Beyond RPA and SaaS Investments: The Rise of Vertical AI in Industry-Specific Automation

In recent years, we’ve seen a surge of AI-first companies focusing on streamlining horizontal enterprise functions such as sales, human resources, and marketing. These have made it easier for businesses to automate routine tasks, enhance productivity, and deliver better customer experiences. However, there is an acute need for industry-specific solutions given their distinct challenges and nuances as mentioned in our previous article on M&A Activity in IT Services: Key Trends in 2025 Shaping the Industry’s Future. With custom-tuned models trained on industry-specific data, Vertical AI offers more accurate, actionable insights and solutions that are specifically suited to the complexities of fields like healthcare, finance, manufacturing, retail, and beyond.

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Vertical AI is revolutionizing industries by automating high-cost and complex workflows, with market potential poised to surpass legacy Vertical SaaS by a factor of ten. Unlike traditional Vertical SaaS, which competes within the software budgets, Vertical AI unlocks entirely new market opportunities and is looking to go beyond to take over the payroll of a firm by replacing people completely. By leveraging multimodal inputs —incorporating text, video, and images—Vertical AI transcends SaaS’s limitations, delivering solutions that are more independent in decision making by integrating with other varied data sources and applications and without being limited by human capacity.

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Key functional models

• Agents: Fully automate repetitive workflows (e.g., Slang AI for restaurant reservations).

• Copilots: Enhance workforce productivity by assisting professionals (e.g., Sixfold’s AI-driven insurance risk analysis).

• AI Services: Replace outsourced tasks with scalable AI solutions (e.g., SmarterDx for healthcare claim audits).

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Moving from RPA to AI agents- a journey of two decades?

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Enterprises have made significant strides in their automation journey over the past two decades, driven by advancements in technology. In the early 2000s, Robotic Process Automation (RPA) and business process automation (BPA) paved the way for streamlining repetitive tasks across industries. For example, BPOs began leveraging IVR systems to automate routine customer interactions. These systems were a game changer in reducing manual workloads and improving operational efficiency.

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Fast forward to today, and we find ourselves in the era of conversational AI voice agents. Unlike traditional IVR systems, AI-driven voice agents can understand and generate natural language, offering personalized interactions.

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RPA and AI agents are revolutionizing automation by combining their strengths to streamline and optimize business processes. RPA excels at automating repetitive, rule-based tasks like data entry, invoice processing, and document management. For example, companies like UiPath and Automation Anywhere specialize in providing RPA solutions that eliminate manual, mundane tasks. AI agents, on the other hand, bring cognitive capabilities to the table, analyzing unstructured data, making complex decisions, and enabling intelligent workflows.

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A common critique of AI applications is that they sometimes act as "wrappers" around third-party AI models, adding limited value and offering minimal differentiation. Recent advancements in AI algorithms, cloud infrastructure, and data accessibility have made integrating RPA and AI more seamless and cost-effective. Application of AI Agents is more suited for Customer support (chatbots), healthcare (diagnostics), finance (fraud detection) etc. While RPA works better for repetitive tasks like Invoice processing, data migration, compliance tasks etc. For example Kasisto (AI Agent) enhances digital banking experiences with AI-driven chatbots and Blue Prism (RPA) automates accounts payable in large enterprises.

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RPA delivers immediate productivity, while AI Agents drive deeper intelligence and adaptability. The future lies in combining both to enhance operational efficiency and innovation. Businesses must evaluate task complexity and automation goals to deploy the right mix for maximum impact.

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Vertical AI vs Vertical SaaS

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Vertical AI’s ability to unlock untapped markets and deliver exponential efficiency gains makes it a prime target for institutional investment. Compared to traditional Vertical SaaS, Vertical AI generally has a significantly faster time to market, as AI-powered solutions can be deployed and integrated much quicker, allowing companies to see value and adapt to market changes much faster; while Vertical SaaS might require more extensive customization and implementation processes.

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Why Vertical AI might be an attractive investment opportunity compared to their SaaS counterparts?

