Vertical AI: The subsequent logical iteration of vertical SaaS

At Index Ventures, we view the emergence of vertical SaaS (vSaaS) — cloud-based software program tailored for particular industries — as a part of a broader pattern of finish customers more and more demanding superior expertise merchandise.

Shoppers need solutions-oriented software program made particularly to unravel their precise enterprise issues. In an surroundings the place we’re inundated with software program, slim and particular is well-positioned versus broad and generalized.

The idea shouldn’t be new: Even the most important horizontal tech firms verticalize their gross sales organizations and product options once they have sufficient scale inside every vertical for that to be a smart method.

Cloud giants AWS, Azure, and Google Cloud Platform prominently function vertical {industry} options with devoted gross sales groups, as do different giant platforms like Salesforce, ServiceNow, Snowflake and Workday.

These tech leaders verticalize their choices over time as a result of it’s a high-quality expertise for purchasers and finish customers when a expertise vendor deeply understands the {industry}, has gross sales and assist reps attending the identical conferences as customers, and is quickly evolving the product to swimsuit buyer wants.

With the AI platform shift upon us, we consider that the following logical iteration of vertical SaaS will probably be vertical AI – vertically-focused AI platforms, bundled alongside workflow SaaS, constructed on prime of fashions which have been uniquely skilled on industry-specific datasets.

Why vertical AI?

The AI class is quickly evolving, however growing into three layers: foundational fashions, AI infrastructure, and AI purposes.

Examples of AI stack startups. (Index Ventures is an investor in Causaly, Cohere, Scale, ServiceTitan and Weaviate.) Picture Credit: Index Ventures

Foundational fashions are the bedrock of the AI stack. Leaders on this house embrace Anthropic, Cohere, and OpenAI. It’s possible there will probably be a restricted variety of distributors within the foundational LLM house given the excessive capital necessities to construct and prepare fashions.

The “picks and shovels” of AI sit on the infrastructure layer, a catch-all which incorporates a wide range of classes together with knowledge enhancement, fine-tuning, databases, and mannequin coaching instruments. For instance, vector databases like Pinecone and Weaviate are gaining vital adoption.

Different firms like Scale are getting used for knowledge technology, labeling, and coaching. Hugging Face has emerged as a frontrunner for mannequin discovery and inference. Weights & Biases is well known inside MLOps. LangChain is an open-source growth framework used to simplify the creation of recent purposes utilizing LLMs. These are a couple of of many firms that are serving to firms remodel fashions and knowledge into merchandise.

Foundational fashions and infrastructure are enabling an explosion of AI enterprise purposes. These AI-powered purposes may very well be utilized by any finish person, in any {industry}, to perform an array of duties.