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Navigating the Shift: How AI Startups Like Tome Pivot to Enterprise Solutions Amid Economic Realities

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Lauren Goode

The Future of Generative AI in Business Applications Lacks Glamour

Keith Peiris began noticing the inevitable rise of generative AI in the business sector half a year ago.

Peiris co-founded and leads Tome, a startup based in San Francisco that develops presentation software enhanced by generative AI. This venture kicked off its operations in early 2022, supported by an impressive $32 million of venture capital investment. Following its launch, the company capitalized on the buzz surrounding ChatGPT to secure additional funds in early 2023. Among its notable investors are Reid Hoffman, co-founder of LinkedIn, Eric Schmidt, former CEO and chairman of Google, and Emad Mostaque, who was the CEO of Stability.ai at the time.

However, Tome faced a major challenge: it was not producing significant income. AI startups such as Tome rely on a mix of open source and proprietary language models for their services and incur substantial costs paying entities like OpenAI for the use of their technology to run their applications. To ensure its survival and continue operations, Tome had to take decisive measures.

Last month, Peiris and his business partner Henri Liriani made the difficult decision to reduce their workforce by 20 percent, impacting their team of 59 employees. In addition, they revealed a shift in their business strategy, targeting their application – frequently likened to a GenAI-powered PowerPoint – directly at corporate clients. This pivot also includes a significant pricing adjustment, tripling the fees for their top-tier subscribers.

Peiris explained in a discussion with WIRED that they acknowledged the challenge of time constraints if they had to train Tome's AI to tackle a range of tasks from completing high school assignments, composing post-operative instructions, to generating marketing and sales briefs. "We decided to focus on a customer segment that not only frequently creates presentations but also has tangible results, such as the success of closing a deal. That segment is sales professionals," Peiris stated.

Previously, Tome's website described the application as a "collaborative AI partner," implying a highly versatile and supportive tool. Currently, the firm positions itself as "the premier AI-native research and presentation platform tailored for sales and marketing departments."

Defining Shift

Tome's strategic pivot to focus on corporate clients aligns with the actions of other AI newcomers, including several unicorns valued at over a billion dollars, who introduced generative AI applications amidst the fervor ignited by ChatGPT. Facing increasing costs from cloud API usage, they are shifting towards offering specialized, high-end products and exploring various pricing strategies to enhance their income.

Recently, the startup Perplexity, known for its artificial intelligence-driven search platform, unveiled its latest product, Perplexity Enterprise Pro, amid news of substantial new investment. Early adopters of Perplexity's technology are notable companies such as Zoom, HP, Stripe—a fintech company, and the Cleveland Cavaliers NBA team. These organizations are leveraging the platform for various purposes, including generating sales strategies and conducting research. For its "Pro" tier service, Perplexity is setting the price at $40 monthly, or an annual fee of $400 per user.

In February, Bret Taylor, previously the co-CEO at Salesforce, along with Clay Bavor, a well-known ex-executive from Google, revealed their collaboration in creating Sierra, a venture that leverages generative AI to enhance the intelligence and functionality of brand-specific chatbots, including capabilities such as adjusting delivery timings. The duo has successfully raised substantial funds for their venture into conversational business bots, obtaining $25 million from Benchmark Capital and a further $85 million from Sequoia.

Lauren Goode

Simon Matt

Tess Owen

Charlie Wood

Taylor Sierra also holds the position of board chairman at OpenAI. This company is not your typical startup, boasting a valuation of over $80 billion and receiving upwards of $10 billion in backing from Microsoft. Additionally, OpenAI has been actively expanding its commercial sales operations.

James Dyett, the lead for platform sales at OpenAI, mentions that in the year and a half following the release of ChatGPT in 2022, the organization has been expanding its software sales and market entry division, increasing its size from a team of 15 to a robust group of 200 staff members. This team now constitutes 20% of OpenAI’s present employee base.

OpenAI offers two premium services beyond its complimentary and monthly subscription options priced at $20 for ChatGPT. In August of the previous year, they introduced ChatGPT Enterprise, which offers advanced security options and is available at a cost of $60 for each user or "seat". Additionally, OpenAI provides access to its cloud-based APIs, allowing developers and businesses to create their own AI-driven applications utilizing OpenAI's language processing capabilities. The cost for using these APIs is calculated based on "tokens," which refer to segments of text output that can be as small as a single word or part of one. To use OpenAI's most advanced language model, businesses are charged up to $0.12 for every 1,000 tokens processed.

"During the initial phase of ChatGPT, the platform was known for its impressive poetry and rhymes that amazed many users. However, according to Dyett, it soon became apparent to many corporate leaders that this platform offered much more than entertainment. It had the capability to handle inquiries about legal matters, marketing strategies, and even document summarization. This realization opened up significant commercial prospects for OpenAI, which is crucial for the company as it seeks to balance out the substantial expenses involved in developing its AI technology."

"Dyett mentioned that the executive leadership within Fortune 500 companies have come to realize the significant role this plays in their business operations."

