring.

Exceptional Support from Qwak: Throughout the onboarding phase and transition to production, Qwak's support team provided prompt and invaluable assistance, ensuring a smooth operational transition for OpenWeb.