Hey Everyone,
It’s fairly rare I talk about the B2B world, but for revenue from Generative AI as a movement, it’s exceeding important going forwards.
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Why Enterprise Adoption Matters for Gen AI
Global enterprise spending on generative AI is projected to rocket from $16 billion in 2023 to $143 billion in 2027 and account for 28% of AI expenditures, according to tech research and advisory firm IDC.
Enterprise AI is evolving and at the intersection of the future of business and it’s important that Generative AI builds real tools that are valuable to actual firms of all sizes, and very large Enterprise customers as well.
It’s one thing to find a hit with consumers, that can change relatively fast, but that B2B revenue turns out to be fairly important over time.
API revenue from frontier models for example, is primarily B2B (business-to-business). Nobody can hope to luck out and launch the next ChatGPT that was a unique moment in time in late 2022. But that momentum is reverberating and changing companies and Enterprises from the inside out.
OpenAI vs. Anthropic
Graph by adapted by of Department of Product Newsletter.
In the mid 2020s its Enterprise AI Revenue that Scales
Enterprise AI revenue is becoming more important in how Generative AI continues to evolve as we head from 2024 into 2025 in the months ahead. The way professionals use Perplexity, ChatGPT and other search tools like Genspark to find information is different from a few years ago. But for many kinds of searches, these tools are not appropriate.
As I analyze emerging tech and AI, a lot of what I do is track and try to understand what technology startups are aiming to build and which companies are proving to be winners
These are the five AI startups Sam Altman has asked OpenAI’s recent investors to avoid backing:
🛑 Anthropic
🛑 xAI (Elon Musk)
🛑 Safe Superintelligence (Ilya Sutskever)
🛑 Perplexity
🛑 Glean, who?
The first four make a lot of sense and are known to many AI enthusiasts, but the last one? Not so much. Let’s talk today about Glean AI.
I wanted to go into a bit about what Glean does as one of the most feared competitors of OpenAI themselves. I believe Glean’s revenue growth trajectory points to it being a future winner in the Enterprise AI for work space.
Glean’s annualized revenue grew to $39 million in January 2024, marking a 4x growth from the $10 million recorded in 2023.
Work AI for All
Glean is the Work AI platform connected to your enterprise’s data. Find, create, and automate anything. Explore what Work AI can do for you!
In early September, 2024 Glean raised over $260M in a Series E. It was launched in 2019. Its founders are Arvind Jain (CEO), T.R. Vishwanath (CTO, formerly at Meta and Microsoft), Tony Gentilcore (Product Engineering, formerly at Google), Piyush Prahladka (now CEO of his own stealth startup).
The Work AI platform connected to all your data.
Glean is yet another AI-search company you may not have heard of. Glean competes with a herd of well-financed generative AI startups as well as tech giants, taking on Microsoft Copilot while aiming to disrupt a field of cognitive search tool providers such as Perplexity.
Glean was founded by a seasoned team of former Google search engineers and industry veterans.
Enterprise AI Search – Work AI platform
click to watch the video: 🎥 2:31
Glean wants to expand human potential to do extraordinary work! The recent round values the tech company at $4.6 billion. Find, create, and automate anything using the Glean Platform. So this startup could be a winner of the Generative AI era.
“I spoke with other CEOs to see if they had solutions I’d missed. Their response was, ‘If you find something like that, let us know.’” – Arvind Jain, CEO of Glean (via Sequoia blog)
Work AI for all
Glean has a number a suite of a number of fascinating products:
Customer Testimonials and Stories
Founded by a Google Search Alumni
“In the years since arriving at Google and working on Google Search, Arvind Jain had left his mark on a series of other projects. He had helped engineer YouTube’s video serving system—which pulled up videos related to a user’s search, but also recommended content based on their browsing history. Jain had also worked on the search functions for Google Maps, which were more technically ambitious by far than Google Search and YouTube.” Years later, Arvind Jain would go on to found Glean AI.
Can RAG based Search Augment Worker Productivity?
In terms of B2B and AI workplace tools that are RAG based, Glean specializes in enterprise-grade artificial intelligence (AI) and search capabilities that have the opportunity to scale rather well.
The startups focuses on enhancing workplace productivity by providing a unified search tool that aggregates information from various applications, allowing users to access critical data efficiently.
How is search changing for companies and workplaces in the era of Generative AI? It might be one of the most enduring questions of the hype cycle. Thinking about use cases of retrieval augmented generation (RAG) boils down to AI being really good at summarization and what’s the actual ROI of that for companies? The trajectory of Glean AI thus follows an expected path.
I expect in the next few years for the Enterprise AI search space to become a lot more consolidated into the first winners of the Generative AI wave. I expect Glean AI to win it, at least in the pure-play RAG category.
[This is not a sponsored post]. But I’m very interested in doing more deep dives on the Generative AI winners you might not have heard about.
“Search engines are notoriously difficult to build—they require crawlers sophisticated enough to index data in a multitude of formats in real time and algorithms smart enough to sort and rank that data with precision for any given search.”
How can Enterprise companies increase their productivity.
What can Glean AI’s funding round tell us about its trajectory in this B2B category and as a Generative AI winner?
Who are the competitors of Glean AI and can they disrupt the Enterprise Search market?
Remember, Glean was founded just five years ago!
The Biggest Generative AI use case is Search
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