LightdashBusiness Intelligence (BI) platform, an open-source alternative to Google Looker, is revealing a brand new product that enables corporations to train “AI analysts” for individual teams’ applications, enabling anyone in the corporate to query aggregate business data.

To help, the four-year-old startup also announced Tuesday that it has raised $11 million in a Series A funding round led by Accel.

Lightdash is built for an open-source command-line data transformation tool called db (data authoring tool) that relies on SQL and helps corporations transform raw data into structured, analysis-ready datasets. At the time, the corporate was often known as Hubble has accomplished Y Combinator’s (YC) S20 series.with particular emphasis on testing corporations’ data warehouses to discover data quality issues. As it turned out, these metrics were essentially the most useful in BI tools, hence the co-founder and CEO Hamzah Chaudhary switched product and brand to Lightdash in 2021.

In context, “business analytics” describes the technique of combining and integrating disparate sets of knowledge to derive insights, discover trends, and predict future outcomes. The Lightdash platform serves as each front-end and back-end, so people inexperienced in SQL, similar to marketing or finance teams, can access the visual component through the interface. More technical users can use the backend to create customized workflows and define all of the business logic needed for business reporting purposes.

This ties in with the newest launch of Lightdash, a feature that can enable any team member to ask natural language questions on company data and receive “curated insights” relevant to their department.

“For example, the finance team will have an AI analyst who will only have access to the data, metrics and content that is relevant to them,” Chaudhary explained to TechCrunch via email. “They can interact with their AI analyst in natural language, dramatically reducing the time it takes to get insights in the form of a chart, spreadsheet or dashboard.”

One obstacle to enterprises fully implementing generative AI is the thorny issue of knowledge security; corporations are cautious about sharing confidential company data. However, Chaudhary claims that the corporate’s AI analyst is powered by the identical Lightdash API that’s used in its standard productmeaning corporations already comfortable with Lightdash credentials don’t expose themselves to any additional risk through the use of its AI.

“Data permissions and management is one of the key obstacles preventing larger companies from implementing these tools, and with Lightdash’s AI analyst, these manufacturing capabilities are available right out of the box,” Chaudhary said. “It’s value recognizing; “It’s not a completely new query engine for customer data, it’s actually a completely new way of interacting with our existing query engine.”

Additionally, an AI analyst largely doesn’t need access to actual customer data, Chaudhary added, because he relies on metadata similar to the title and outline of the metric for many of his evaluation. “Clients have full control over what information they want to share with LLM,” he said.

Moreover, Chaudhary says customers can select their preferred LLM provider, including the likes of OpenAI and Anthropic, while still having the ability to use their very own model, which should allay any lingering concerns about opening up access to the corporate’s sensitive data.

In the cloud

Since announcing industrial launch and $8.4 million in seed funding two years ago, Lightdash has launched a hosted cloud service for its basic open source productwith additional features including security tools. Chaudhary says greater than 5,000 teams currently use the open source product on their very own, though it’s often a place to begin before upgrading to the complete feature set available in a industrial version.

“Larger teams have successfully used the OSS product to perform proofs of concept without being bogged down by information and procurement reviews,” Chaudhary said. “This allows companies to decouple the purchasing process from Lightdash testing, dramatically lowering the barrier to trialing the tool and building internal Lightdash champions before moving to a cloud product. Lightdash OSS also provides hobbyists and smaller teams with an easy introduction to BI as it provides a complete set of features to help you get started. As teams grow, they prefer a cloud platform for managed deployment, additional features, and better performance and security.”

Chaudhary claims to have increased its revenue sevenfold in the last 12 months, and its clients include: $60 billion enterprise software company Workday, in addition to Beauty Pie, Hypebeast and Morning Brew.

Currently, Lightdash says its global team has 13 employees split between Europe and the United States, and with the infusion of fresh money, the corporate said it intends to expand its team and product by incorporating latest features along the lines of what it’s currently rolling out in its AI Analysts.

In addition to lead sponsor Accel, Lightdash’s Series A round included participation from Operator Partners, Shopify Ventures, Y Combinator and a handful of angel investors.

