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Pitch Deck Demolition: Protecto’s $4 million seed deck

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In an era where data is king and its volume and complexity are exploding, Security goals to eliminate the long-standing dilemma that corporations face between harnessing the ability of artificial intelligence while ensuring data privacy. With the surge in popularity of generative AI tools like ChatGPT, recalcitrant data is becoming easier to seek out, process, and do naughty things with. Protecto APIs are designed to guard sensitive data throughout the AI ​​lifecycle while maintaining its usability.

The company announced that it had raised approx $4 million seed funding round led by the Together fund, with the support of Better Capital, FortyTwo VC, Arali Ventures and Speciale Invest. This round brings Protecto’s total funding to $5 million.


Slides on this deck

Before submitting its deck to TechCrunch, Protecto made revisions to its short-term and five-year goals and specific details of its short-term product roadmap. A timeline of goals and milestones for the seed funding round has also been edited. Still, there’s lots you possibly can learn from a 14-slide deck:

  1. Cover slide
  2. Problem slide
  3. Urgent slide
  4. Interstitial platform slide
  5. Technology overview slide
  6. Results slide
  7. Slide with solution
  8. Case study, slide 1
  9. Case study, slide 2
  10. Competitive alternatives are shifting
  11. Team slide
  12. Go to market slide
  13. Slide with motion plan
  14. Ask and use the funds slide

Three things I loved concerning the Protecto pitch

There are just a few things missing from this deck, but there are also some good things value highlighting.

Competitive alternatives

This slide doesn’t discuss direct competitors (there are one or two). But the corporate still does a superb job of showing you this information:

(Slide 10) Competitive alternatives are an incredible solution to take a look at the competitive landscape. Image credits: Security

Competitive alternatives are corporations, methods, or approaches which might be different from yours but meet the identical customer needs or solve the identical problems. For example, if you happen to run a coffee shop, your direct competitor could be one other coffee shop, and a competitive alternative may be a tea shop or fast-food restaurant that also sells coffee and other beverages. These competitors matter because they represent alternative solutions to your customers, underscoring the importance of understanding broader market dynamics and customer preferences.

Understanding and analyzing these competitive alternatives might be powerful as an extra layer of data, uncovering potential opportunities for differentiation and helping to discover unmet customer needs. Having said all this, Protecto should consider its direct competitors, but this slide continues to be an incredible example of how a startup can examine its position available in the market.

Hello, team

This team slide is so solid – the one downside is that they put it because the eleventh slide:

(Slide 11) Solid team slide. Image credits: Security

To stand out within the suddenly crowded AI space, it is best to bring receipts to prove you may have the nerve to do it. The left side of the slide has an excessive amount of information (why are the funds, products, and customers on the team moving?), however the part on the best has a variety of great information.

CEO Amar Kanagaraj spent nearly eight years at Microsoft, including working on search and artificial intelligence, based on his LinkedIn. CTO Baskaran Alagarsamy spent seven years as a ‘manager’ at Apple India. I’d like to see more details about what exactly he was managing there (and why the slide says 18 years and LinkedIn says seven), but that is the beginning of a extremely solid team. If I were investing on this space, a team of this caliber would pique my interest and I’d likely schedule a gathering.

An elegant solution

Privacy and AI can quickly develop into painfully complicated. I appreciate Protecto’s efforts to simplify it to the purpose where most individuals can understand what is going on on in technology.

(Slide 5) Collect sensitive, private data. Replace with similar fake data. It is sensible to me. Image credits: Security

Three things that Protecto could have improved

The design of a pitch deck is not often that essential, however the design of this deck is especially bad. There are also rather more serious flaws hidden in these pages.

These case studies are usually not case studies

In a 14-slide set, Protecto wastes slide 4 as full-screen (it simply says “our platform”). He then wastes two slides titled “case studies.” However, a more accurate term could be “use cases”.

(Slide 8) This shouldn’t be a case study. Image credits: Security

A full case study would come with rather more information concerning the solution’s effectiveness (did the product manage to remove all sensitive data? How was this measured?), how long the combination took, and the way satisfied the client was with the answer. Slide 9 is one other “case study” that is comparable: a use case, not a case study.

The slide header is a promise that the remainder of the slide must fulfill. In this case, I used to be upset on each counts, expecting one kind of information and receiving one other. Proper case studies could be really helpful in telling this story.

Not an incredible “use of funds” slide.

Editorial aside, there’s not much here.

(Slide 14) Almost completely irrelevant information. Image credits: Security

The company wanted to lift $3 million. However, using funds is so fluffy; every point here makes me wish to ask, “But how do you know it works?”

  • Expand engineering: Yes, but why, for what purpose and for a way much?
  • Promote marketing: Yes, but for what purposes? Until when? How much growth?
  • Build channel sales: Yes, but which channels do you select first? Why?
  • Encourage developers to evangelize: What does that even mean?
  • Define category: ???

Basically, it’s all corporate jargon. Even if the founders themselves buy into it, investors probably won’t.

Yes, prediction and specificity are terrifying. What if you happen to fail? All plans and forecasts are predictions. We know. Investors know. The idea is to indicate how you’re thinking that whenever you analyze these predictions; investors can learn lots about you as a founder. This is incredibly helpful – and never optional.

