Personal blog of Yzmir Ramirez

Perigee founder Mollie Breen used to work for NSA where she built a security solution to help protect the agency’s critical infrastructure. She spent the last two years at Harvard Business School talking to Chief Information Security Officers (CISOs) and fine-tuning that idea she started at NSA into a commercial product.

Today, the solution that she built moves into public beta and will compete at TechCrunch Disrupt Battlefield with other startups for $100,000 and the Disrupt Cup.

Perigree helps protect things like heating and cooling systems or elevators that may lack patches or true security, yet are connected to the network in a very real way. It learns what normal behavior looks like from an operations system when it interacts with the network, such as what systems it interacts with and which individual employees tend to access it. It can then determine when something seems awry and stop an anomalous activity before it reaches the network. Without a solution like the one Breen has built, these systems would be vulnerable to attack.

“Perigee is a cloud-based platform that creates a custom firewall for every device on your network,” Breen told TechCrunch. “It learns each device’s unique behavior, the quirks of its operational environment and how it interacts with other devices to prevent malicious and abnormal usage while providing analytics to boost performance.”

Image Credits: Perigee

One of the key aspects of her solution is that it doesn’t require an agent, a small piece of software on the device, to make it work. Breen says this is especially important since that approach doesn’t scale across thousands of devices and can also introduce bugs from the agent itself. What’s more, it can use up precious resources on these devices if they can even support a software agent.

“Our sweet spot is that we can protect those thousands of devices by learning those nuances and we can do that really quickly, scaling up to thousands of devices with our generalized model because we take this agentless-based approach,” she said.

By creating these custom firewalls, her company is able to place security in front of the device preventing a hacker from using it as a vehicle to get on the network.

“One thing that makes us fundamentally different from other companies out there is that we sit in front of all of these devices as a shield,” she said. That essentially stops an attack before it reaches the device.

While Breen acknowledges that her approach can add a small bit of latency, it’s a tradeoff that CISOs have told her they are willing to make to protect these kinds of operational systems from possible attacks. Her system is also providing real-time status updates on how these devices are operating, giving them centralized device visibility. If there are issues found, the software recommends corrective action.

It’s still very early for her company, which Breen founded last year. She has raised an undisclosed amount of pre-seed capital. While Perigee is pre-revenue with just one employee, she is looking to add paying customers and begin growing the company as she moves into a wider public beta.

When it comes to pop culture, a company executive or history questions, most of us use Google as a memory crutch to recall information we can’t always keep in our heads, but Google can’t help you remember the name of your client’s spouse or the great idea you came up with at a meeting the other day.

Enter Luther.AI, which purports to be Google for your memory by capturing and transcribing audio recordings, while using AI to deliver the right information from your virtual memory bank in the moment of another online conversation or via search.

The company is releasing an initial browser-based version of their product this week at TechCrunch Disrupt where it’s competing for the $100,000 prize at TechCrunch Disrupt Battlefield.

Luther.AI’s founders say the company is built on the premise that human memory is fallible, and that weakness limits our individual intelligence. The idea behind Luther.AI is to provide a tool to retain, recall and even augment our own brains.

It’s a tall order, but the company’s founders believe it’s possible through the growing power of artificial intelligence and other technologies.

“It’s made possible through a convergence of neuroscience, NLP and blockchain to deliver seamless in-the-moment recall. GPT-3 is built on the memories of the public internet, while Luther is built on the memories of your private self,” company founder and CEO Suman Kanuganti told TechCrunch.

It starts by recording your interactions throughout the day. For starters, that will be online meetings in a browser, as we find ourselves in a time where that is the way we interact most often. Over time though, they envision a high-quality 5G recording device you wear throughout your day at work and capture your interactions.

If that is worrisome to you from a privacy perspective, Luther is building in a few safeguards starting with high-end encryption. Further, you can only save other parties’ parts of a conversation with their explicit permission. “Technologically, we make users the owner of what they are speaking. So for example, if you and I are having a conversation in the physical world unless you provide explicit permission, your memories are not shared from this particular conversation with me,” Kanuganti explained.

