AI-Native Applications
Enterprise software is on the brink of its next evolution with the advent of Large Language Models (LLMs). Traditionally, unstructured data – from emails to contracts – has been primarily underutilized and managed through labor-intensive manual processes. LLMs represent a breakthrough in managing and understanding this data. This shift will change more than just how we process data; it will transform traditional software approaches and make advanced tools (eg, agents) more accessible to everyone.
Focus areas.
AI-Native Vertical SaaS.
The enterprise software market, valued at $150 billion, has traditionally been focused on automating structured data, often sidelining unstructured data such as emails and contracts to manual processes. With the emergence of LLMs, companies now have the ability to automate and understand unstructured data at scale for the first time. New LLM-powered entrants will find opportunities in vertical sectors that rely on unstructured data, such as legal, healthcare, and accounting. In addition to managing unstructured data, we like companies that target areas with stringent accuracy requirements and operate in complex regulatory environments.
Disrupting Traditional Enterprise Categories.
Companies like Salesforce, Workday, and SAP have historically dominated their markets, benefiting from deep integration into their customers’ operations. However, the advent of generative AI marks a pivotal moment for the potential displacement of these entrenched players. This transition towards AI-native solutions represents a profound shift in technology and distribution models, threatening to disrupt the status quo for incumbents across every enterprise software category. The disruptive products will have the following traits:
Modular and easily customizable without expensive developers/admins
Natural language interfaces to better discern and cater to user needs
First-party treatment of unstructured data
Non-siloed databases built atop of data lakes like Snowflake
AI agents to automate certain tasks and roles such as SDRs, customer support, etc.
User-centric design that is personalized and as easy to use as Airtable, Notion, and Slack
Next-generation no-code solutions will deliver on the “no-code” promise.
Over the last two decades, low/no-code solutions have drastically reduced the resources required to build internal and external-facing tools for companies of all sizes. With tech-savvy business users, organizations were able to achieve great results at a fraction of the cost. However, these solutions often failed to deliver an experience that could serve non-technical users. We believe that will change as drag-and-drop interfaces will take a back seat to natural language interfaces; LLMs will prove they can build applications end-to-end without the need for engineering, product, or design resources.
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