How do the platforms’ or solutions’ algorithms and AI differ between ProureTech solution providers, such as Tealbook, Ivalua, ORO LABS, Zycus, SAP Ariba, and GEP?
The next major battleground in ProcureTech will be between platforms that truly own and intelligently curate their data and workflows versus those simply bolting AI onto legacy structures.
When he first founded his company, Henry Ford used to say that customers could have any color car they wanted, as long as it was black.
Regarding ProcureTech solution provider offerings, is there really a difference?
How solution providers apply AI builds competitive value, not that the AI models themselves are entirely secret or structurally alien.
The above statement clearly demonstrates what I have known (and written about) since the late 1990s: a human-led Agent-based model versus a technology-led Equation-based model increases the likelihood of a successful ProcureTech implementation exponentially.
Here is an excerpt from a more recent Procurement Insights article regarding the difference between agent and equation-based models:
Over the years with each amazing breakthrough – and yes, spreadsheets and amber or green monochrome monitor graphics were amazing in their time, I was asked what I think about the “evergreen” evolution of high-tech computing. My answer has always been the same – it’s not about the technology but the problems the technology solves. In other words, as great as the tech may be, it means nothing if it doesn’t come after people and process understanding.
When organizations make the mistake of leading with technology, they are bending their people and processes around an equation-based model approach in which the tech is the driver for success.
When you lead with people and process understanding – an agent-based model, technology moves from a functional driver to a problem-solving tool that streamlines and delivers efficiencies and tangible results.
Here are the results of using an Agent-based model to develop and implement a self-learning algorithm process within a nascent AI framework:
Improved SLA performance from 51% to 97.3% in 3 months
Consistently reduce their MRO cost-of-goods by 23% year-over-year
How we reduced their FTE from 23 down to 3 in eighteen months
The Coca-Cola and KFC Equations
Are ProcureTech solution provider platform algorithms and AI uniquely structured, e.g., a special or patented coding or framework like Coca-Cola’s recipe for its beverage or KFC for its herbs and spices – how unique are they to each ProcureTech solution provider?
No, most ProcureTech AI algorithms and frameworks are not as uniquely structured or secret as Coca-Cola’s recipe or KFC’s herbs and spices.
Instead, they are:
Built on common commercial AI models (like Python-based ML libraries, cloud-native AI frameworks)
Customized internally for procurement-specific workflows
Occasionally layered with proprietary training data or workflow logic that makes their application more specialized — but not necessarily fundamentally unique in a deep scientific sense.
Therefore, the uniqueness usually lies more in the data models, use cases, UI/UX, and domain-specific tuning, not the core AI engine itself. In short, a human-led Agent-based model.
Watch the brief video below that provides a practical case example of how to practically apply the Agent-based model in the real world:
What Differentiates These ProcureTech Solution Providers’ Tech Platforms?
Besides their procurement industry expertise regarding workflows and data identification and capture, which, if missing, results in a high rate of initiative failure, it is how said industry expertise is incorporated into a solution provider’s platform. In other words, how effectively are they “leveraging technology” to address versus define the operational requirements of a procurement and supply chain practice?
Provider
Uniqueness of AI/Algorithms
Notes on Specialization
TealBook
Moderately Unique
Proprietary supplier data models and enrichment techniques are unique. However, AI enrichment algorithms (ML scraping, entity resolution) are built on standard methods.
Ivalua
Low–Moderate Uniqueness
IVA (their generative AI assistant) is based on integrating standard GenAI models (likely OpenAI/GCP/Azure AI backbones) into their no-code platform. The workflow logic is tuned but not highly unique.
ORO Labs
Moderately Unique
The orchestration engine (workflow AI) is positioned as innovative, especially how it humanizes procurement workflows, but under the hood likely built on standard orchestration and LLM/GenAI techniques.
Zycus
Moderate Uniqueness (Agentic AI)
Zycus’ Merlin platform claims “Agentic AI” — this branding is unique, but it applies widely available ML and automation algorithms. The specialization lies more in how it’s embedded into procurement tasks.
SAP Ariba
Low Uniqueness
SAP uses standard AI models adapted into Ariba workflows. Some personalization in “guided buying,” but fundamentally broad, cloud-based AI services adapted to procurement.
GEP
Moderate Uniqueness
GEP SMART leverages big data ingestion + AI analytics tuned for procurement insights, but again the core AI stack uses known technologies (Azure, AWS AI services) with customization on top.
