Tl;dr - Rupert is an analytics distribution platform that actually delivers business value from analytics. We are growing and want to make Rupert available for more teams. We raised some money to make it happen.

The Pursuit for Data Driveness

The investment in analytics is not stopping. Executives’ pursuit to make the business better by taking advantage of the endless data they accumulate has accelerated in recent years and reached its peak with the explosion of the “modern data stack".

As analysts, we enjoyed that. Our executives generously funded state-of-the-art tools that helped us build better analytics products – from models through dashboards – and funded more teammates to help us withstand the ever-growing burden of ad-hoc requests, urgent pings about bad data, and endless dashboard iterations.

However, at the end of the day, we don’t feel like we’ve arrived at the promised land: a data-driven organization where we are truly realizing the impact of our analytics products on our business stakeholders and outcomes.

This is no surprise. Even with innovations in data processing, metric layers, and visualizations - business teams (e.g. go-to-market, operations, product, etc) are overwhelmed with hitting targets, solving strategic problems, building products, and putting out fires. This leaves them little time to go the last mile of becoming data-driven. The gap has narrowed, but a sequence of problems keeps stakeholders from getting over the hump:

  1. It’s hard to know when analytics can help - business users have dozens of tasks to complete and decisions to make. Thinking of looking for data that might be helpful is not in most people’s nature. Not to mention looking at data when an important change happens.
    But when they do think that data can help them at the right time,
  2. It’s hard to find data they can trust - users have endless BI and business applications where their analytics reside. It’s a challenge to know which application hosts the required data, and then find trusted data within the explosion of reports in the application.
    But when they do find the trusted data,
  3. It’s hard to extract insights - most business users weren’t trained as analysts. Knowing how to: read visualizations and tables, ignore visualizations and tables that are useless for the task at hand (did anyone say analysis paralysis?), filter reports correctly, cross-reference two or more metrics, and so forth - is darn hard.
    But when they do extract the insights,
  4. It’s hard to know exactly what to do next, and do it - having the right insight with the right context is just the starting point to reach superior business outcomes. Next is: what action should I take with what I learned? When should I take it? Where and how do I take the action? And can somebody please help me not procrastinate..?

Like many other analytics practitioners, our team has personally experienced every combination of these problems. This drove us to build Rupert. It’s the product we and data teams have been searching for to be truly impactful on the business.

We started building a Product. We called it Rupert.

To tackle these problems, we started by promoting analytics content to business users via Slack and email recommendations. We shared dashboards they should be reviewing and exposed relevant queries they could explore through our natural language search interface. We saw more business engagement with analytics, but users started consuming content with bad data due to the ever exploding report production in organizations. So we built the Rupert Desk to give analysts a UI to verify trusted content for their business users. Behind the scenes, we used text-to-sql and sql-to-text natural language models for connecting questions to answers encoded in data assets.

And ta-da! Business users can find the right data with enough context to use it on their own, all without analysts’ help. Analysts from our first customers at Insider, Solo Brands, Vida Health, and Coalition, loved how it shortened the time-to-insight and cleared their analysts’ plates.

But there was still work to be done to solve the thorny, intertwined problems described above. For analytics to live up to its business value potential and to truly make business users perform better thanks to analytics, workflows that depend on them taking the initiative, like intelligent search and discovery, aren’t enough. We’ve realized that getting more proactive and getting directly into our business users’ existing workflows, where business value is created, is the solution.

Rupert is the only tool that deeply understands both analytics products and business users’ analytics consumption behavior. Or in other words, the analytics supply and demand. This allows us to break down analytics into bite size units and create personalized insight snippets. We deliver insights with a recommended business action (and an embedded action module to take it), exactly when and where they are the most relevant. When equipped with the right analytical insight and the right next step, business users have a direct path to their promised land.

Automating Proactive Analytics means we need to build

Our vision for analytics distribution has never been more clear. The future has better business-integrated analytics workflow with smart proactive delivery of hyper-personalized business insights with the context and simplicity needed to take action.  We are automating this workflow while allowing analysts and other analytics power users full control and end-to-end visibility as nobody (including gpt-powered robots!) will ever understand the intricacies and idiosyncrasy of the organization’s data and business operation better than them.

The pieces are in place and our users already impact their organizations’ bottom line with Rupert day in, day out. But there’s still so much to build for them and the community.

Content. We are huge believers in Headless BI. We are shipping capabilities that allow our users to work directly with metric layers and enable faster integration into business workflows. This means proactive alerting and notifications fueled by the trusted core of your analytics. But we know the metric layer concept is far from being fully implemented in the market, so we continue and allow the Rupert capabilities over BI assets and reporting tools people use today – there’s just no reason to wait further to get business value from such tools. And so, we are adding more BI/visualization sources and allowing a headless-like distribution experience over them.

Triggers. Personalization is not just sending an insight with tailored metrics to a user based on their attributes. A big part of personalization is the trigger for sending the insight. We are adding more triggers every day, both contextual and data ones, so deliveries are perfectly timed so they maximize business impact potential, for each business user.

Action Modules. Just like we integrate with content sources, we integrate with business applications where business users work. With integrations with tools such as Salesforce and Jira, we are only scratching the surface and we are adding more integrations based on our users’ needs. Our action modules allow delivery owners to set and recommend the right action for each insight for each user at scale and allow business users to swiftly act and improve their and their team’s performance via tools they work with everyday.  

Impact tracking & analysis. Such empowering and simple experience cannot be complete if we don’t measure and attribute the business impact to the people who deserve it. Our analyst users deserve to see and analyze what we believe should be their north star – the impact they make on the business. We are presenting an end-to-end user journey – from insight impression through business action and outcome – and we are deepening the granularity. This allows Rupert to help delivery owners perfect delivery performance by reducing noise and modifying delivery characteristics in our no-code interface. And not less importantly, allows them to celebrate and attribute the business success to themselves and their data assets. It’s time analysts had a seat around the table.  

Simplified access & journeys. Last but not least, while we love interacting with our users f2f, we appreciate their time. We’ll continue stripping every technical complexity off our interface and removing friction from journey steps that can use some gpt-style love (who said it again?). In addition, we’ll be coming out with a full self-serve way to get started with Rupert from our website so anyone could move from publishing a data asset to making immediate business impact in 2-clicks and on-the-go.

And, as written in every product and fundraise announcement, this is truly only the beginning! We close the insight-to-business outcome loop and we won’t sit still until hidden, idle, and underutilized insights go the full way, until they drive actions that bring observable and quantifiable value to the organization. Our mission is to create a win-win situation for analytics and business users that together turn insights into value.

And building requires some cash

With these big aspirations, and the many pizzas that charge us, we needed funding, so we raised $8M led by Cortical Ventures and IA Ventures who help us navigate towards our vision without making too many mistakes. We are also supported by phenomenal and truly valuable partners like Citi Ventures, Joule Ventures, Chris Lynch and his crew, as well as founders and executives of generational data companies such as Alation, AtScale, Looker, Alteryx, SAP, Snowflake, Snowplow, Stitch, and Weights & Biases. And many others

We're pumped to introduce Rupert to the world and bring it to more teams. Learn more, take Rupert for a spin (for free!), and join our team at!