Finally, each person owns their own data in Luther and nobody else can access or use these conversations either from Luther or any other individual. They will eventually enforce this ownership using blockchain technology, although Kanuganti says that will be added in a future version of the product.

Image Credits: Luther.ai

Kanuganti says the true power of the product won’t be realized with a few individuals using the product inside a company, but in the network effect of having dozens or hundreds of people using it, even though it will have utility even for an individual to help with memory recall, he said.

While they are releasing the browser-based product this week, they will eventually have a stand-alone app, and can also envision other applications taking advantage of the technology in the future via an API where developers can build Luther functionality into other apps.

The company was founded at the beginning of this year by Kanuganti and three co-founders including CTO Sharon Zhang, design director Kristie Kaiser and scientist Marc Ettlinger . It has raised $500,000 and currently has 14 employees including the founders.

Latent AI, a startup that was spun out of SRI International, makes it easier to run AI workloads at the edge by dynamically managing workloads as necessary.

Using its proprietary compression and compilation process, Latent AI promises to compress library files by 10x and run them with 5x lower latency than other systems, all while using less power thanks to its new adaptive AI technology, which the company is launching as part of its appearance in the TechCrunch Disrupt Battlefield competition today.

Founded by CEO Jags Kandasamy and CTO Sek Chai, the company has already raised a $6.5 million seed round led by Steve Jurvetson of Future Ventures and followed by Autotech Ventures .

Before starting Latent AI, Kandasamy sold his previous startup OtoSense to Analog Devices (in addition to managing HPE Mid-Market Security business before that). OtoSense used data from sound and vibration sensors for predictive maintenance use cases. Before its sale, the company worked with the likes of Delta Airlines and Airbus.

Image Credits: Latent AI

In some ways, Latent AI picks up some of this work and marries it with IP from SRI International .

“With OtoSense, I had already done some edge work,” Kandasamy said. “We had moved the audio recognition part out of the cloud. We did the learning in the cloud, but the recognition was done in the edge device and we had to convert quickly and get it down. Our bill in the first few months made us move that way. You couldn’t be streaming data over LTE or 3G for too long.”

At SRI, Chai worked on a project that looked at how to best manage power for flying objects where, if you have a single source of power, the system could intelligently allocate resources for either powering the flight or running the onboard compute workloads, mostly for surveillance, and then switch between them as needed. Most of the time, in a surveillance use case, nothing happens. And while that’s the case, you don’t need to compute every frame you see.

“We took that and we made it into a tool and a platform so that you can apply it to all sorts of use cases, from voice to vision to segmentation to time series stuff,” Kandasamy explained.

What’s important to note here is that the company offers the various components of what it calls the Latent AI Efficient Inference Platform (LEIP) as standalone modules or as a fully integrated system. The compressor and compiler are the first two of these and what the company is launching today is LEIP Adapt, the part of the system that manages the dynamic AI workloads Kandasamy described above.

Image Credits: Latent AI

In practical terms, the use case for LEIP Adapt is that your battery-powered smart doorbell, for example, can run in a low-powered mode for a long time, waiting for something to happen. Then, when somebody arrives at your door, the camera wakes up to run a larger model — maybe even on the doorbell’s base station that is plugged into power — to do image recognition. And if a whole group of people arrives at ones (which isn’t likely right now, but maybe next year, after the pandemic is under control), the system can offload the workload to the cloud as needed.

Kandasamy tells me that the interest in the technology has been “tremendous.” Given his previous experience and the network of SRI International, it’s maybe no surprise that Latent AI is getting a lot of interest from the automotive industry, but Kandasamy also noted that the company is working with consumer companies, including a camera and a hearing aid maker.

The company is also working with a major telco company that is looking at Latent AI as part of its AI orchestration platform and a large CDN provider to help them run AI workloads on a JavaScript backend.

Hitachi Vantara, the wholly owned subsidiary of Hitachi that focuses on building hardware and software to help companies manage their data, today announced that it has acquired the assets of Containership, one of the earlier players in the container ecosystem, which shut down its operations last October.

