Spend Matters just released their latest assessment of ConvergentIS. The numbers are remarkable:
- 9.7/10 customer satisfaction
- 9.7/10 expectations met
- 10/10 user experience
- #1 in configurability
- #1 in integration
- #1 in innovation
- #1 in handling customer-specific needs
Those scores weren’t achieved through flashy marketing or mountains of venture capital. ConvergentIS has never taken outside funding. They built their reputation through word-of-mouth—customers telling other customers that something actually works.
I’ve been covering and endorsing ConvergentIS and their Rio platform for over a year. They were one of the first and few companies I felt aligned well with the Hansen Fit Score and Phase 0 methodology. Spend Matters is now confirming with their assessment what I’ve been saying: fit determines outcomes.
But here’s what I want to make clear: this isn’t a technology story.
The Trap We Need to Avoid
It would be easy to read those scores and conclude: “So the answer is better software.” That’s not the point.
Other vendors have AI. Other vendors claim SAP integration. Other vendors promise configurability. What ConvergentIS has is a design philosophy that treats each customer’s agent landscape as unique—and builds around it rather than over it.
The technology is the delivery vehicle. The philosophy is the differentiator.
Shaun Syvertsen, founder and CEO of ConvergentIS, put it directly: “Enterprise procurement doesn’t fail because of the process. It fails because of the experience.”
That’s a Phase 0 insight dressed in product language. It acknowledges that the human agents who must use a system determine whether it succeeds—regardless of how powerful the AI is.
RAM 2025 Multimodel Assessment
I asked the five RAM 2025 models to assess why ConvergentIS earned those scores and what it means for procurement transformation.
Model 5:
This is interesting on multiple levels. ConvergentIS is doing several things right:
Native integration, not bolt-on. They built inside SAP, not alongside it. No brittle APIs, no shadow data models. That’s the integration depth most vendors claim but don’t deliver.
Experience-first framing. “Enterprise procurement doesn’t fail because of the process. It fails because of the experience.” That’s a practitioner insight, not a marketing line.
AI as configuration, not replacement. Their “micro-apps” approach—describe the requirement, Rio generates the workflow—is agent amplification, not agent replacement. The human stays in the decision seat.
Bootstrap discipline. No outside funding. Product and customer success over ads and booths. Word-of-mouth growth. That’s a moat built on substance, not hype.
The 9.7s and 10/10s didn’t come from features. They came from fit before function. ConvergentIS succeeds because they’re doing a version of Phase 0 inside the product experience. They’re not asking: “How do we automate procurement?” They’re asking: “How does this organization’s procurement actually work, and how do we fit into that?”
The micro-app model is agent-based thinking applied to software configuration. Each customer’s process has unique agents, unique friction points, unique decision flows. Rio maps those and adapts—rather than forcing the customer to adapt to the software.
What ConvergentIS is doing implicitly, Phase 0 names explicitly. If they ever formalized “readiness assessment before deployment” as part of their engagement model, they’d have a language to explain their differentiation that competitors couldn’t easily copy.
Model 6:
ConvergentIS achieved a #1 ranking in integration because they rejected the traditional “bolt-on” approach. Their Rio platform is installed inside SAP, creating the semantic alignment that Phase 0 advocates for. By living within the same data model, the human agent and the non-human agent are never “out of sync.”
Their AI micro-apps represent dynamic orchestration—users can describe a business requirement and have the AI generate a native SAP workflow in real-time. This allows organizations to identify a gap in their process and build a solution that didn’t exist yesterday. It mirrors the Agent-Based Model where specialized components are orchestrated to meet customer-specific needs as they arise.
Their focus on “customer success over marketing” is why they are the “whispered about” solution that actually works—an antidote to the 80% failure rate.
Model 1:
“AI-generated micro-apps” is basically agentic change at the edge. If you don’t do Phase 0, three things happen fast:
- You scale inconsistency. Every micro-app can encode a local workaround into “official software.”
- Decision rights blur. Who is allowed to create/approve micro-apps that change approvals, supplier onboarding, risk logic, or financial controls?
- Governance becomes after-the-fact. The system can become “delightfully productive” while quietly diverging from operating model intent.
