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Subscribe now “Grouping + AI” for Triage One area I’m quite excited to see AI revolutionize is “grouping + triage” workflows. Many of them AI based. They each have some of the largest cloud businesses in the world in AWS, Azure and Google Cloud respectively. Perfect for a LLM!
Cloud Capex in Q1 AWS $14 billion Azure $14 billion Google Cloud $12 billion These are not one-time investments, but part of a broader trend that started to occur after the introduction of GPT 3 in mid-2020 Amazon was the first to invest significantly. “Moving to AWS.
At SaaStr AI Day , Mike Tamir, Head of AI at Shopify, and Rudina Seseri, founder and Managing Partner at Glasswing Ventures, level-set about where we are in the cycle for Enterprises adopting AI and the critical work being done at Shopify to leverage AI and solve real problems. The future of Enterprise is “Ambient AI.”
And AI is obviously on fire, pulling up AWS, Google Cloud, Azure, etc. So not everyone is seeing tougher times these days. SaaS outside of classic “B2B’ is often holding up well. Klaviyo, Toast, etc. just had very strong quarters. More B2B2C there. Security remains on fire overall as well.
There are 4 questions a startup should ask themselves about building a startup that uses generative AI. The narrative is : AI is a massive platform change that Goldman Sachs projects will increase GDP 300x more than the PC. There are 4 questions startups should ask themselves about building with generative AI. The video is here.
It’s worth pointing out that Azure is a bit above the long term trendline, while AWS is still below (but accelerating up). It’s worth pointing out that Azure is a bit above the long term trendline, while AWS is still below (but accelerating up).
Because thats how their customerswho were used to AWS, Azure, and GCP pricingexpected to buy. Enterprise sales require a field presence, strategic account management, and a drive to go where your customers are. Pricing: Keep It Simple (At First) Databricks started with a simple, consumption-based pricing model.
Drift brings Conversational Marketing, Conversational Sales and Conversational Service into a single platform that integrates chat, email and video and powers personalized experiences with artificial intelligence (AI) at all stages of the customer journey.
Subscribe now Cloud Giants Report Q3 ‘23 Not a great signal for software this week from the Cloud Giants (AWS, Azure and Google Cloud)…After Q2 (3 months ago), the tone from the Cloud Giants around optimizations was largely: optimizations have started to ease, and net new workloads have picked up. Staggering scale already.
Amazon on AWS : “…customers are continuing to shift their focus towards driving innovation and bringing new workloads to the cloud. ” Microsoft on Azure : “And I think last quarter, we said one, we are going to continue to have these cycles where people will build new workloads. Follow along to stay up to date!
" As with many other companies reporting strength in the market, AI & unstructured data workloads are fueling growth. “I don’t even hear the words AI and budget in the same sentence.” “Yes, we actually saw quite a bit of energy coming from the Azure platform this quarter.
This is why the consumption players (Snowflake, Mongo, Confluent, Azure, AWS, etc) so more variability in the macro slowdown. This brings me to AI (everything leads to AI these days…). When it comes to AI there is now another BIG culprit in misused ARR which I’m calling ERR (we use this term internally).
AWS (Amazon), Azure (Microsoft), and Google Cloud (Google) all reported this week. Azure reported on Tuesday and gave us that glimmer of hope. Then AWS appeared to add fuel to that hope before giving us a huge rug pull. Azure came in at 31% (constant currency). They then guided to 26-27% Azure growth in Q2.
Hyperscaler Preview Next week Amazon, Microsoft and Google report earnings and we’ll see Q3 data for AWS, Azure and Google Cloud. These are thought to be the early AI winners, largely due to all of the compute they’re selling to power GenAI applications.
Cloud Giants Report Q2 We also got the Q2 quarters from AWS / Azure / GCP this week! Our expectation, obviously again, is that we are going to significantly increase our investments in AI infrastructure next year, and we'll give further guidance as appropriate.”
Subscribe now Foundation Models Are to AI what S3 was to the Public Cloud Many people look at 2006 as the birth of the public cloud - the year Amazon launched AWS. Every week I’ll provide updates on the latest trends in cloud software companies. Follow along to stay up to date! Why am I mentioning all this?
Who are the real AI winners. It looks at the YoY dollar change in quarterly revenue from the hyperscalers (just looking at Azure / AWS because the data goes back further) going back a few years. net retention and CAC payback). Is Software Rebounding? The first few months of this year felt like a lot of churning in the market.
When I think about the monetization of AI (and which “layers” monetize first) I’ve always thought it would follow the below order, with each layer lagging the one that comes before it. Model providers (OpenAI, Anthropic, etc as companies start building out AI). 2024 will be the year of AI applications!
So far - you’re either tied to AI tailwinds, or it’s rough out there. And in the public universe, it’s really only been the hyperscalers who’ve benefited from AI. We’ll see if anything improved in the month of April, or if it was another challenged month.
This can lead to an airpocket of valuation as companies transition to a different primary valuation metric Outside of the hypserscalers (Azure, AWS, GCP) who have uniquely benefited from AI revenue (mainly selling compute), everyone else has largely struggled. Coming in to Q1 there was broader optimism.
Usage on Snowflake is driven by queries run on Snowflake Azure: Neutral Tone With Strength in AI Overall I’d characterize Azure’s quarter as a net positive. ” They’re also seeing some real strength in AI Services. They guided to 26-27% growth in Azure in Q2 (with 1% coming from AI).
AI = Data + Compute I’ll continue beating this drum, but we got two great quotes from Azure and AWS this week. Satya at Microsoft said “Every AI app starts with data and having a comprehensive data and analytics platform is more important than ever.” AWS reports next week. So what did we learn?