Containership, which launched as part of our 2015 Disrupt New York Startup Battlefield, started as a service that helped businesses move their containerized workloads between clouds, but as so many similar startups, it then moved on to focus solely on Kubernetes and helping enterprises manage their Kubernetes infrastructure. Before it called it quits, the company’s specialty was managing multi-cloud Kubernetes deployments. The company wasn’t able to monetize its Kubernetes efforts quickly enough, though, the company said at the time in a blog post that it has now removed from its website.

“Containership enables customers to easily deploy and manage Kubernetes clusters and containerized applications in public cloud, private cloud, and on-premise environments,” writes Bobby Soni, the COO for digital infrastructure at Hitachi Vantara. “The software addresses critical cloud native application issues facing customers working with Kubernetes such as persistent storage support, centralized authentication, access control, audit logging, continuous deployment, workload portability, cost analysis, autoscaling, upgrades, and more.”

Hitachi Vantara tells me that it is not acquiring any of Containership’s customer contracts or employees and has no plans to keep the Containership brand. “Our primary focus is to develop new offerings based on the Containership IP. We do hope to engage with prior customers once our new offerings become commercially available,” a company spokesperson said.

The companies did not disclose the price of the acquisition. Pittsburgh-based Containership only raised about $2.6 million since it was founded in 2014, though, and things had become pretty quiet around the company in the last year or two before its early demise. Chances are then that the price wasn’t all that high. Investors include Birchmere Ventures, Draper Triangle and Innovation Works.

Hitachi Vantara says it will continue to work with the Kubernetes community. Containership was a member of the Cloud Native Computing Foundation. Hitachi never was, but after this acquisition, that may change.

When T4 co-founder and CEO Maks Khurgin was working at Bain and Company, he ran into a common problem for analysts looking for market data. He spent way too much time searching for it and felt there had to be a better way. He decided to build a centralized market data platform himself, and T4 was born. This week the company competes in the TechCrunch Disrupt SF Startup Battlefield.

What he created with the help of his long-time friend and CTO, Yev Spektor, was built on a couple of key components. The first is an industry classification system, a taxonomy, that organizes markets by industries and sub-industries. Using search and aggregation tools powered by artificial intelligence, it scours the web looking for information sources that match their taxonomy labels.

As they researched the tool, the founders realized that the AI could only get them so far. There were always pieces that it missed. So they built a second part to provide a way for human indexers to fill in those missing parts to offer as comprehensive a list of sources as possible.

“AI alone cannot solve this problem. If we bring people into this and avoid the last mile delivery problem, then you can actually start organizing this information in a much better way than anyone else had ever done,” Khurgin explained.

It seems simple enough, but it’s a problem that well-heeled companies like Bain have been trying to solve for years, and there was a lot of skepticism when Khurgin told his superiors he was leaving to build a product to solve this problem. “I had a partner at Bain and Company actually tell me, “You know, every consulting firm has tried to do something like this — and they failed. Why do you think you can do this?””

He knew that figuring out the nature of the problem and why the other attempts had failed was the key to solving the puzzle. He decided to take the challenge, and on his 30th birthday, he quit his job at Bain and started T4 the next day — without a product yet, mind you.

This was not the first time he had left a high-paying job to try something unconventional. “Last time I left a high paying job, actually after undergrad, I was a commodities derivatives trader for a financial [services company]. I left that to pursue a lifelong dream of being in the Marine Corps,” Khurgin said.

T4 was probably a less risky proposition, but it still took a leap of faith that only a startup founder can understand, who believes in his idea. “I felt the problem first-hand, and the the big kind of realization that I had was that there is actually a finite amount of information out there. Market research is created by humans, and you don’t necessarily have to take a pure AI approach,” he said.

The product searches for all of the related information on a topic, finds all of the data related to a category and places it in an index. Users can search by topic and find all of the free and paid reports related to that search. The product shows which reports are free and which will cost you money, and like Google, you get a title and a brief summary.

The company is just getting started with five main market categories so far, including cloud computing, cybersecurity, networking, data centers and eSports. The founders plan to add additional categories over time, and have a bold goal for the future.

“Our long-term vision is that we become your one-stop shop to find market research in the same way that if you need to buy something, you go to Amazon, or you need financial data, you go on Bloomberg or Thomson. If you need market research, our vision is that T4 is the place that you go,” Khurgin said.