General Catalyst, certainly one of Silicon Valley’s largest enterprise capital firms, is preparing to launch a so-called “follow-on fund” worth between $800 million and $1 billion, according to a person conversant in the plans.

The follow-on fund consists of a portion of the shares that the VC firm holds in portfolio firms. From approx $25 billion by way of assets under management for 2023, the precise composition of General Catalyst’s follow-on fund portfolio is still being determined. However, it’s going to likely take stakes in Stripe, Gusto and Circle, the person added. The company recently hired Jefferies as a further investment advisor.

Once the fund is created and investors are found for it, General Catalyst’s original limited partners could have a alternative: sell their shares and money out, making room for brand new investors, or remain invested within the follow-on fund (a process called “rolling”). ‘

Although private equity firms have long used follow-on funds, this mechanism has only recently gained popularity amongst enterprise capitalists, largely due to the low variety of IPOs and slowing M&A activity. This has forced some large enterprise capital firms to use the secondary market to return capital to their limited partners.

In July, for instance, Bloomberg reported that NEA sold shares in 11 portfolio firms, including Databricks and Plaid, to secondary investors who collectively paid $540 million for assets. Lightspeed is currently within the technique of selling a group of existing businesses valued at as much as $1 billion to used buyers.

Like NEA and Lightspeed, General Catalyst’s follow-on fund will consist of late-stage startups which have increased in value for the reason that company first invested within the asset.

General Catalyst didn’t respond to a request for comment.

The primary advantage of a follow-on fund, as opposed to simply selling the shares to one other buyer in a secondary market transaction, is that it allows VC investors to proceed to manage the shares while retaining any future advantages from them. Follow-on funds are also considered more founder-friendly than secondary sales of shares of individual startups because they don’t introduce latest owners into the startup capitalization table. The same VC fund stays invested, albeit through a different fund.

VC funds have been more willing to sell on secondary markets currently as some LPs tell them they’ll reduce on their investments in one other VC fund in the event that they don’t receive at the least a few of the money returns on older investments.

While follow-on funds are generally useful to enterprise capital funds, they will pose a conundrum for some limited partners. Because secondary partnerships sell stock at a significant discount to current valuations – typically 20% to 30% from current valuations – when selling shares, limited partners cannot only take a haircut to existing valuations, but additionally forgo potential increases in stock prices.

Still, one General Catalyst limited partner told TechCrunch that given the shortage of liquidity from enterprise capital investments, his pension fund would at all times select to money out reasonably than move into a follow-on fund.

The person didn’t say when this LP would receive this chance, and Top Contributor is unable to estimate this. Follow-on funds are complex transactions that may take anywhere from six months to a 12 months to sell. These transactions may additionally fail completely. Last 12 months, Tiger Global tried to sell a sort of follow-on fund called a strip portfolio, which sells only a portion of its holdings in each company. However, it couldn’t find a buyer willing to pay a price that the corporate considered fair, PitchBook reported.

When Shasta Ventures asked its limited partners earlier this 12 months to approve a follow-on fund that was valued at 35% below carrying value, the corporate’s investors voted against the deal, – Axios reported.
In April, the Financial Times reported that General Catalyst would commit capital worth almost $6 billion to the brand new core fund. The latest fund has still not been announced. When TechCrunch asked for more details about its fundraising efforts last week, the corporate declined to comment.

Tesla lost a top executive to Waymo on the eve of the electrical vehicle maker’s Robotaxi unveiling on Thursday.

Daniel Ho, Tesla’s former head of vehicle programs and recent product integration, announced his recent role as chief program officer at Waymo last week.

Ho, who previously reported directly to Tesla CEO Elon Musk, oversaw the event and development of the Model Y and Cybertruck, launched recent plants in Berlin and Texas and increased production volumes “from 0.5 million to 1.85 million cars per year,” setting at the identical time According to him, preparatory work on Robotaxi LinkedIn.

Ho joins Waymo because the autonomous vehicle maker adds the Hyundai Ioniq 5 to its robotxi lineup and prepares to scale its purpose-built Zeekr robotics.

Daniel Zhang, one of Tesla’s top vehicle program managers who worked under Ho, also recently left Tesla, according to Post on LinkedIn.