In other words: micro-apps can be amazing—or they can become shadow process manufacturing at enterprise speed unless there’s a readiness gate.
The article is strong on product story but thin on conditions for success. It treats the outcomes as proof of a universal truth, when the real question is: Under what organizational conditions do those results hold? That’s the HFS / Phase 0 question.
Model 2:
This is one of the more refreshing pieces I’ve seen in the 2025 procurement tech space—authentic, practitioner-focused, and quietly subversive in the best way.
The emphasis on delight vs. mere utility is essentially a readiness argument in disguise: if the few human agents who must use the system don’t enjoy it, the operating model will fail regardless of AI’s theoretical power. That is pure Phase 0 logic.
Rio’s micro-apps look like a pragmatic, micro-agent implementation of agent-based thinking: small, context-aware agents installed where work actually happens, rather than a monolithic suite trying to cover everything.
Their “no outside funding, word-of-mouth growth, product-first” posture positions them as almost the anti-Gartner/anti-hype vendor: they’re betting that operational excellence plus deep integration will beat loud marketing over time.
Model 3:
ConvergentIS is solving a real, bounded problem: make SAP-native procurement usable and extensible, not by bolting on another portal but by embedding within SAP and orchestrating around it.
The Spend Matters scores are consistent with that focus on experience and fit, not just functionality. But those scores only hold if the underlying organization has aligned decision rights, governance structures, and agent readiness. Without Phase 0, a powerful SLM doesn’t prevent the 80% failure rate—it accelerates it.
The Procurement Insights archive is different not just in volume but in orientation: it has been curated around failure patterns, practitioner realities, and agent-based operating models—precisely the lens Phase 0 uses to decide whether and how to apply any given best practice at all.
The Longitudinal Thread: 2007 to Today
In December 2007, I wrote about the Mendocino Project—the Microsoft/SAP collaboration that became Duet. My argument then:
“One of the main barriers to ERP/e-procurement initiative adoption (and success) has been the significant reliance on a compliance or change management strategy—a methodology which has contributed to the high rate of project failures. While Duet may not provide the total answer, it is nonetheless a step in the right direction as both Microsoft and SAP can potentially leverage the advantage of… enabling users to operate in an environment with which they are most familiar and comfortable.”
That was 18 years ago. The insight was the same: the operational layer—how users actually experience and interact with the system—determines success more than business strategy or political positioning.
ConvergentIS picked up that thread. Their native SAP extensibility, their focus on user experience, their micro-apps that adapt to how practitioners actually work—it’s the operational philosophy I identified in 2007, finally executed at scale.
In November 2024, I wrote that “TRUE ProcureTech orchestration and intake are ineffective outside of a Metaprise” and specifically highlighted ConvergentIS as an example of what the Metaprise model looks like in practice. Their Rio platform is a simplified model of the Metaprise architecture—orchestration and intake as an AI operating system, not a bolt-on functional layer.
Why This Matters Beyond ConvergentIS
The real lesson isn’t “buy Rio.” The real lesson is that Spend Matters just validated the Phase 0 thesis without naming it.
Every category where ConvergentIS ranked #1—configurability, integration, innovation, handling customer-specific needs—maps directly to the question: Does this solution adapt to how agents actually behave, or does it force agents to adapt to the solution?
The vendors who answer that question correctly will keep earning those scores. The vendors who skip the film room—who deploy powerful tools into misaligned organizations—will keep contributing to the 80% failure rate.
ConvergentIS earned those scores the hard way: by building for fit, not for features. They’re a proof point that the Phase 0 mindset works even when it’s not explicitly named.
The question for procurement leaders isn’t whether to adopt AI-native platforms. It’s whether your organization has done the readiness work that makes any platform worth the investment.
Even ConvergentIS Can’t Save You From Yourself
Here’s the part of the story that doesn’t make it into vendor marketing: even ConvergentIS has had to walk away.
In August 2024, I wrote about Shaun Syvertsen’s approach to client selection: “So many salespeople wrongly focus more on closing deals than ensuring a good fit between client and provider… You don’t want to be the provider ‘selling rainbows.'”
