Tile

What do they actually do

Tile is an AI-assisted analytics notebook for building operational data apps. It lets teams explore data in modular steps using visual or low-code tiles and then convert that work into SQL blocks, so analyses can be hardened into reports and lightweight apps without getting stuck in a proprietary format. The product emphasizes explainability by showing step-by-step transformations and supports creating production-grade data automations and applications without heavy coding source.

Today, Tile offers a self-serve product with a free 14-day trial to use it on your own data. The company is actively running demos and hands-on onboarding with early users while iterating on the product source.

Who are their target customer(s)

• Data analysts at mid-market companies (SQL-proficient, limited engineering support): Exploratory work in SQL is verbose and brittle; moving from exploration to shareable reports/apps requires manual rework and handoffs to BI or engineering.
• Operations leaders who own recurring metrics and workflows (RevOps, Supply Chain, CX): Dashboards are static and slow to change; ad-hoc questions still require analysts to pull data, and small operational apps often stall due to lack of developer time.
• Analytics engineers/BI developers in the modern data stack: Tooling is fragmented between notebooks, BI, and orchestration; iterating quickly while keeping everything in SQL and production-ready is cumbersome.
• Founders/ops leads at early-stage startups with a warehouse: They need usable reports and lightweight data apps fast, without standing up a full BI stack or writing a lot of custom code.
• Analytics consultancies and data/BI integrators: They need to prototype, iterate, and deliver operational analytics for clients quickly while handing off maintainable artifacts that clients can own.

How would they acquire their first 10, 50, and 100 customers

• First 10: Founder-led pilots via Palantir/analytics networks: run 1–2 week hands-on pilots loading each customer’s data, build one operational report, train core users, and convert with a measured workflow improvement and testimonial source.
• First 50: Targeted PLG + case studies: expand to YC startups and analytics/ops teams with free trials and templated onboarding, run weekly public demos and 1:1 office hours, and publish 3 short case studies to improve trial-to-paid conversion source.
• First 100: Partnerships, marketplaces, first sales hire: lean into channels with best pilot conversion (analytics consultancies, BI integrators, accelerators), list where data teams discover tools, and hire a sales engineer to run paid pilots and standardize onboarding playbooks source.

What is the rough total addressable market

Top-down context:

The Analytics & BI software market was about $20.3B in 2024 and is projected to reach $28.5B by 2029, while the broader data and analytics software market reached ~$175B in 2024, framing the upper bound for adjacent spend Apps Run the World Gartner.

Bottom-up calculation:

Focus on data-mature organizations using modern warehouses and BI: assume ~60,000 target orgs globally with active data teams, each averaging ~$12k ARR for an AI-first notebook that converts exploration into operational reports/apps, implying roughly $720M in bottom-up TAM.

Assumptions:

• Targetable orgs are limited to those with an existing warehouse/BI and at least a small analytics team (~60k globally).
• Average contract assumes ~10 editor seats at ~$100/month or equivalent mix of seats/features.
• Scope is the wedge of Analytics/BI spend addressable by an AI-first notebook that produces operational reports/apps, not the full BI suite.

Who are some of their notable competitors

• Hex: Collaborative notebook for data teams that turns analyses into interactive apps with SQL/Python and UI components—close overlap on notebook-to-app workflows.
• Mode: SQL-first BI and notebooks with sharing and visualization; widely used for exploratory analysis and report building that can serve operational needs.
• Deepnote: Collaborative notebooks for data exploration and sharing; targets fast iteration and teamwork with SQL/Python and app-like outputs.
• Evidence: SQL-based reporting framework that compiles to production-grade reports and sites, appealing to teams that want SQL-backed, versioned operational reporting.
• Retool: Internal app builder that connects to databases and APIs to create operational tools and dashboards—often used to stand up the kinds of simple data apps Tile targets.