Here is a further breakdown of what the above “Uniqueness Scores” entail, e.g., Moat Building:
As you consider the above two tables, the following early statement is worth repeating:
How they (ProcureTech solution providers) apply AI builds competitive value — not that the AI models themselves are entirely secret or structurally alien.
Back To Coca-Cola And KFC
Brand Secret Type
ProcureTech AI Equivalence
Coca-Cola Recipe
Not really applicable (no secret algorithm formula)
Apple iPhone UX
More accurate analogy — standard tech components uniquely integrated and user-optimized
Netflix Content Algorithms
Close analogy — AI/ML techniques are standard, but personalized use and data advantage create uniqueness
ProcureTech AI platforms are not “secret recipes.” They are “well-crafted kitchens” using known ingredients, with some unique recipes for procurement-specific needs.
The true differentiators are data, domain tuning, UX simplicity, and workflow orchestration, not secret proprietary AI algorithms.
NEXT INSTALLMENT IN THIS SERIES: Meet the leaders behind the above ProcureTech companies.
Procurement Insights
How do the platforms’ or solutions’ algorithms and AI differ between ProureTech solution providers, such as Tealbook, Ivalua, ORO LABS, Zycus, SAP Ariba, and GEP?
Posted on April 28, 2025
0
The next major battleground in ProcureTech will be between platforms that truly own and intelligently curate their data and workflows versus those simply bolting AI onto legacy structures.
Proprietary supplier intelligence + smart, humanized orchestration = real long-term winners.
Procurement Insights Reference Articles:
When he first founded his company, Henry Ford used to say that customers could have any color car they wanted, as long as it was black.
Regarding ProcureTech solution provider offerings, is there really a difference?
How solution providers apply AI builds competitive value, not that the AI models themselves are entirely secret or structurally alien.
The above statement clearly demonstrates what I have known (and written about) since the late 1990s: a human-led Agent-based model versus a technology-led Equation-based model increases the likelihood of a successful ProcureTech implementation exponentially.
Here is an excerpt from a more recent Procurement Insights article regarding the difference between agent and equation-based models:
Over the years with each amazing breakthrough – and yes, spreadsheets and amber or green monochrome monitor graphics were amazing in their time, I was asked what I think about the “evergreen” evolution of high-tech computing. My answer has always been the same – it’s not about the technology but the problems the technology solves. In other words, as great as the tech may be, it means nothing if it doesn’t come after people and process understanding.
When organizations make the mistake of leading with technology, they are bending their people and processes around an equation-based model approach in which the tech is the driver for success.
When you lead with people and process understanding – an agent-based model, technology moves from a functional driver to a problem-solving tool that streamlines and delivers efficiencies and tangible results.
Here are the results of using an Agent-based model to develop and implement a self-learning algorithm process within a nascent AI framework:
The Coca-Cola and KFC Equations
Are ProcureTech solution provider platform algorithms and AI uniquely structured, e.g., a special or patented coding or framework like Coca-Cola’s recipe for its beverage or KFC for its herbs and spices – how unique are they to each ProcureTech solution provider?
No, most ProcureTech AI algorithms and frameworks are not as uniquely structured or secret as Coca-Cola’s recipe or KFC’s herbs and spices.
Instead, they are:
Therefore, the uniqueness usually lies more in the data models, use cases, UI/UX, and domain-specific tuning, not the core AI engine itself. In short, a human-led Agent-based model.
Watch the brief video below that provides a practical case example of how to practically apply the Agent-based model in the real world:
What Differentiates These ProcureTech Solution Providers’ Tech Platforms?
Besides their procurement industry expertise regarding workflows and data identification and capture, which, if missing, results in a high rate of initiative failure, it is how said industry expertise is incorporated into a solution provider’s platform. In other words, how effectively are they “leveraging technology” to address versus define the operational requirements of a procurement and supply chain practice?
Here is a further breakdown of what the above “Uniqueness Scores” entail, e.g., Moat Building:
As you consider the above two tables, the following early statement is worth repeating:
How they (ProcureTech solution providers) apply AI builds competitive value — not that the AI models themselves are entirely secret or structurally alien.
Back To Coca-Cola And KFC
NEXT INSTALLMENT IN THIS SERIES: Meet the leaders behind the above ProcureTech companies.
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