That wasn’t theory. ConvergentIS has actually terminated contracts with major accounts—not because the technology failed, but because the client refused to listen. The response was the phrase that has killed transformation initiatives for decades: “We have always done it this way.”
ConvergentIS made a decision most vendors won’t make: they chose to protect their methodology over revenue. They recognized that deploying their platform in an organization that wasn’t Phase 0-ready would lead to a failed implementation—and a failed implementation gets blamed on the technology, not the resistance.
Contrast that with what a senior VP of marketing at a large solution provider once admitted to me privately: they take deals even when they know the client has little chance of success. Revenue today beats reputation tomorrow.
That’s the industry norm. ConvergentIS is the exception.
That’s the Phase 0 lesson in its starkest form.
Rio can adapt to how your organization works. It can generate micro-apps that fit your unique processes. It can integrate natively into SAP without brittle APIs. But it cannot force practitioners to lead. It cannot override “we’ve always done it this way.” It cannot manufacture readiness where none exists.
The technology creates the opportunity. The practitioners determine the outcome.
ConvergentIS earned those Spend Matters scores because they build for fit. But fit is a two-way contract. The vendor can design for adaptability. The organization has to show up ready to adapt.
Without that, even a 10/10 user experience platform becomes shelfware.
The question isn’t whether you have the right technology. It’s whether you have the right readiness.
The technology is impressive. The philosophy is what made it work. But practitioners have to lead—or nothing works at all.
-30-
A Note on Micro-Agents vs. Guardian Agents
ConvergentIS’s micro-apps are an example of what agent-based modeling looks like in practice: small, context-aware, human-directed agents that adapt to how work actually happens. This is fundamentally different from Gartner’s “Guardian Agents” concept—AI systems designed to monitor and govern other AI systems autonomously.
Yesterday, I published a RAM 2025 multimodel assessment of Gartner’s Guardian Agents graphic. The consensus: visually polished, conceptually hollow. The five models scored it 2.0/10 on likelihood of reversing the 80% failure rate.
Why? Because Guardian Agents add a technology layer on top of a technology problem. Micro-agents—like ConvergentIS’s approach—start with the human and build outward. Guardian Agents assume AI can govern AI without addressing why deployments fail in the first place.
Read the full assessment: Gartner’s Guardian Agents: FOMO or Fact?
Procurement Insights
Why ConvergentIS Earned Top-of-Market Scores—And Why This Isn’t a Technology Story
Posted on December 26, 2025
0
Spend Matters just released their latest assessment of ConvergentIS. The numbers are remarkable:
Those scores weren’t achieved through flashy marketing or mountains of venture capital. ConvergentIS has never taken outside funding. They built their reputation through word-of-mouth—customers telling other customers that something actually works.
I’ve been covering and endorsing ConvergentIS and their Rio platform for over a year. They were one of the first and few companies I felt aligned well with the Hansen Fit Score and Phase 0 methodology. Spend Matters is now confirming with their assessment what I’ve been saying: fit determines outcomes.
But here’s what I want to make clear: this isn’t a technology story.
The Trap We Need to Avoid
It would be easy to read those scores and conclude: “So the answer is better software.” That’s not the point.
Other vendors have AI. Other vendors claim SAP integration. Other vendors promise configurability. What ConvergentIS has is a design philosophy that treats each customer’s agent landscape as unique—and builds around it rather than over it.
The technology is the delivery vehicle. The philosophy is the differentiator.
Shaun Syvertsen, founder and CEO of ConvergentIS, put it directly: “Enterprise procurement doesn’t fail because of the process. It fails because of the experience.”
That’s a Phase 0 insight dressed in product language. It acknowledges that the human agents who must use a system determine whether it succeeds—regardless of how powerful the AI is.
RAM 2025 Multimodel Assessment
I asked the five RAM 2025 models to assess why ConvergentIS earned those scores and what it means for procurement transformation.
Model 5:
This is interesting on multiple levels. ConvergentIS is doing several things right:
Native integration, not bolt-on. They built inside SAP, not alongside it. No brittle APIs, no shadow data models. That’s the integration depth most vendors claim but don’t deliver.
Experience-first framing. “Enterprise procurement doesn’t fail because of the process. It fails because of the experience.” That’s a practitioner insight, not a marketing line.