It’s a brainstorming session, not a plan

(Slide 12) This entry into the market is just too vague. Image credits: Security

There are many problems with this slide. The company says it can grow through product-led development. That’s great, however it rarely works in isolation – it must be done along side other marketing channels. “If you build it, they will come” shouldn’t be a thing within the crowded startup ecosystem.

I’d wish to know what these integrations actually mean and the way customers find them. I would love to know how Snowflake and Databricks impact this plan. What does he imagine about “solution integrators”?

This slide is a pile of words on a page, not an actionable and measurable go-to-market plan.

Plus all of the stuff is missing from the deck…

  • How big is the marketplace for such a thing?
  • How much traction do you may have up to now? Did the “case studies” repay? If so, how much? Did they still use the product?
  • There is nothing concerning the business model: how will they charge? How much?
  • How can this be defended? Does the corporate have any patents? Is there any special magic sauce?

Overall, the issue with this deck is that it doesn’t explain why this problem is difficult to resolve and why this company might be the one to resolve it. Perhaps this is just too simplistic within the deck, but based on what’s here, I believe I could get a handful of developers together and construct most of this product in just a few weeks. This cannot be true, right? Because if that’s the case, there’s nothing here. But since that is probably not the case, meaning there’s simply a storytelling problem. Yes, it is a big problem; now explain why it is a difficult problem to resolve.

Full deck


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This article was originally published on : techcrunch.com
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Letta, one of the most anticipated AI startups at UC Berkeley, has just come out of hiding

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Letta, one of UC Berkeley’s most anticipated AI startups, has just come out of stealth

A startup called To read has just come out of hiding with technology that helps AI models remember users and conversations. Built in the famed startup factory of UC Berkeley’s labs, it also announced $10 million in seed funding led by Felicis’ Astasia Myers, at a post-money valuation of $70 million.

Letta also advantages from the backing of some of the most outstanding angel investors in AI, including Jeff Dean of Google, Clem Delangue of Hugging Face, Cristóbal Valenzuela of Runway and Robert Nishihara of Anyscale.

Founded by Berkeley PhD students Sarah Wooders and Charles Packer, it’s a highly anticipated AI startup. That’s since it’s the brainchild of Berkeley’s Sky Computing Lab and is a business arm of the popular open-source project MemGPT.

Berkeley’s Sky Computing Lab, led by renowned professor and Databricks co-founder Ion Stoica, is the offspring of RISELab and AMPLab, which spawned corporations corresponding to Anyscale, Databricks, and SiFive. In particular, Sky Lab spawned quite a few popular open-source large language model (LLM) projects, including Gorilla LLM, vLLM, and the LLM structured language SGLang.

“A lot of projects came out of the lab very quickly, within a year. Just people sitting next to us,” Wooders described. “So it was an amazing time.”

One such project is MemGPT. It is so popular that it went viral even before its release.

“Someone beat us to it,” Packer told TechCrunch. The founders had published an information document on Thursday, Oct. 12, 2023, and planned to publish a more detailed document and code to GitHub the following Monday. Some random person found the document, posted it to Hacker News on Sunday, and “it went viral on Hacker News before we had a chance to properly publish the code or publish the document or, like, start a Twitter thread or something like that,” he said.

The reason for the excitement was that MemGPT alleviates a pernicious problem for LLM: In their native form, models like ChatGPT are stateless, meaning they don’t store historical data in long-term memory. That’s problematic for AI applications that depend on learning from and understanding a user over time—from customer support bots to apps that track health care symptoms. MemGPT manages data and memory so AI agents and chatbots can remember previous users and conversations.

The newspaper post stayed at the top of Hacker News, a preferred developer site run by Y Combinator, for 48 hours, Packer said. So he spent the weekend and the next few days answering questions on the site, attempting to get the code ready for release. Once the project was continue to exist GitHub, a link to it went viral on Hacker News, again. Interviews on YouTube and tutorials, Medium posts, 11,000 stars and 1.2k forks on GitHub happened quickly.

Myers of VC Felicis also learned about Wooders and Packer while reading about MemGPT and immediately realized the business possibilities of the technology.

“I saw that paper when it came out,” she told TechCrunch, and immediately reached out to the founders. “We had an investment theme around AI agent infrastructure, and we appreciated that a really important piece of that was managing data and memory to make these conversational chat bots and AI agents effective.”

The founders continued to virtually drive down Sand Hill Road, on Zoom calls with enterprise capitalists before selecting the one who first loved them.

In the meantime, Stoica was brokering connections with Dean, Nishihara, and other outstanding Silicon Valley angel investors. “A lot of the Berkeley professors, just by virtue of being at Berkeley, are very well-connected,” Packer recalled, describing how easy the angel investor process was. “They have their eye on projects coming out of this lab that are going to be commercialized.”

