As many of you know, we tend to dive deep and invest in subsectors across fintech, infrastructure, and B2B application software. Traditionally, at the outset of each year, we post the areas we are hunting or plan to develop a thesis within the next year. Like many of our VC ecosystem friends, we’ve observed a distinct shift in the market in the last six months. This shift is pushing us to change the cadence of these posts to twice a year, in Q1 and Q3, as we believe things are changing just that quickly.

Reflecting on the past six months, it’s clear that the pace at which founder-market fit and innovative ideas are emerging has accelerated tremendously. We’ve turned a corner from the 2020-2021 investment scene, which candidly backed more ideas than should have been backed, often endorsing or tolerating inefficient practices. Now, we’re spotting new ideas that not only address market gaps created by the previous period’s frenetic activity but also those applying AI in truly exciting ways to solve customer problems.

A central figure in this transformation is the progress of AI. Its influence in accelerating the creation and deployment of these innovations is immense. Over 2022 and 2023, we saw an explosion in companies propelled by AI. Initial enthusiasm has given way to a more discerning appreciation of AI’s genuine value add. Focus has shifted from companies centered around AI to those pragmatically leveraging AI to address real customer problems.

This evolution in how AI is utilized reflects a broader trend: AI for the sake of AI is fading into the background, replaced by a strategic application of AI to solve customer problems. As we continue through 2024, our perspective is that AI should not dominate the conversation but rather enable and enhance more effective solutions. If we were to distill this article’s essence, it would be “let’s make enterprise more efficient.”

AI Applications, Challenges, and Cognitive Software

The shift towards a more dynamic, efficient, and context-aware AI ecosystem underscores the imperative for a paradigmatic shift in both technological infrastructure and data strategy. We are hunting companies building data infrastructure primitives to enable this new ecosystem, such as advanced embedding management, data engineering automation, and the effective utilization of unstructured data reservoirs.

Conversely, as AI and GenAI usage within the enterprise new risks swiftly emerge from governance to cyberrisk. Enterprises are faced with the critical task of reassessing their existing security frameworks and adopting novel tools to protect essential AI system components, such as interfaces, data sources, inference APIs, outputs, and the models themselves. This is where “MLSecOps” becomes pivotal, embedding security practices from the initial stages of model development through to deployment, heralding a new era of cyber and compliance vigilance.

Software is getting smarter every day. Current software solutions already incorporate some level of “intelligence” into the system. We would argue that vertical SaaS is entering a new era leveraging AI (Vertical SaaS 2.0, if you will). We’re interested in applications using AI for truly novel tasks, where complex data moats and regulated industries mandate purpose-built models and applications. Still, next-generation winners will be organizations that construct “cognitive” software from the ground up, leveraging advances in GenAI.

Risk & Compliance

We believe two trends are converging in a big way. The “attack surface” for companies is expanding due to the increasing scope of data, geography, business units, and personnel, coupled with the rise in government protectionism at both national and local levels. This expansion adds layers of complexity and challenge for enterprises, underscoring a pressing need for enhanced efficiency and oversight.

For over a decade, we’ve been actively investing in compliance solutions, from broad horizontal GRC platforms like LogicGate to more specialized offerings like data privacy in Osano and targeted solutions like Ironscales or Siemplify. However, the swift adoption of intelligent applications and models within enterprises has introduced new risk considerations—essentially, a new player in the game. Now, our focus is on understanding how these developments affect AI model governance across different industries and create specific software requirements in verticals like financial services, manufacturing, industrials, and life sciences.

We believe risk management should not only shield the enterprise from external threats but also involve the internal identification, mitigation, and enhancement of efficiency in its management. The specter of liability for enterprise and their leaders makes a strong case for beefed-up cybersecurity that intertwines closely with compliance – we’re talking about everything from getting ahead of incidents with proactive governance to ensuring rapid response and thorough follow-ups.

Inner workings of FIs

Financial Institutions (FIs) connective tissue is being scrutinized, whether it’s the risk component, compliance, or the way they communicate or interact—FIs are re-evaluating the way they work.

Harsh fines have been a wake-up call, showing just how dangerous (and costly) communications over text or voice can be. Our interest also extends to exploring better ways of communicating with regulators, including advancements in trade reporting mechanisms.

Beyond the sphere of compliance, our attention pivots towards enhancing operational efficiencies and uncovering strategic opportunities for FIs. This encompasses how FIs navigate deposit requirements, identify new counterparties, secure payments, and gain access to new markets, such as Foreign Exchange (FX). Indeed, we’re diving deep into how FIs approach risk management and validation alongside strategies to streamline claims processing workflow.

Reskilling and upskilling for tomorrow’s jobs

The shift towards onshoring—bringing jobs back home—coupled with the ever-widening skills gap and the cooling interest in traditional four-year degrees highlights the need for fresh approaches to skill development.

The landscape is clearly changing—high schoolers are increasingly questioning the value of a pricey college degree, and AI is reinforcing that the required skills for the job market are evolving faster than ever. Fundamentally, we already don’t have enough skilled people to fill available roles, and the gap will only widen if we don’t solve it. Simply put, the market has a skill bid-ask spread. This, combined with a push towards fostering more local job creation in the face of increasing protectionist measures, is compelling companies to deeply reconsider their strategies for equipping their workforce for the future.

We see this not just as a challenge but as a significant opportunity. It’s more than just enhancing training and finding the right match for skills within companies. Our focus is on bridging the divide between the traditional blue-collar workforce and the broader job market. This entails introducing innovative tools and financial solutions that cater to a new kind of employee—one who’s versatile, tech-savvy, and prepared to navigate the changing dynamics of the global economy.

Legal Efficiency Unleashed

The transforming role of the Chief Legal Officer (CLO) and the increasing desire to more effectively control rising in-house expenditure have captured our attention, particularly regarding the software solutions rising to meet this challenge.

We are equally keen to observe how Big Law adapts to the redistribution of work away from their traditional domains and the mounting scrutiny over the billable hour model. Innovations such as modular services, AI co-pilots, collaborative workflows, and novel payment methods are all areas of interest. Beyond the quest for operational efficiency, we find the prospect of enhancing collaboration across the spectrum—between insurance companies, law firms, and clients—especially compelling.

Re-tooling RevOps + Customer Success

Is the Enterprise GTM approach broken? It may be. The effectiveness of demand generation is rapidly declining amidst a cluttered field of tech solutions and companies all selling to the same buyers. Cutting through the noise is increasingly difficult, signaling a new approach, data signals and tooling may be required.

The traditional pillars of customer success—implementation, support, and account management—have often seen a disproportionate focus on account management. This emphasis was mainly driven by its direct impact on internal company metrics, namely, the immediate gains from cross-sells and upsells.

Yet, we contend the foundation of true customer success lies deeper, anchored in the quality of customer relationships and the depth of engagement with the product. Genuine success starts much earlier in the customer journey than traditionally acknowledged in the B2B enterprise space. This critical aspect has been overlooked, highlighting the need for a paradigm shift to unlock the full potential of customer success.

What we’re saying is

Across the diverse sectors we’ve highlighted, each presents distinct challenges and opportunities. The common thread weaving through these varied fields is the transformative role of technology. Whether it’s AI, cybersecurity, data infrastructure, or innovative tools for skills development, the quest for efficiency is being revolutionized by technological advancements.

We’re inspired by the potential to reshape industries. If you’re creating solutions in any of these spaces, we want to speak with you.