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Alaska Airlines venture capital lab creates its first startup: Odysee

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Odysee CEO Steve Casley sees dollar signs in the information. More specifically, artificial intelligence-based software that may analyze vast amounts of information to assist industrial airlines profit from complex flight schedules.

That’s exactly what Odysee, the first startup born from the aviation-focused research lab created by Alaska Airlines and UP.Labs, is doing. The two corporations launched a venture lab last 12 months to create startups designed to resolve specific problems in air travel, reminiscent of guest experience, operational efficiency, aircraft maintenance, routing and revenue management. Odysee said it raised $5 million in a pre-seed round led by UP.Partners, a Los Angeles-based VC firm affiliated with UP.Labs. Alaska Star Ventures, which launched in October 2021, has invested $15 million in UP.Partners’ inaugural early-stage fund.

According to Casley, Alaska Airlines CEO Ben Minicucci flagged a scheduling problem early on. And no wonder. While there may be software available to investigate flight data and plan flights, Casley says they lack the type of real-time data – and, most significantly, revenue forecasts – that Odysee produces.

“You need tools to make better decisions because typically in airlines, schedule changes are made by experienced planners who do it intuitively,” Casley said in a recent interview. “I would not say what their seat within the pants is because numerous the time they will likely be right because they’ve seen each bad and good changes. But they never actually had the information to support their decisions.

According to the corporate, the data-enabled software can run a whole lot of simulations in seconds to quickly determine how schedule changes could impact revenue, profits and reliability.

“There are other optimizers, but to my knowledge none of these models or any optimization company offers revenue forecasts,” Casley said.

The machine learning model built by Odysee accommodates roughly 42 attributes, which include every part from departure time and day to traffic volumes on a selected route and competition schedules. The startup present in early simulations that it was able to save lots of a whole lot of hundreds of dollars in Alaska with only one schedule change.

Odysee is currently conducting user acceptance testing in Alaska. Once all that is accomplished, Alaska will begin a trial period of the software, which Casley said will begin in late October.

That’s a brief timeframe, considering UP.LAbs and Alaska Airlines only established the flight lab a 12 months ago. A fast path to industrial products is one among the major benefits of UP.Labs. UP.Labs, which launched for the first time in 2022, is structured as a venture lab with a brand new variety of financial investment vehicle. The company partners with large corporations reminiscent of Porsche, Alaska Airlines, and most recently JB Hunt to launch startups with recent business models aimed toward solving the industry’s biggest problems. Each partnership will create six startups over three years.

Under the UP.Labs structure, these startups is not going to be created solely to serve a company partner – on this case, Alaska Airlines. Rather, they may operate independently and as industrial enterprises from the outset, ultimately generating revenue from the sale of services or products throughout the industry.

This article was originally published on : techcrunch.com
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Open-source BI platform Lightdash gains Accel’s support in bringing artificial intelligence to business analytics

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Lightdash founders Hamzah Chaudhary and Oliver Laslett

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.”

Lightdash AI Analyst. Image credits:Lightdash

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.

This article was originally published on : techcrunch.com
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Black women push for emojis representing diverse hairstyles

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black social media influencers, Emojis

A non-profit organization in London has launched a campaign to acquire emojis with different hairstyles.


The group, based in Hackney, London, is advocating for a more diverse range of emojis that higher reflect the range of black hairstyles.

Rise.365, community support group based in London, tries to incorporate hairstyles comparable to afros, braids and curls among the many 3,790 emojis available. The organization launched the campaign in response to growing concerns from members who’ve experienced hair discrimination.

“It’s sad and disappointing since it just shows what we’re like [Black people] they do not really show up in vivid light because you’ve got a blonde or redhead girl, not only a daily girl with an afro or braids or something like that” – Reanna Bryan, 18, he said .

Bryan contacted Rise.365 after being told her braided hairstyle wasn’t appropriate for the kitchen at her latest culinary job. Seeing that many others have similar experiences, Rise.365 has launched a campaign advocating for more diverse emojis depicting black hairstyles.

“Black people, especially women, tend to have many different hairstyles, but none of them are representative,” said Amina Gray, mentor and youth coordinator at Rise.365.

“We need to normalize that our hair – whether it is in its natural state or after a protective style – is acceptable… it is professional.”

Young group members at Rise.365 were tasked with designing emojis that may help address the imbalance and showcase popular hairstyles worn by black people.

“I asked all the young people to draw something that represented them or an emoji they would like to see on the keyboard,” Gray explained.

The group narrowed their designs all the way down to 4 styles that best reflected the range of hairstyles locally: braids, afros, curls and braids. Vanita Brown, a junior designer at Good Relations PR, helped bring the sketches to life.

“Most emojis reflect the majority,” Brown said. “I believe that in the initial designs, black and mixed hairstyles were not prioritized because the creators did not necessarily consider or prioritize the diversity of black hairstyles.”

The Unicode Consortium accepts latest emoji proposals, of which only a small proportion have been approved for encoding. Rise.365 plans to submit its projects in April 2025.

“The four we have designed are just the beginning. [The campaign] it is an opportunity to teach,” Gray said. “I don’t want people to think we want emojis just because we want to be represented that way. This is because there is a much deeper message behind it – empowering people and helping them realize that their hair is beautiful.”


This article was originally published on : www.blackenterprise.com
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Sources say General Catalyst is working on a “follow-on” fund worth up to $1 billion

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Hemant Taneja, Managing Partner, General Catalyst

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.

This article was originally published on : techcrunch.com
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