A new startup is clearing the way for other companies to better monitor and manage their risk and compliance with privacy laws.

Osano, an Austin, Texas-based startup, bills itself as a privacy platform startup, which uses a software-as-a-service solution to give businesses real-time visibility into their current privacy and compliance posture. On one hand, that helps startups and enterprises large and small insight into whether or not they’re complying with global or state privacy laws, and manage risk factors associated with their business such as when partner or vendor privacy policies change.

The company launched its privacy platform at Disrupt SF on the Startup Battlefield stage.

Risk and compliance is typically a fusty, boring and frankly unsexy topic. But with ever-changing legal landscapes and constantly moving requirements, it’s hard to keep up. Although Europe’s GDPR has been around for a year, it’s still causing headaches. And stateside, the California Consumer Privacy Act is about to kick in and it is terrifying large companies for fear they can’t comply with it.

Osano mixes tech with its legal chops to help companies, particularly smaller startups without their own legal support, to provide a one-stop shop for businesses to get insight, advice and guidance.

“We believe that any time a company does a better job with transparency and data protection, we think that’s a really good thing for the internet,” the company’s founder Arlo Gilbert told TechCrunch.

Gilbert, along with his co-founder and chief technology officer Scott Hertel, have built their company’s software-as-a-service solution with several components in mind, including maintaining its scorecard of 6,000 vendors and their privacy practices to objectively grade how a company fares, as well as monitoring vendor privacy policies to spot changes as soon as they are made.

One of its standout features is allowing its corporate customers to comply with dozens of privacy laws across the world with a single line of code.

You’ve seen them before: The “consent” popups that ask (or demand) you to allow cookies or you can’t come in. Osano’s consent management lets companies install a dynamic consent management in just five minutes, which delivers the right consent message to the right people in the best language. Using the blockchain, the company says it can record and provide searchable and cryptographically verifiable proof-of-consent in the event of a person’s data access request.

“There are 40 countries with cookie and data privacy laws that require consent,” said Gilbert. “Each of them has nuances about what they consider to be consent: what you have to tell them; what you have to offer them; when you have to do it.”

Osano also has an office in Dublin, Ireland, allowing its corporate customers to say it has a physical representative in the European Union — a requirement for companies that have to comply with GDPR.

And, for corporate customers with questions, they can dial-an-expert from Osano’s outsourced and freelance team of attorneys and privacy experts to help break down complex questions into bitesize answers.

Or as Gilbert calls it, “Uber, but for lawyers.”

The concept seems novel but it’s not restricted to GDPR or California’s upcoming law. The company says it monitors international, federal and state legislatures for new laws and changes to existing privacy legislation to alert customers of upcoming changes and requirements that might affect their business.

In other words, plug in a new law or two and Osano’s customers are as good as covered.

Osano is still in its pre-seed stage. But while the company is focusing on its product, it’s not thinking too much about money.

“We’re planning to kind of go the binary outcome — go big or go home,” said Gilbert, with his eye on the small- to medium-sized enterprise. “It’s greenfield right now. There’s really nobody doing what we’re doing.”

The plan is to take on enough funding to own the market, and then focus on turning a profit. So much so, Gilbert said, that the company is registered as a B Corporation, a more socially conscious and less profit-driven approach of corporate structure, allowing it to generate profits while maintaining its social vision.

The company’s idea is strong; its corporate structure seems mindful. But is it enough of an enticement for fellow startups and small businesses? It’s either dominate the market or bust, and only time will tell.

Render, a participant in the TechCrunch Disrupt SF Startup Battlefield, has a big idea. It wants to take on the world’s biggest cloud vendors by offering developers a cheaper alternative that also removes a lot of the complexity around managing cloud infrastructure.

Render’s goal is to help developers, especially those in smaller companies, who don’t have large DevOps teams, to still take advantage of modern development approaches in the cloud. “We are focused on being the easiest and most flexible provider for teams to run any application in the cloud,” CEO and founder Anurag Goel explained.

