Full Funnel AI & The Forgotten Art and DNA of Enterprise Software

Over the past two decades, B2B software has shifted dramatically. Once grounded in complex, interconnected systems, the landscape has veered toward simplicity, speed, and SaaS tools built for SMBs. While this made software more accessible, it came at a cost: the erosion of Enterprise DNA—the foundational principles that enable software to thrive in large, variable, and interdependent environments.

1. From Systems to Simplicity

In the 1990s and 2000s, enterprise software was built to orchestrate complexity—ERPs, planning systems, Enterprise CRMs, and BI platforms. These were not apps but operating systems for organizations. They aligned departments, data, and decisions across finance, operations, and sales.

But in the 2010s, simplicity took over. With product-led growth (PLG) and consumer-like UX, tools were designed for adoption speed, not system resilience. They served the needs of SMBs well—but left larger, more complex organizations underserved.

2. The Culture Shift That Got Us Here

This fragmentation is no accident—it’s embedded in the startup and VC playbook:

• PMF and MVP
• Solve for a single persona
• Pick a niche, go deep
• "Sell before you build"

While powerful in the early stages, these tactics prioritize local wins over systemic thinking. They de-emphasize building for interconnected business processes, scalable architecture, governance, and variability —core ingredients of genuine enterprise software.

As a result, enterprise-grade systems became a niche—built only by legacy tech giants, repeat founders with deep domain expertise, or those backed by the few VCs who still believe in multi-year, complex software builds with high-ticket average customer values (ACVs) compared to small-ticket, volume-distribution software. 

Of course, there are exceptions, but the exceptions only serve to reinforce the general trend. 

3. The Rise and Limit of Point Solutions

This shift led to an explosion of point tools, each solving a narrow problem for a specific persona. But when these tools attempted to scale into enterprise environments, they hit critical roadblocks:

Limitations of Point Solutions

• Scalability: Architectures built for transactional usage couldn’t support deep, complex data or a variety of user bases.
• Adaptability: Inability to adapt to complex business processes. E.g., in the case of B2B GTM hybrid GTM motions, which are a mix of product-led, sales-led, marketing-led, and inbound/ outbound, partner-led, multi-product, multi-channel, multi-segment and multi-region
• Governance: Lacked enterprise-grade role-based access, auditability, logging, observability (data and activity level), heterogeneous environments driven by the imperatives of acquisitions, multi-legal-entity businesses,  and compliance readiness
• Integration: Failed to connect with broader systems or workflows and inability to harmonize and resolve inconsistent data across systems

Today, the average B2B GTM team uses 23 different tools across marketing, sales development, and sales. The result? Disconnected processes, fragmented data, and disjointed buyer journeys. No wonder GTM efficiency is at an all-time low.

4. The Danger of Solving in Silos: Point Solutions Creating More Problems Than Solutions

Complex systems don’t tolerate local fixes. I learned this in the world of supply chain ERP and planning. You can’t approve a PO or ship an order unless everything, from inventory to forecast, is reconciled.

Yet modern GTM teams are full of local fixes:

• Lead scoring in marketing
• Cold Outbound/Warm Outbound
• Routing rules in sales development
• Forecasting in sales
• Etc.

Each team is solving its piece, but the system is still broken. Our work with mid-market and enterprise B2B GTM teams reveals a frustrating paradox: despite a proliferation of point tools, companies are still struggling with low GTM efficiency.

These point solutions create:

• Disjointed buyer journeys
• Fragmented GTM workflows
• Local “islands of truth” that don’t connect upstream or downstream

Any aspect that demands visibility across the full buyer journey—whether it’s attribution, pipeline acceleration, lead & account, prioritization, next best action, or revenue forecasting—suffers because of these silos. Each tool is optimized in isolation, with no shared context or continuity.

To compensate, companies often throw more tech and labor at the problem:

• Datalakes and ETL tools
• BI dashboards and warehouse layers
• Data engineers, analysts, and scientists

Yet even with this arsenal, they often still can’t get the answers they need. Why? Because these technologies are stitching together fragments, not solving the root issue. The problem isn’t a lack of data—it’s the lack of a system.

Throwing more technology and headcount is not the solution. We need a different foundation—one built for system-wide coordination, not local optimization.

5. What We’re Doing at RevSure

RevSure is building the future of enterprise GTM AI infrastructure.

We’re solving for the complex and interconnected problem of optimizing the entire buyer journey across Marketing, SDR/BDR, and Sales motions. And we’re doing it for mid-market and enterprise GTM environments, which are inherently:

• Multi-channel (online/offline)
• Multi-segment
• Multi-region
• Multi-product, and
• Hybrid GTM - a mix of Inbound, Outbound, Marketing-led, Sales-led, ABM, Lead-Based, PLG, etc.

You can’t just solve for marketing. Or sales. Or ops. You need a unified system that understands the dependencies between them.

That’s what RevSure is:

A Full-Funnel AI system that automates the entire revenue engine, building the first and only machinery for the modern, complex sales and marketing ecosystem.

We’re not layering dashboards on top of disconnected tools. We’re re-architecting how GTM operates—end-to-end and from the ground up.

6. Rebuilding Enterprise DNA

To do this, we’re returning to the foundational principles of enterprise software:

• Systems Thinking: Buyer journeys don’t happen in silos—neither should your tech stack.
• Scale: Serve large data volumes, a variety of user personas, and diverse workflows.
• Variability by Design: Accommodate changing regions, products, teams, and motions.
• Governance & Auditability: Make control, security, and reliability first-class citizens.
• Adaptability: GTM strategies evolve. The system must, too.
• Hybrid Interaction Paradigms: Modern enterprise users don’t all want the same interface, and they shouldn’t have to. Enterprise systems must support a multimodal interaction model, including data-rich GUIs, Chat Interfaces, Ambient Automation, and agentic AI.

This is what it takes to be truly usable, scalable, and intelligent inside a modern enterprise.

7. The Next Era of B2B Software

The future won’t be won by the 24th point tool or another isolated dashboard. It will be built by systems that can orchestrate complexity, eliminate blind spots, and unify revenue teams under one intelligent tunnel for revenue generation. 

It’s time to retire the fragmented GTM stack.

It’s time to rebuild real enterprise platforms.

It’s time to bring back Enterprise DNA—and power it with AI built for Complex Multimodal GTM.