The three worlds are: B2B2C B2B2B AI And then there are folks in impacted categories like ZoomInfo , where things haven’t really improved. And there’s AI. Jason tweeted WTF because many things are happening in AI, like 200x ARR rounds. A lot of the funding rounds for AI feel like 2021 again, but only for this subset of people.
This conversation is part of our AI Revolution series, which features some of the most impactful builders in the field of AI discussing and debating where we are, where we’re going, and the big open questions in AI. Find more content from our AI Revolution series on www.a16z.com/AIRevolution. Ali: Enterprises move slow.
If next quarter we get similar commentary that Azure gave us this quarter (“still a couple quarters away” without any specific guidance), then we may see market loose a little patience. And everyone hoping for AI acceleration will need to wait. The question is how patient will they be waiting for this?
This is why we’re seeing more and more SaaS companies—Datadog, Twilio, AWS, Snowflake, and Stripe, to name a few—find success with product led growth paired with usage-based pricing. Though it was pioneered in the infrastructure layer (think: AWS and Azure), it’s becoming increasingly popular for API-based products and application software.
We have companies like BuzzFeed and C3 making loose announcements about how they will incorporate generative AI into their business, sending their stocks up 50-100%+. In the short term, enjoy the ride as the chase continues 😊 Kind of related to all of this - we now have seen the Q4’s from AWS, Azure and Google Cloud.
The rise of foundation models and generative AI only furthers this trend. But this isn’t another post about AI, it’s about the future of data infrastructure. As Frank Slootman (Snowflake CEO) said, “Enterprises are also realizing that they cannot have an AI strategy without a data strategy to base it on.”
Key examples are Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform, which provide scalable resources like virtual servers and storage. Some of Microsoft’s features are: Enterprise solutions : Microsoft provides comprehensive enterprise solutions, including cloud computing, AI, digital transformation, and more.
Besides, their data professionals could develop comprehensive data strategies, deploy sophisticated analytics, and use AI to acquire deeper insights. Within a few minutes of receiving a claim and recording the closure, an AI algorithm could complete the full health insurance claims procedure in a recent pilot without human participation.
Running your own server to handle your customer's valuable data requires a huge investment to match the same level of security and reliability that comes baked into services like Amazon AWS and Microsoft Azure cloud. AI Integrations. As such, many SaaS businesses are opting for the latter.
Microsoft’s recent deal with SAP to bring SAP cloud customers onto the Azure platform, together with similar deals with Oracle and VMWare, gives AWS a run for its money. The move to the Cloud is well underway, but the impact of AI on new growth and productivity is not yet well understood. and Adobe is in third place with 6.7%
We’ve all seen AWS and what they’ve done with their platform. Azure has been gaining on them rapidly and is growing a double that rate. What we’ve built is this core AI machine learning engine that takes literally millions and millions of unique sources so that we can deliver 95% accuracy to our clients.
Bonus points : Experience with cloud platforms (AWS, Azure, GCP). Making Data Simple : Hosted by AI VP at IBM, Martin AI, this podcast focuses on making complex data science concepts understandable for a broader audience. Experience with data visualization tools (e.g., Tableau, Power BI).
With this AI tool, you will discover effective ways to perform enterprise-grade application security and implement security patches really fast. What steps should I take to see if automated vulnerability scanning is right for my software team? Get Cyber Chief's free trial today and ship your application with zero-known vulnerabilities.
The ultimate failure of Siri to dominate the AI personal assistant game might come to be seen as its biggest miss of the decade. The wave of SaaS companies that built themselves on the likes of AWS and Azure have reinforced the pre-eminence of cloud computing.
Found in 2011 by Ashish Thusoo and Joydeep Sen Sarma, Qubole works on developing a “cloud-based data lake platform for self-service AI.” The company offers a data analytics platform based on Amazon Web Services (AWS), Google Clouds, and Microsoft Azure.
Five people in the digital team were looking at blockchain projects and three people on that digital team were looking for long term AI transformation. If there’s a social security number and other pieces of AI, then automatically it’s limited to this org or this subset of the org. Is AWS in the lead?
“AWS’ AI business is a multibillion-dollar revenue run rate business that continues to grow at a triple-digit year-over-year percentage and is growing more than 3x faster at this stage of its evolution as AWS itself grew, and we felt like AWS grew pretty quickly.” Azure 26 33 26.9% GCP 23 35 52.2%
AI Commentary Some interesting AI commentary / stats I wanted to highlight from a couple earnings calls this week Microsoft on AI “We're excited that only 2.5 years in, our AI business is on track to surpass $10 billion of annual revenue run rate in Q2.
Whether you’re using AWS, GCP, or MS Azure as your IaaS (Infrastructure as a Service) provider, hosting your data in the cloud doesnt automatically mean its secure. AWS Security Hub Built for AWS users, this tool provides centralized security and compliance insights across all your AWS accounts.
Plus, with built-in penetration testing , AI security questionnaires , and a customizable Trust Center , you can easily meet your security goals while staying ahead of risks. Additionally, it integrates well with other tools and can be deployed on AWS or Azure. DOWNLOAD WHITEPAPER 6.
is OpenAIs newest Generative Pre-trained Transformer model, unveiled as a research preview in late February 2025 Its essentially an upgrade to the powerful GPT-4 model, aimed at making AI responses feel more natural, knowledgeable, and reliable. But what does that mean for an AI? OpenAI describes GPT-4.5 Initially, access to GPT-4.5
From AI-driven applications to automation that slashes tedious tasks, SaaS solutions are becoming smarter and more efficient by the day. Well, AI and machine learning (ML) are making it a reality. In 2025, AI is supercharging SaaS applications, making them more intuitive, predictive, and flat-out smarter. Lets break it down. (A)
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