He says that one of the biggest pain points for developers and startups, even fairly large startups, is that they have to build up a lot of DevOps expertise when they run applications in the cloud. “That means they are going to hire extremely expensive DevOps engineers or consultants to build out the infrastructure on AWS,” he said. Even after they set up the cloud infrastructure, and move applications there, he points out that there is ongoing maintenance around patching, security and identity access management. “Render abstracts all of that away, and automates all of it,” Goel said.

It’s not easy competing with the big players on scale, but he says so far they have been doing pretty well, and plan to move much of their operations to bare metal servers, which he believes will help stabilize costs further.

“Longer term, we have a lot of ideas [about how to reduce our costs], and the simplest thing we can do is to switch to bare metal to reduce our costs pretty much instantly.” He says the way they have built Render will make that easier to do. The plan now is to start moving their services to bare metal in the fourth quarter this year.

Even though the company only launched in April, it is already seeing great traction. “The response has been great. We’re now doing over 100 million HTTP requests every week. And we have thousands of developers and startups and everyone from people doing small hobby projects to even a major presidential campaign,” he said.

Although he couldn’t share the candidate’s name, he said they were using Render for everything including their infrastructure for hosting their web site and their back-end administration. “Basically all of their cloud infrastructure is on Render,” he said.

Render has raised a $2.2 million seed round and is continuing to add services to the product, including several new services it will announce this week around storage, infrastructure as code and one-click deployment.

Last year at this time, Forethought won the TechCrunch Disrupt Battlefield competition. A $9 million Series A investment followed last December. Today at TechCrunch Sessions: Enterprise in San Francisco, the company introduced the latest addition to its platform, called Agatha Predictions.

Forethought CEO and co-founder Deon Nicholas said that after launching its original product, Agatha Answers (to provide suggested answers to customer queries), customers were asking for help with the routing part of the process, as well. “We learned that there’s a whole front end of that problem before the ticket even gets to the agent,” he said. Forethought developed Agatha Predictions to help sort the tickets and get them to the most qualified agent to solve the problem.

“It’s effectively an entire tool that helps triage and route tickets. So when a ticket is coming in, it can predict whether it’s a high-priority or low-priority ticket and which agent is best qualified to handle this question. And this all happens before the agent even touches the ticket. This really helps drive efficiencies across the organization by helping to reduce triage time,” Nicholas explained.

The original product (Agatha Answers) is designed to help agents get answers more quickly and reduce the amount of time it takes to resolve an issue. “It’s a tool that integrates into your Help Desk software, indexes your past support tickets, knowledge base articles and other [related content]. Then we give agents suggested answers to help them close questions with reduced handle time,” Nicholas said.

He says that Agatha Predictions is based on the same underlying AI engine as Agatha Answers. Both use Natural Language Understanding (NLU) developed by the company. “We’ve been building out our product, and the Natural Language Understanding engine, the engine behind the system, works in a very similar manner [across our products]. So as a ticket comes in the AI reads it, understands what the customer is asking about, and understands the semantics, the words being used,” he explained. This enables them to automate the routing and supply a likely answer for the issue involved.

Nicholas maintains that winning Battlefield gave his company a jump start and a certain legitimacy it lacked as an early-stage startup. Lots of customers came knocking after the event, as did investors. The company has grown from five employees when it launched last year at TechCrunch Disrupt to 20 today.

Got hardware? Well then, listen up, because our search continues for boundary-pushing, early-stage hardware startups to join us in Shenzhen, China for an epic opportunity; launch your startup on a global stage and compete in Hardware Battlefield at TC Shenzhen on November 11-12.

Apply here to compete in TC Hardware Battlefield 2019. Why? It’s your chance to demo your product to the top investors and technologists in the world. Hardware Battlefield, cousin to Startup Battlefield, focuses exclusively on innovative hardware because, let’s face it, it’s the backbone of technology. From enterprise solutions to agtech advancements, medical devices to consumer product goods — hardware startups are in the international spotlight.

If you make the cut, you’ll compete against 15 of the world’s most innovative hardware makers for bragging rights, plenty of investor love, media exposure and $25,000 in equity-free cash. Just participating in a Battlefield can change the whole trajectory of your business in the best way possible.