Competition and the threat from OpenAI o1

While MemGPT is already available and in use, the business version of Letta, Letta Cloud, isn’t yet open for business. As of Monday, Letta is accepting requests from beta users. It will offer a hosted agent service that enables developers to deploy and run stateful agents in the cloud, accessible via REST APIs, a programming interface that may maintain state. Letta Cloud will store the long-term data vital for this purpose. Letta can even offer developer tools for constructing AI agents.

With MemGPT, Wooders sees a wide selection of applications. “I think the most common use case we see is basically highly personalized, highly engaging chatbots,” he says. But there are also novel applications, corresponding to a “chatbot for cancer patients,” where patients upload their history after which share their current symptoms so the bot can learn and offer guidance over time.

It’s price noting that MemGPT isn’t the only one working on this. LangChain might be its best-known competitor and already offers business options. Major modelers also offer tools for creating AI agents, corresponding to the OpenAI Assistant API.

And OpenAI’s latest o1 model could make the need for state fixing a moot point for users. Because it’s a multi-stage model, it essentially needs to take care of some level of state to “think” and fact-check before responding.

But Wooders, Packer, and Myers see some key differences between what Letta offers and what the 800-pound gorilla of the market, OpenAI, does. Letta says it can work with any AI model, and it expects its users to make use of many of them: OpenAI, Anthropic, Mistral, their very own models. OpenAI’s technology currently works only with itself.

More importantly, Letta uses the open-source MemGPT code and firmly sides with the open-source side of the FOSS vs. black-box LLM debate, arguing that open-source is the more sensible choice for AI application developers.

“We’re positioning ourselves as an open alternative to OpenAI,” Packer says. “I think it’s actually very, very hard to build very good AI applications, especially when you’re after something like hallucination, if you can’t see what’s going on under the hood.”

This article was originally published on : techcrunch.com
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Jump raises $12M to help freelancers get benefits on par with employees

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Jump raises $12M to help freelancers get benefits just like employees

French startup Jumpa contemporary take on the umbrella company concept in France, raised €11 million (about $12 million at current exchange rates) in a Series A funding round.

Jump offers full-time contracts to freelancers in search of the soundness and benefits of full-time work. It acts as an administrative companion only, and employees remain independent—they’ll work with multiple clients and negotiate their contracts directly.

Breega is leading today’s funding round, with Index Ventures and Raise Ventures also participating. The startup previously raised €4 million (around $4.5 million) in 2021.

Once signed up, freelancers can invoice their clients through Jump’s platform, and at the tip of the month, they’ll create pay slips and get paid. This feature alone implies that freelancers can set a pay schedule for themselves that may work all yr long—even during those slow summer months.

And with a everlasting contract, employees are registered with the national health system and may contribute to the national pension scheme. Jump also offers medical insurance contracts through Alana, food vouchers through Swile, access to worker savings schemes and more. In France, a everlasting contract can be particularly helpful when you are attempting to buy a house and are negotiating a mortgage with a bank.

There are some trade-offs, though. Corporate dues are deducted out of your salary, and Jump itself costs €99 per thirty days. But whenever you’re a freelancer, money is simply a part of the equation. I see numerous freelancers who want the very best of each freelancing and full-time work. So far, the startup has managed to persuade 2,000 freelancers to jump.

The startup also recently launched a free offer for freelancers just starting out. It features a free, skilled checking account with a virtual debit card that works with Apple Pay or Google Pay. There are also a couple of software features that may help you invoice your first clients, akin to a built-in invoicing tool and a dashboard for tracking financial performance.

“This more or less corresponds to the way freelancers work: they often start with the basic French freelance status, and then move to another status when they start to feel the limitations of their status and have enough income,” said Nicolas Fayon, co-founder and CEO of Jump (pictured above).

Jump wants to support more independent employees in the long run, so it currently offers services to software developers, data engineers, project managers, creative consultants, and sports coaches.

For example, it wants to support B2C merchants, akin to “businesses that bill customers through Stripe, using online payments or physical payment terminals,” Fayon said. Jump also plans to expand to other countries, starting with a U.K. umbrella company for freelancers working within the U.K.

This article was originally published on : techcrunch.com
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SoftBank’s Masayoshi Son was planning his comeback

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SoftBank’s Masayoshi Son has been planning his comeback

AND latest Financial Times profile Mayayoshi Son opens with the SoftBank CEO seemingly hitting all-time low, gazing his “ugly” face on Zoom and telling himself, “I haven’t done anything to be proud of.”

Indeed, Son largely disappeared from the general public eye after SoftBank’s Vision Fund suffered huge losses on investments like WeWork. But FT journalist Lionel Barber, whose latest biography of Son is titled “Gambling Man,” writes that while Son gave the impression to be “doing penance,” he was in actual fact “plotting a comeback.”

Now SoftBank is specializing in artificial intelligence and has achieved success by taking integrated circuit design company Arm public.

The profile also includes some amusing personal details, resembling Son’s apparent fascination with Napoleon. When the activist investor mentioned Bill Gates and Mark Zuckerberg in a 2020 meeting with Son, he reportedly dismissed them as “one-business men.”

“The right comparison for me is Napoleon, Genghis Khan or Emperor Qin,” Son said. “I’m not a CEO. I’m building an empire.”

This article was originally published on : techcrunch.com
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