The problem DarkFlow solves

Our MLOps platform addresses the complexities of machine learning workflows, making it easier for users to build, deploy, and manage models without extensive technical expertise. Traditional platforms often have steep learning curves, but our enhanced user interface and simplified user layers allow anyone, regardless of coding experience, to navigate the system effortlessly.

Dataset querying can be a significant challenge, but our platform features dynamic querying capabilities that enable users to analyze datasets directly, leading to better insights before model deployment. This empowers users to make informed decisions based on a comprehensive understanding of their data.

Accessing trained models can be cumbersome in existing solutions. Our integration with AWS APIs streamlines model retrieval, enhancing collaboration and efficiency within teams.

Key differentiators include our entirely custom-built platform, offering flexibility without reliance on external MLOps APIs. Additionally, our low-code, no-code interface democratizes model management, allowing users with minimal coding skills to effectively interact with the system.

Ultimately, our automated end-to-end solution covers the entire machine learning lifecycle—from data preparation to deployment—ensuring a seamless experience that enhances productivity and safety for users at every step.

Challenges we ran into

1. Integration of diverse techstack in frontend and backend.
2. Storage over AWS Bucket.
3. Current development of the RAG tool to query dataset.
4. Visualization of Graphs from frontend just based on numeric data from backend.