We chose to bring our fifth Hardware Battlefield to Shenzhen because of its outstanding track record of supporting hardware startups. The city achieves this through a combination of accelerators, rapid prototyping and world-class manufacturing. What’s more, TC Hardware Battlefield 2019 takes place as part of the larger TechCrunch Shenzhen that runs November 9-12.

Creativity and innovation no know boundaries, and that’s why we’re opening this competition to any early-stage hardware startup from any country. While we’ve seen amazing hardware in previous Battlefields — like robotic arms, food testing devices, malaria diagnostic tools, smart socks for diabetics and e-motorcycles, we can’t wait to see the next generation of hardware, so bring it on!

Meet the minimum requirements listed below, and we’ll consider your startup:

• Submit your application to TC Hardware Battlefield 2019 by August 14th
• You must have a minimally viable product to demo onstage
• Your product has received little if any, press coverage to date
• Your product must have a hardware device or component

Here’s how Hardware Battlefield works. TechCrunch editors vet every qualified application and pick 15 startups to compete. Those startups receive six rigorous weeks of free coaching. Forget stage fright. You’ll be prepped and ready to step into the spotlight.

Teams have six minutes to pitch and demo their products, which is immediately followed by an in-depth Q&A with the judges. If you make it to the final round, you’ll repeat the process in front of a new set of judges.

The judges will name one outstanding startup the Hardware Battlefield champion. Hoist the Battlefield Cup, claim those bragging rights and the $25,000. This nerve-wracking thrill-ride takes place in front of a live audience, and we capture the entire event on video and post it to our global audience on TechCrunch.

Hardware Battlefield at TC Shenzhen takes place on November 11-12. Don’t hide your hardware or miss your chance to show us — and the entire tech world — your startup magic. Apply to compete in TC Hardware Battlefield 2019, and join us in Shenzhen!

Is your company interested in sponsoring or exhibiting at Hardware Battlefield at TC Shenzhen? Contact our sponsorship sales team by filling out this form.

Forethought, a 2018 TechCrunch Disrupt Battlefield participant, has a modern vision for enterprise search that uses AI to surface the content that matters most in the context of work. Its first use case involves customer service, but it has a broader ambition to work across the enterprise.

The startup takes a bit of an unusual approach to search. Instead of a keyword-driven experience we are used to with Google, Forethought uses an information retrieval model driven by artificial intelligence underpinnings that they then embed directly into the workflow, company co-founder and CEO Deon Nicholas told TechCrunch. They have dubbed their answer engine “Agatha.”

Much like any search product, it begins by indexing relevant content. Nicholas says they built the search engine to be able to index millions of documents at scale very quickly. It then uses natural language processing (NLP) and natural language understanding (NLU) to read the documents as a human would.

“We don’t work on keywords. You can ask questions without keywords and using synonyms to help understand what you actually mean, we can actually pull out the correct answer [from the content] and deliver it to you,” he said.

One of first use cases where they are seeing traction in is customer support. “Our AI, Agatha for Support, integrates into a company’s help desk software, either Zendesk, Salesforce Service Cloud, and then we [read] tickets and suggest answers and relevant knowledge base articles to help close tickets more efficiently,” Nicholas explained. He claims their approach has increased agent efficiency by 20-30 percent.

The plan is to eventually expand beyond the initial customer service use case into other areas of the enterprise and follow a similar path of indexing documents and embedding the solution into the tools that people are using to do their jobs.

When they reach beta or general release, they will operate as a cloud service where customers sign up, enter their Zendesk or Salesforce credentials (or whatever other products happen to be supported at that point) and the product begins indexing the content.

The founding team, mostly in their mid-20s, have had a passion for artificial intelligence since high school. In fact, Nicholas built an AI program to read his notes and quiz him on history while still in high school. Later, at the University of Waterloo, he published a paper on machine learning and had internships at Palantir, Facebook and Dropbox. His first job out of school was at Pure Storage. All these positions had a common thread of working with data and AI.

The company launched last year and they debuted Agatha in private beta four months ago. They currently have six companies participating, the first of which has been converted to a paying customer.

They have closed a pre-seed round of funding too, and although they weren’t prepared to share the amount, the investment was led by K9 Ventures. Village Global, Original Capital and other unnamed investors also participated.