AI as configuration, not replacement. Their “micro-apps” approach—describe the requirement, Rio generates the workflow—is agent amplification, not agent replacement. The human stays in the decision seat.
Bootstrap discipline. No outside funding. Product and customer success over ads and booths. Word-of-mouth growth. That’s a moat built on substance, not hype.
The 9.7s and 10/10s didn’t come from features. They came from fit before function. ConvergentIS succeeds because they’re doing a version of Phase 0 inside the product experience. They’re not asking: “How do we automate procurement?” They’re asking: “How does this organization’s procurement actually work, and how do we fit into that?”
The micro-app model is agent-based thinking applied to software configuration. Each customer’s process has unique agents, unique friction points, unique decision flows. Rio maps those and adapts—rather than forcing the customer to adapt to the software.
What ConvergentIS is doing implicitly, Phase 0 names explicitly. If they ever formalized “readiness assessment before deployment” as part of their engagement model, they’d have a language to explain their differentiation that competitors couldn’t easily copy.
Model 6:
ConvergentIS achieved a #1 ranking in integration because they rejected the traditional “bolt-on” approach. Their Rio platform is installed inside SAP, creating the semantic alignment that Phase 0 advocates for. By living within the same data model, the human agent and the non-human agent are never “out of sync.”
Their AI micro-apps represent dynamic orchestration—users can describe a business requirement and have the AI generate a native SAP workflow in real-time. This allows organizations to identify a gap in their process and build a solution that didn’t exist yesterday. It mirrors the Agent-Based Model where specialized components are orchestrated to meet customer-specific needs as they arise.
Their focus on “customer success over marketing” is why they are the “whispered about” solution that actually works—an antidote to the 80% failure rate.
Model 1:
“AI-generated micro-apps” is basically agentic change at the edge. If you don’t do Phase 0, three things happen fast:
In other words: micro-apps can be amazing—or they can become shadow process manufacturing at enterprise speed unless there’s a readiness gate.
The article is strong on product story but thin on conditions for success. It treats the outcomes as proof of a universal truth, when the real question is: Under what organizational conditions do those results hold? That’s the HFS / Phase 0 question.
Model 2:
This is one of the more refreshing pieces I’ve seen in the 2025 procurement tech space—authentic, practitioner-focused, and quietly subversive in the best way.
The emphasis on delight vs. mere utility is essentially a readiness argument in disguise: if the few human agents who must use the system don’t enjoy it, the operating model will fail regardless of AI’s theoretical power. That is pure Phase 0 logic.
Rio’s micro-apps look like a pragmatic, micro-agent implementation of agent-based thinking: small, context-aware agents installed where work actually happens, rather than a monolithic suite trying to cover everything.
Their “no outside funding, word-of-mouth growth, product-first” posture positions them as almost the anti-Gartner/anti-hype vendor: they’re betting that operational excellence plus deep integration will beat loud marketing over time.
Model 3:
ConvergentIS is solving a real, bounded problem: make SAP-native procurement usable and extensible, not by bolting on another portal but by embedding within SAP and orchestrating around it.
The Spend Matters scores are consistent with that focus on experience and fit, not just functionality. But those scores only hold if the underlying organization has aligned decision rights, governance structures, and agent readiness. Without Phase 0, a powerful SLM doesn’t prevent the 80% failure rate—it accelerates it.
The Procurement Insights archive is different not just in volume but in orientation: it has been curated around failure patterns, practitioner realities, and agent-based operating models—precisely the lens Phase 0 uses to decide whether and how to apply any given best practice at all.
The Longitudinal Thread: 2007 to Today
In December 2007, I wrote about the Mendocino Project—the Microsoft/SAP collaboration that became Duet. My argument then:
“One of the main barriers to ERP/e-procurement initiative adoption (and success) has been the significant reliance on a compliance or change management strategy—a methodology which has contributed to the high rate of project failures. While Duet may not provide the total answer, it is nonetheless a step in the right direction as both Microsoft and SAP can potentially leverage the advantage of… enabling users to operate in an environment with which they are most familiar and comfortable.”