Costly Ventures in AI

Launching and maintaining AI startups requires a significant investment primarily due to their high demand for computational resources, according to Peiris. "Venture capitalists examining these enterprises might be skeptical about projections of scaling to tens of millions of users with a plan to generate revenue at a later stage. This skepticism stems from a contrast with the growth models of earlier mobile or social networking ventures."

Currently, AI startups find themselves navigating a challenging investment landscape, marked by increased caution among investors due to rising interest rates. According to Peiris, one strategy for these companies to attract venture capital is to generate consistent revenue streams, thus reducing their reliance on the unpredictable consumer market. This approach mirrors the strategies employed by tech giants such as Microsoft, Google, and Salesforce. These companies have successfully leveraged the software-as-a-service (SaaS) model for years and are now enhancing their offerings with significant AI integration. However, unlike many nascent AI ventures, these established firms are financially self-reliant.

PitchBook, a firm that monitors venture capital and private equity investments, has been recording funding for startups focused on generative AI since 2021. By the end of 2023, these businesses had secured $23.2 billion in funding, marking a 250 percent increase from the total raised in 2022, according to their data.

Lauren Goode

Simon Matt

Owen Tess

Charlie Wood

Nonetheless, this figure encompasses substantial financial support from business giants, such as the significant investment by Microsoft in OpenAI and the monetary backing Amazon provided to Anthropic. When you remove these large corporate contributions and focus solely on traditional venture capital (VC) funding, the amount of money raised by AI startups in 2023 significantly decreases, aligning with the fundraising levels seen in 2021.

In a report, Brendan Burke, a senior analyst at PitchBook, observed that venture capital investments are progressively directed towards essential AI technologies and their specific industry uses, rather than broad-based middleware solutions in areas such as audio, language, imagery, and video.

To put it differently: A GenAI application designed to boost a company's online sales, analyze legal paperwork, or ensure SOC2 compliance is likely a safer investment than an app that occasionally creates an innovative video or image.

Sierra's co-founder, Clay Bavor, suggests that the inclination of AI startups towards B2B models isn't mainly due to the expenses related to computing or cloud APIs. Instead, he believes the real advantage lies in focusing on a distinct client base and refining their product through direct customer feedback. "I, like many others, am quite hopeful that the efficiency of AI technologies will improve as their operational costs decrease," states Bavor.

"He emphasizes the significance of identifying a specific issue that needs resolution for a certain customer," he mentions. "Following that, you can gather insights on whether your solution is effective or actually addressing the issue. Building a business around this concept can be incredibly impactful."

The surge in artificial intelligence interest, partly due to ChatGPT's ability to effortlessly switch between crafting code and composing poetry, does not change the fact that specialized tools remain in demand, according to Arvind Jain, the CEO of AI startup Glean. He points out that a typical large organization operates with over a thousand distinct technological solutions for data and information management, presenting numerous opportunities for smaller tech enterprises to offer their products to these large corporations.

"In today's era, we're surrounded by numerous practical instruments designed to address distinct needs. This trend is the direction we're heading into," explains Jain, a former Google search engineer with over ten years of experience. Glean, the company he founded in 2019, enhances workplace productivity by integrating with a variety of business applications. It has successfully secured more than $200 million in venture capital investments from prominent firms including Kleiner Perkins, Sequoia Capital, Coatue, among others.

Error Verification

Adjusting a generative artificial intelligence solution for business clientele presents unique obstacles. Mistakes and the unintended outputs, often referred to as "hallucinations" in platforms such as ChatGPT, can have significant implications within sectors like corporate, legal, or healthcare. Furthermore, when offering generative AI technologies to businesses, it's crucial to align with their privacy and security protocols, as well as any legal and regulatory mandates specific to their industry.

"Bavor points out that while ChatGPT or Midjourney unleashing creativity for individual users is noteworthy, it’s a completely different scenario when AI exhibits creativity within business applications."

Bavor mentions that Sierra has put in a significant amount of work and resources into creating protective measures and guidelines to adhere to security and compliance norms. This involves employing more advanced AI to refine Sierra's AI operations. He details that if an AI model initially provides accurate results 90% of the time, introducing supplementary tech to identify and rectify some of the mistakes can significantly increase the accuracy rate.

"Jain, the CEO of Glean, emphasizes the importance of establishing a solid foundation for AI systems when it comes to enterprise applications. He illustrates his point by referring to a scenario where a nurse utilizes AI within a hospital setting to inform patient care decisions, stressing the critical nature of accuracy in such situations."

A more uncertain risk for smaller AI firms offering their products to corporate clients emerges: What happens if a leading gen AI behemoth such as OpenAI, alongside its expanding sales force, opts to launch an identical solution that a specific startup has dedicated itself to developing?

Numerous AI startups that were interviewed by WIRED are shifting their focus away from solely relying on OpenAI's solutions, opting instead for other options such as Anthropic's Claude or Meta's open-source Llama 3 large language models. Additionally, some startups are considering the development of their proprietary AI technologies. However, a significant number of these AI innovators find themselves in a position where they continue to purchase access to OpenAI's technology, even as they may face competition against it down the line.

Peiris, from Tome, pondered the inquiry before stating that his current sole concentration is on sales and marketing applications, aiming to excel in producing high-quality outcomes for these individuals.

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