Get Started with mimilabs
Ready to dive into data? Let's get you set up in 3 simple steps.
Step 1: Meet mimibot 🤖
Your AI data companion is waiting
Get mimibot's power wherever you work:
- Web: Visit mimilabs.ai/mimibot
- Slack: Type
@mimibot-v2
in our community (most powerful version - exclusive to members!) - Your favorite AI app: Use our MCP endpoint in Claude Desktop, Cursor, and more
mimibot isn't just a chatbot—it's your personal data scientist, SQL wizard, and research assistant all rolled into one.
Try it now: Ask mimibot anything about our datasets, request SQL queries, or get live healthcare data analysis. It's like having a data expert on speed dial.
Step 2: Join the Slack Community 💬
Where data nerds unite
Sign up and you'll get a Slack invite within minutes. Our community is where insights are shared, questions get answered, and data discoveries come to life. Plus, mimibot lives here too—ready to help 24/7.
Step 3: Get Your Hands Dirty 🔥
Jump straight into our data playground
No lengthy tutorials. No complex setup. Just pure data exploration powered by Databricks. Query with SQL, Python, or R. Export what you need. Build what you want.
Why mimibot Changes Everything
✨ Healthcare insights instantly – "Where should I build my next clinic?"
✨ Benchmark rates on demand – "Show me Medicare rates for CPT code 99213"
✨ Population health analysis – "Analyze diabetes trends by county"
✨ Social determinants research – "How does ADI correlate with readmission rates?"
✨ Works everywhere – Web, Slack, Claude Desktop, Cursor
✨ 24/7 availability – Never stuck, never alone
Ready to Start?
- Sign up → Get Slack invite
- Choose your mimibot experience:
- Web interface for full features
@mimibot-v2
in Slack for the most powerful version (members only!)- MCP setup for Claude Desktop/Cursor
- Start exploring → Build amazing things
Questions? mimibot has answers. Stuck? Our Slack community has your back. Excited? We are too.
Welcome to the future of data exploration. Welcome to mimilabs.
Resources
Data Engineering
Learn about how we downloaded and ingested thousands of public datasets into our data lakehouse.