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o Eating into payroll vs. software budget: Vertical AI reduces hiring needs (e.g., Uptake optimizes operations).

o Greenfield segments with limited competitors: Taps into emerging markets (e.g., Flock Safety (Series E at 34x EV/ARR valuing it U$3.4B) uses AI-driven cameras for surveillance).

o Boosting productivity or replacing employees: AI enhances or replaces repetitive tasks (e.g., Automation Anywhere automates processes).

o Larger TAM by unlocking new markets: Opens new markets, replacing SaaS (e.g., Zebra Medical Vision in medical imaging).

o Not limited by human usage: AI scales without human constraints (e.g., Cedar automates patient billing).

o Multimodal models expand beyond text/data workflows: Leverages voice, video, and images (e.g., JusticeText analyzes and transcribes legal evidences).

o Legacy SaaS must adopt AI: SaaS is integrating AI for relevance (e.g., Intercom, Zapier (36x EV/ARR), Canva (20x EV/ARR)).

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High-Growth Sectors

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• Customer Support: AI agents like Ada and Kore.ai reduce team sizes and costs while handling complex workflows.

• Healthcare: AI agents such as Abridge (Series C at U$2.5B valuation) automates clinical note-taking, streamlining healthcare operations.

• Finance: Companies like Kasisto use conversational AI agents to enhance customer engagement and financial management.

• Retail: Pecan AI leverages predictive analytics and automation to optimize inventory and improve personalization.

• Cybersecurity: AI agents like Darktrace (acquired by Thoma Bravo for U$5.3B at 7x EV/ARR) proactively identify threats and minimize risks through automated monitoring.

• Quality Assurance (QA) Testing: AI systems are streamlining QA processes, enabling faster development cycles with fewer errors by automating testing procedures.

• Debt Collection: AI voice agents are handling debt collection calls, making the process more scalable and efficient, while reducing human worker churn. Vodex.AI (raised at 35x EV/ARR), Skit.AI (raised Series B at 21x EV/ARR) are offering fully function agents

• Recruitment: AI recruitment platforms are automating technical and recruiter screenings, reducing hiring friction, and improving candidate matching.

• Marketing: AI is revolutionizing the marketing industry by enabling personalized content creation, optimizing campaigns, and enhancing customer engagement through data-driven insights.

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Opportunity for Indian players:

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The launch of DeepSeek has sent shockwaves through the AI landscape, leveraging reinforcement learning with minimal supervised fine-tuning to claim superior performance at a fraction of the cost. This breakthrough fuels homegrown AI innovation in India, with companies like Krutrtim.ai, (backed by Ola - advised by Merisis on multiple transactions like their Series A fundraise, acquisition of GoCabs and Zipcash) hosting DeepSeek on its cloud and launching its own open-source multi-lingual LLM models for 10+ Indian languages. With the rise of tailored, cost-effective AI models, startups now have unprecedented access to cutting-edge technology, enabling faster scaling at lower costs.

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AI startups are scaling faster than ever, jumping from pre-revenue to double-digit ARR within months. Companies like 11x.ai and Hebbia exemplify this shift—11x.ai raised $50M at a 35x EV/ARR multiple, growing ARR from $1M to $10M in a year, while Hebbia saw its revenue 15x in 18 months to $13m ARR, securing a valuation at 50x multiple. The open-source AI movement is further accelerating this trend, cutting development costs and making high-performing AI models more accessible. Investors are flocking to these startups, drawn by their rapid growth, strong margins, and the democratization of AI model deployment.  

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At the same time, AI startups are disrupting the traditional B2B sales playbook by forging partnerships with consulting giants like Deloitte and Accenture, enabling them to land multimillion-dollar enterprise contracts from day one. This model is shortening the time to first revenue and reshaping AI commercialization.

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With affordable, high-performing AI models becoming more widely available, the next wave of AI-first companies will scale at an unprecedented pace, fundamentally altering how businesses integrate AI into their operations. Indian vertical AI startups have a unique opportunity to lead the charge in delivering innovative solutions for diverse industries. With the growing accessibility of advanced AI tools, these startups are poised to scale rapidly and redefine the global AI landscape.

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How Merisis can help - Contact Us

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The Enterprise practice is focused on delivering high-impact solutions to drive the growth agenda of companies in the fast-changing technology sector. We leverage our extensive knowledge and relationships in this sector to provide customized capital raising and strategic M&A advice to our corporate clients. Our endeavor is to always deliver a superior customer experience based on trust and partnership. Read more

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