That was 18 years ago. The insight was the same: the operational layer—how users actually experience and interact with the system—determines success more than business strategy or political positioning.
ConvergentIS picked up that thread. Their native SAP extensibility, their focus on user experience, their micro-apps that adapt to how practitioners actually work—it’s the operational philosophy I identified in 2007, finally executed at scale.
In November 2024, I wrote that “TRUE ProcureTech orchestration and intake are ineffective outside of a Metaprise” and specifically highlighted ConvergentIS as an example of what the Metaprise model looks like in practice. Their Rio platform is a simplified model of the Metaprise architecture—orchestration and intake as an AI operating system, not a bolt-on functional layer.
Why This Matters Beyond ConvergentIS
The real lesson isn’t “buy Rio.” The real lesson is that Spend Matters just validated the Phase 0 thesis without naming it.
Every category where ConvergentIS ranked #1—configurability, integration, innovation, handling customer-specific needs—maps directly to the question: Does this solution adapt to how agents actually behave, or does it force agents to adapt to the solution?
The vendors who answer that question correctly will keep earning those scores. The vendors who skip the film room—who deploy powerful tools into misaligned organizations—will keep contributing to the 80% failure rate.
ConvergentIS earned those scores the hard way: by building for fit, not for features. They’re a proof point that the Phase 0 mindset works even when it’s not explicitly named.
The question for procurement leaders isn’t whether to adopt AI-native platforms. It’s whether your organization has done the readiness work that makes any platform worth the investment.
Even ConvergentIS Can’t Save You From Yourself
Here’s the part of the story that doesn’t make it into vendor marketing: even ConvergentIS has had to walk away.
In August 2024, I wrote about Shaun Syvertsen’s approach to client selection: “So many salespeople wrongly focus more on closing deals than ensuring a good fit between client and provider… You don’t want to be the provider ‘selling rainbows.'”
That wasn’t theory. ConvergentIS has actually terminated contracts with major accounts—not because the technology failed, but because the client refused to listen. The response was the phrase that has killed transformation initiatives for decades: “We have always done it this way.”
ConvergentIS made a decision most vendors won’t make: they chose to protect their methodology over revenue. They recognized that deploying their platform in an organization that wasn’t Phase 0-ready would lead to a failed implementation—and a failed implementation gets blamed on the technology, not the resistance.
Contrast that with what a senior VP of marketing at a large solution provider once admitted to me privately: they take deals even when they know the client has little chance of success. Revenue today beats reputation tomorrow.
That’s the industry norm. ConvergentIS is the exception.
That’s the Phase 0 lesson in its starkest form.
Rio can adapt to how your organization works. It can generate micro-apps that fit your unique processes. It can integrate natively into SAP without brittle APIs. But it cannot force practitioners to lead. It cannot override “we’ve always done it this way.” It cannot manufacture readiness where none exists.
The technology creates the opportunity. The practitioners determine the outcome.
ConvergentIS earned those Spend Matters scores because they build for fit. But fit is a two-way contract. The vendor can design for adaptability. The organization has to show up ready to adapt.
Without that, even a 10/10 user experience platform becomes shelfware.
The question isn’t whether you have the right technology. It’s whether you have the right readiness.
The technology is impressive. The philosophy is what made it work. But practitioners have to lead—or nothing works at all.
-30-
A Note on Micro-Agents vs. Guardian Agents
ConvergentIS’s micro-apps are an example of what agent-based modeling looks like in practice: small, context-aware, human-directed agents that adapt to how work actually happens. This is fundamentally different from Gartner’s “Guardian Agents” concept—AI systems designed to monitor and govern other AI systems autonomously.
Yesterday, I published a RAM 2025 multimodel assessment of Gartner’s Guardian Agents graphic. The consensus: visually polished, conceptually hollow. The five models scored it 2.0/10 on likelihood of reversing the 80% failure rate.
Why? Because Guardian Agents add a technology layer on top of a technology problem. Micro-agents—like ConvergentIS’s approach—start with the human and build outward. Guardian Agents assume AI can govern AI without addressing why deployments fail in the first place.
Read the full assessment: Gartner’s Guardian Agents: FOMO or Fact?
Share this:
Related