Tile

Tile is an AI-first SQL notebook for building stunning data apps. It allows anyone to explore and investigate their data in modularized steps without the clunky syntax of SQL. Once the insight is found, users can convert their tiles to a SQL block to have the robustness of code when building reports to share this insight with others.

What the company does (products/services)

Tile provides a notebook with visual, low-code, and SQL tiles. Every tile compiles to SQL, so users' work will never get locked in. The platform allows users to explore and investigate their data in modularized steps without the clunky syntax of SQL. Once an insight is found, users can convert their tiles to a SQL block to have the robustness of code when building reports to share this insight with others.

Technology stack and engineering culture

As a YC-backed startup, Tile likely uses a modern tech stack. While specific details are not public, it is reasonable to assume they use a combination of popular web technologies such as React for the frontend, a Python backend for their data processing and AI features, and a cloud provider like AWS for infrastructure. The engineering culture is likely focused on building a powerful and intuitive data analysis tool.

Work environment and benefits

Tile is a small, early-stage startup with a team of 2. The work environment is likely collaborative and hands-on, with a strong emphasis on teamwork and communication. As a YC company, they offer equity as part of their compensation package.

Why someone should work there

Working at Tile offers a unique opportunity to join an early-stage startup and have a significant impact on the company's growth and direction. Employees will have the chance to work on a product that is disrupting the data analytics industry. The company is backed by Y Combinator, which provides a strong network and resources for growth.

Key roles they typically hire for

Tile is not currently hiring. As the company grows, they will likely hire for roles in software engineering, data science, and product management.