Launched in December by Databricks Inc., the new venture arm aims to invest in young companies developing data and artificial intelligence systems that work with the parent company’s Databricks Lakehouse data storage and analytics platform. Databricks on Thursday introduced a version of that platform to Lakehouse for Retail for retailers.

Andrew Ferguson, head of the new venture, is leading the strategic investment effort. Earlier this month, Databricks Ventures made its first investment by participating in a $110 million Series D funding round from Labelbox Inc., a San Francisco-based training data platform for enterprise machine learning applications.

Mr Ferguson spoke to WSJ Pro AI about the Lakehouse Fund, the unit’s first, and efforts to identify startups that can contribute to Databricks’ Lakehouse ecosystem. In the past, more general data repositories required companies to make copies of their data so that it could be structured and analyzed in an isolated environment. A Lakehouse allows users to analyze data, according to Databricks, a startup with a value of $38 billion.

Corporate-backed venture capital funds may have strategies that go beyond purely financial. “We can derive value from a strategic approach and joint customer relationships,” said Mr. Ferguson. “We have patience.”

Edited excerpts follow.

WSJ Pro AI: It is interesting to see how one startup launches an investment fund to invest in other startups.

Mr. Ferguson: We raised about $2.6 billion in capital last year. So even though we are private, we are very well capitalized and probably better capitalized than many companies that have already gone public.

We invest off-balance sheet in venture-backed early-stage companies aligned with the Databricks and Lakehouse ecosystems.

WSJ Pro AI: What Kind of Companies?

Mr. Ferguson: It is basically any category where the product offering complements Databricks. That’s why LabelBox is a good example, as they fall under the Data Label category. And they help companies collect unstructured data [pieces of information that don’t easily fit into a database] and put some structure in it so they can analyze it more efficiently within the Databricks platform, so that they can to get more value.

Another example is startup that records data. Businesses need to get data from a legacy system, perhaps a cloud environment, wherever the data is stored in the Databricks platform.

Since Lake House is a relatively new category and not set up like some of the other categories like Basic Data Lake or Data Warehouse, we want to ensure that customers have a wide range of partners they can work with. Range of different use scenarios within the lake house ecosystem.

WSJ Pro AI: How big will the fund be and how many companies do you want to invest in?

Mr. Ferguson: We don’t have a specific goal.

We will invest in only the best companies that are in line with our financial profile and strategic fit. We have announced one investment so far and more have closed, though not yet announced.

WSJ Pro AI: How does Databrix Ventures work?

Mr. Ferguson: We don’t run funding rounds. The company must raise Series A or Series B or later. We participate as a part of that big round.

And want to make sure that the potential portfolio company is actually offering a high quality product. So that we can work on integration with confidence, help in joint promotion in the market and bring that product to the attention of our customers. We have an excellent group of technical experts in this field. And they can really help us with a lot of technical investigations.

And they have to believe in and contribute to the lakehouse ecosystem.

WSJ Pro AI: How does Databricks Ventures see the VC landscape?

Mr. Ferguson: Because we invest off-balance sheet, we don’t have the need to raise external capital. But we had some very thoughtful discussions to make sure that we had a very clear mandate for Databrix Ventures and that we weren’t throwing money randomly throughout the ecosystem.

It is a prolific investment environment. But we have patience. We do not have to return the capital to the investors at any time.

For us, in addition to a purely financial return on investment, we can derive value from a strategic approach and joint customer relationships. So we may have a slightly different view of the environment than a completely financially oriented VC.

WSJ Pro AI: Will Databrix launch another fund?

Mr. Ferguson: I think so. I think it will get very strategic over time. We started with a fund and a specific mandate. And as we can prove our success, so will our ambitions.

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