AI-first notebook for building operational data apps
Create production-grade data automations and applications without writing SQL or code
Active Founders
Jenica Zhong
Cofounder and CEO of Tile. She was previously at Palantir for 4 years as a PM on their big data product (Foundry), Tactical Intelligence Targeting Access Node (TITAN), and AI-Assisted Decisions for Defense (Gotham). She majored in math at Harvard specializing in differential topology. She is also a math olympian who still enjoys solving USAMO problems in her free time as well as running marathons and oil painting (national-award winner!).
Jessica Fang
Co-founder and CTO of Tile. Previously at Palantir for 5 years as a Forward Deployed Engineer, she specialized in developing low-latency pipelines, analytical applications, and deployment infrastructure for Palantir's big data product (Foundry). Career highlights: technical lead for Palantir's first FedRAMP deployment, technical lead for Palantir's first secure cloud disaster recovery accreditation. She studied computer science at MIT.
Company Launches
Hi! We’re building Tile.
About Us
Jenica and Jessica have collectively spent 9 years data wrangling at Palantir. We have built AI models and analytics products for both commercial enterprise and defense customers. Before Palantir, Jenica studied Math/CS at Harvard, and Jessica studied CS at MIT.
Problem
1. SQL is verbose and hard to use for exploratory data analysis
Data analysis is an iterative and investigative process. While SQL remains the most powerful language for working with data, SQL syntax results in long code blocks that are unforgiving when trying to quickly explore data.
2. Plain english is good for describing a high level query, but not the right UI for refinement
AI has been an incredible technology for fetching the right general data and columns on a well-defined and metadata-rich semantic layer. However, analysts must write long descriptive sentences to refine the query.
Solution
Tile allows anyone to explore and investigate their data in modularized steps without the clunky syntax of SQL.
Once the insight is found, convert your tiles to a SQL block so you still have the robustness of code when building reports to share this insight with others.
Vision: The future is AI-enabled data analysis and report building. However, for it to work, explainability will be key. Tile will allow AI to show its work with step-by-step tiles and allow end users to fine-tune its responses.
Demo: Learn how Dwight can use Tile to explore Dunder Mifflin’s transactions data
Try Tile with your data
Sign up for a free 14 day trial using Tile with your data! Reach out to jenica@tile.sh for specific questions.
