Last September, we wrote about the landscape for AI-native software after reviewing over 1,000 generative AI startups in just a few months. At the time, there were a few key industries with exciting activity in the B2B, verticalized AI-native software space:
We’ve seen a notable surge in both the number of companies and the venture capital flowing into verticalized GenAI startups since then. The market’s development has been extremely fast, with adoption and activity that would normally unfold over four years compressed into just one. This acceleration has made the market one of the most active for investors.
These verticals have matured quickly, with startups now subcategorizing by function, industry, and end user. For example, The LegalTech Fund’s Early-Stage Legaltech Generative AI Market Map features 200+ companies, segmented by law firm or corporate focus, and further by operational areas like research, litigation, and contracting. Similarly, Andreessen Horowitz’s “Death, Taxes, and AI: How Generative AI Will Change Accounting” includes a market map of AI-driven subcategories in accounting, such as tax filing, bookkeeping, and auditing.
Across Verticals, Trends Emerge.
We’re seeing early breakout companies in verticalized generative AI software, with four key trends across those attracting rapid funding. First, RPA 2.0 is advancing enterprise automation with adaptable workflows, enabling non-technical users to create automations. Second, GenAI tools are quickly transforming large volumes of structured and unstructured data into actionable insights. Third, multimodal capabilities are enhancing documentation and customer interactions through audio-driven tools. Lastly, AI-powered co-pilots are boosting junior professionals’ productivity, improving both speed and accuracy across roles.
Trend #1: RPA 2.0 — Automating Enterprise Workflows
A major trend among breakout vertical GenAI companies is enterprise workflow automation across knowledge management, decision-making, and process optimization. Menlo Ventures’ article, Beyond Bots: How AI Agents Are Driving the Next Wave of Enterprise Automation, details this shift. Unlike rigid RPA 1.0 systems that were reliant on structured data and would normally fail if a user interface changed, new LLM-based automation tools are flexible, processing unstructured inputs and adjusting dynamically. They also enable non-technical users to create automations from natural language instructions.
Companies like Fabric, which raised a $60M Series A, are bringing automation to the healthcare sector. Meanwhile, Sixfold, Oscilar, Glean, and Aiwyn are automating finance-related workflows, and Lexion and EvenUp are leading the charge in the legal industry. We’ve also invested in this space through PilotDesk, which automates workflows within advertising operations.
Trend #2: Processing large amounts of structured and unstructured data
Another key trend is using GenAI to process large volumes of structured and unstructured data, traditionally handled manually. These tools leverage LLMs to ingest, organize, and synthesize data, transforming it into readable, actionable formats like timelines, charts, and summaries. They also add advanced search functions, allowing users to ask questions in natural language and receive relevant insights.
Companies like Truveta in healthcare, Trullion in financial data, and Darrow in legal data have raised significant venture capital funding to bring these capabilities to their respective verticals.
Trend #3: Multi-modal: audio and voice-driven features
Multimodal LLM capabilities now allow processing, generating, and synthesizing text, audio, and images, providing a huge unlock when applied to fields like healthcare and legal services. For example, Abridge uses AI to transcribe and summarize patient-doctor conversations in real-time, enhancing documentation and follow-up care, while early-stage legal tech companies apply similar technology to streamline tasks like deposition transcription.
Additionally, voice-enabled applications will be pervasive. Multimodal LLMs are powering virtual receptionists and call centers, with companies like Hippocratic and Smith AI handling complex customer interactions. Our investment in Drillbit reflects the potential for these tools to improve efficiency and customer experience in the home services industry. Andreessen Horowitz’s “Hi, AI: Our Thesis on AI Voice Agents.”, covers the opportunity in depth.
Trend #4: Co-pilots for junior professionals
The last major trend is improving efficiency for junior professionals. These LLM-powered tools help junior staff work faster and more accurately, reducing the time and additional oversight necessary to get the job across the line. Companies like Paxton, Solomon, and Dili support project management, while well-funded companies like Hebbia and Harvey enhance research capabilities, providing quick, accurate answers to analysts’ questions. By boosting output and lowering errors, these tools allow junior professionals to contribute more independently and effectively.
Burgeoning Verticals Will Follow a Similar Path
While some verticals have matured rapidly, others are still in the early stages, with broad-based solutions and fewer startup activity. We expect these areas to evolve quickly, following a similar path toward verticalization and specialization. The breakout companies that raise significant funding will likely incorporate the qualities we’ve described; automating workflows, processing large amounts of unstructured and structured data, leveraging multimodal capabilities, and enhancing junior professional efficiency
In education, the startup landscape is well-developed on the consumer side, with many AI-native solutions already in use by students and parents. However, we expect to see more “B2B”-focused companies emerge, offering tools to assist educators, administrators, and institutions with tasks such as content generation, student management, and administrative automation. Early-stage companies like MagicSchool and TeachFX are already making headway.
The market in construction is still largely broad-based, but we foresee more niche companies emerging, focusing on specific workflows and subcategories like project management, compliance, or materials sourcing. Similarly, in architecture, early-stage startups such as Archistar and Swapp are beginning to carve out opportunities by providing AI-driven design tools that streamline architectural processes.
Conclusion
The revolution of vertical B2B GenAI is unlike any other, moving at a pace we’ve never seen before. As vertical markets mature and companies continue to refine their offerings, we’re witnessing unprecedented growth and innovation across sectors.
At Ardent, we will continue to track the market closely, searching for early-stage B2B vertical startups that incorporate the key trends we’ve discussed. We’ve already made five investments in this space — Collective, e:cue, PilotDesk, Drillbit, and Roe — and we look forward to making more as this market evolves.
