TL;DR

We are a shared source of truth for data teams living in the data warehouse.

Why is it that your “daily active users” never add up to the same number in different reports? Your data team is amazing, but it’s a struggle to keep all metrics synchronized. There is no single place that enables a shared workflow and truth.

Have you ever seen a screw-up like:

1. Presenting wrong numbers in an exec meeting 🤦‍♂️
2. Not being able to understand how a KPI such as Daily Active Users, Churn or ARR was built 😡
3. Spending all your time on preparing and transforming data instead of producing insights on top of it 😫
4. Making a change to a KPI calculation and breaking the CEOs favorite dashboard 🙀

We fix this! Honeydew helps the data team organize analytics into manageable blocks of knowledge supporting every data flow. Users can consume them in SQL, Tableau, Looker, Python, or dbt.

Our product is being used by multiple early adopters - unicorn companies in cyber, insurance tech, and cloud ops.

We (Baruch, Liron and David) always want to talk, at founders@honeydew.ai; or just grab a time if you ever felt or feel the data mess pain.

Would you like to know more?

💡 How does it work?

We connect to Snowflake and act as a layer on top of it for different data tools.

(we don’t need to access your data, and yes - we are SOC2-compliant)

Then,

1. Map the source data and relations (we can map it automatically for you 😎)
2. Create reusable pieces of logic like what is a User, what is Active, what is Daily
3. Create a workflow around it, that helps the team to control changes
4. Connect any tool, it will use the same logic ✌️: Tableau, Looker, dbt, Python or SQL
5. Under the hood: we’ll will build the needed data pipeline on the fly and then maintain it to reflect the current truth.

https://www.youtube.com/watch?v=gSfIU-FOfW4

🏗️ Why did we build this?

All three of us encountered and solved this problem in our previous roles.

Liron founded a company that turned fashion consumer behavior data into real-time (yes, the numbers always lie 🤥 ). Baruch built AI products on sales data in Salesforce (yes, the numbers lie even with AI 🤥 ). David founded a company that built data lake acceleration (we calculated everything right, the questions lied 🤥 ).

So far we talked with over 300 analytics teams. They were all busy trying to get consistent data their stakeholders can trust. The surprising thing is that there is a gap that nobody is filling at the moment - this gap was covered before BI like Looker, and even before with likes of SAP Business Object. We fill this gap.

👩‍💻 Why do customers want to use Honeydew?

• “I struggle to keep logic in Looker and in the warehouse the same. I want to build it once”
• “I am building a new data team, and I don’t want to end up with another dbt spaghetti”
• “We have every tool in the modern data stack, and yet our KPIs calculations end up being managed in a wiki, reimplemented in ETL and dashboards. This does not make any sense”

🙏 Our ask

• Does your company have a data team? We would love to talk to them!
• Does your company plan to have a data team? We would love to talk to you!
• Do you like to talk about data in general? We also do, any time 😀

🍈 Our deal

• Sign up before demo day, and we do all the onboarding for you, free of charge

Love - team Honeydew

Find us at founders@honeydew.ai; or just grab a time