The Rise of Systems of Consolidation Applications
A new class of applications aggregating across enterprise data sources is becoming the most valuable software layer yet.
Introduction
The arc of enterprise software follows a clear evolution: In the 2000’s, software products’ core functions were storing and structuring data—think CRMs, ERPs, and EHRs as systems of record. They primarily served as static repositories of truth. As businesses digitized workflows, the next wave of software in the 2010’s added systems of engagement. These are collaboration platforms and communication layers that prioritized usability and access, like Slack, ServiceNow, and Atlassian. These products had higher customer love and user engagement, but often still sat on siloed backends with siloed enterprise records. In the 2020’s, a new class of companies is emerging. These applications sit above the sprawl of enterprise software and have holistic access to enterprise data. They don’t just capture or surface information, but also interpret, learn, and synthesizes new information to drive decisions and actions. I call these companies systems of consolidation.
What is a System of Consolidation
The rise of systems of consolidation stems from the proliferation of enterprise data sources. Companies now have valuable information sitting in tens, hundreds, and thousands of different places. However, these systems aren’t connected, making it difficult for users to find and use the most relevant information. And until more recently, applications didn’t have open APIs, real-time data infrastructure, and semantic search capabilities with LLMs to make connections easy.
A system of consolidation solves these issues by doing a few things:
It aggregates data across multiple sources and abstracts away the multitude of record siloes in an organization.
It centralizes end user engagement and information access so users don’t have to check a multitude of underlying sources.
Increasingly so with AI agents, it can be a source of intelligence and take actions on behalf of the user.
Examples of Systems of Consolidation
Glean: Actions across the knowledge stack
Glean’s bread and butter business is enterprise search for knowledge workers. But Glean itself does not hold any enterprise data. Instead, the platform integrates with dozens, and sometimes hundreds of data sources within an organization, including Slack, Salesforce, and GitHub, among others. Its power lies in pulling user attention away from individual apps and into a single interface, all with the right access controls. You don’t need to remember whether customer notes were in Slack or Salesforce – just go to Glean. This creates a much simpler, faster, and enjoyable way to do work.
It is no secret that with access to enterprise data, Glean is expanding to enterprise agents. Glean is now turning the search layer into the action layer, across enterprise applications.
Innovaccer: Population health management
Innovaccer is doing something similar in the world of healthcare. Innovaccer aggregates data across various health records, insurances, government payers, and other sources to create a one-stop-shop population health management platform for providers. This is particularly helpful for large providers that have multiple different EHR systems. For example, rather than looking across multiple systems to try to piece together what percent of a population still has unaddressed care gaps, a clinician can just look in Innovaccer. The underlying EHR becomes more commoditized as just a system of record.
As value-based care populations continue to grow with increased penetration of Medicare Advantage, Innovaccer is becoming mission critical software for providers managing thousands of patients.
Peregrine: Unifying law enforcement intelligence
Peregrine serves the law enforcement end market with a data analytics platform. Today, law enforcement agencies manage dozens of data feeds, including social media, body camera footage, arrest warrant records, and more. Peregrine consolidates all that data onto one platform with shared context so detectives can better connect the dots and solve cases. It doesn’t matter if your agency uses Axon or Motorola cameras because you are no longer dependent on their software – it all goes to Peregrine.
Over time, Peregrine will benefit from network effects as information sharing happens across agencies, all on their platform.
Implications for Builders in the Enterprise Tech Stack
The rise of systems of consolidation has many implications on the enterprise tech stack:
Systems of record will become increasingly commoditized – Very few companies love using the SAPs of the world. They do it because that is where information sits. When systems of consolidation suck up all the information from the SAPs, SAPs get reduced to read / write databases. This diminishes their pricing power, right to win on attach products, and stickiness. Customers will spend less time in their environments, which leads to less workflow embeddedness, making an ERP rip and replace more possible now than ever before. Furthermore, with the power of LLM supported data mapping and transformation, new age ERPs such as Doss and Everest are making this increasingly easy to do. In essence, systems of consolidation put old school systems of record that have not invested in user love under threat.
GTM motion will shift more towards top-down – Due to the deep integrations needed for such platforms, GTM sales motions will need more C-suite, multi-department buy-in. As a result, sales cycles tend to be longer and require more dedicated account management. For quickly scaling companies, this means investing and growing enterprise sales talent earlier in your PMF journey. Good enterprise sales talent is a part of PMF, not something you get after PMF.
Longer deployment timelines – Having deep integrations is a double-edged sword. On one side it creates customer stickiness. On the other, it leads to longer deployment timeline. It’s hard to even just build a simple PoC or run a pilot because you need the integrations to be done for anything to work. Furthermore, getting the right governance and access takes additional time and attention. As a result, speed = power: teams that show faster time-to-value will have a comparative advantage in winning.
Agentic AI should exist on this layer - The core of an AI agent is something that can take action independently, on behalf of a user. The most valuable workloads frequently involve context and usage across multiple systems. Therefore, the most valuable agentic work will happen across multiple systems. This puts systems of consolidation in the best position to build high-value AI agents with most reach and ubiquity. In comparison, application specific “vertical” AI agents will have more limited scopes and capabilities, making them less valuable. For example, a system of consolidation in healthcare may be able to gather a patient’s lab results, doctor notes, and medical records to come up with a diagnosis, and then send a subscription to the nearest pharmacist and schedule a follow up appointment for 1 week later. This is much more valuable, than anything an appointment scheduler agent that only sits in Calendly can do on its own.
Conclusion
The past two decades were about building systems that store and engage. The next decade belongs to systems that consolidate and act. Companies building in this category will become the control plane for enterprise workflows and unlock the full potential of AI in the enterprise. By aggregating enterprise data, pushing down legacy systems of record, and owning end user actions, the systems of consolidation will become the most valuable software layer yet.
Disclaimer: This post and the information presented are intended for informational purposes only. The views expressed herein are the author’s alone and do not constitute an offer to sell, or a recommendation to purchase, or a solicitation of an offer to buy, any security, nor a recommendation for any investment product or service. While certain information contained herein has been obtained from sources believed to be reliable, neither the author nor any of his employers or their affiliates have independently verified this information, and its accuracy and completeness cannot be guaranteed. Accordingly, no representation or warranty, express or implied, is made as to, and no reliance should be placed on, the fairness, accuracy, timeliness or completeness of this information. The author and all employers and their affiliated persons assume no liability for this information and no obligation to update the information or analysis contained herein in the future.
Thanks for this insight and perspective, Salina! Great post!