thomas.wieberneit@aheadcrm.co.nz
Creatio’s AI CRM: Who Gets to Build the Next Agent?

Creatio’s AI CRM: Who Gets to Build the Next Agent?

Every AI CRM vendor selling into 2026 has an AI agent story by now. The differentiator is no longer whether agents exist, but who is allowed to build the next one, how long that takes, and what happens to the bill once it works. For decades, CRM has promised growth and mostly delivered data entry, decaying from a system of action into a system of record. The agentic shift changes that, and with it the questions buyers should ask. Let’s put Creatio’s AI CRM to those questions, following a deal from lead to order to see how much orchestration ships out of the box and how much a revenue team must assemble. The findings are published in full in my report, AI CRM for Revenue Growth: Inside Creatio’s AI-Native No-Code Platform. The company behind the platform Creatio is a privately held, AI CRM and no-code workflow automation company headquartered in Boston, founded in 2014 by Katherine Kostereva, who remains CEO. It ran as bpm’online until a 2019 rebranding, bootstrapped until its first institutional round in 2021. A $200 million round led by Sapphire Ventures in June 2024 lifted its valuation to $1.2 billion; total funding raised now stands at roughly $268 million, and it reported around 50 percent year-over-year revenue growth at the time. Creatio employs around 1,000 people and sells through more than 500 implementation partners worldwide. The company’s partner program has held a 5-star rating in CRN’s Partner Program Guide for eight consecutive years. Customers span more than 100 countries, among them AMD, Colgate-Palmolive, and MetLife, with millions of workflows launched daily. One platform, two studios The...
Fewer Graveyards, Please: Legacy, AI, and the Debt You Cannot See

Fewer Graveyards, Please: Legacy, AI, and the Debt You Cannot See

Every so often a vendor conversation earns the word “useful,” and this one flirts with it. On CRMKonvo #309, Pega‘s Matt Healy walked into a room of skeptics and, refreshingly, did not try to sell AI as pixie dust. He sold governance. Let me explain why that is the interesting part, and where the pitch still needs a second look. First, the setup, because it is absurd. According to Matt, ninety-five percent of Fortune 500s still run a mainframe in some capacity. Roughly thirty thousand organizations are still on Lotus Notes. Healy mentions a government claims system running on hardware funded by a grant from the JFK administration, and a separate agency contracting retirees back out of retirement homes to keep the thing alive. This is the installed base that every “AI-native transformation” slide ignores. TL;DR If you want to watch the full CRMKonvo, please go ahead here (optimized for smartphones) or here (optimized for tablets/computers). Else, be my guest and continue to read. Or do both … The graveyard problem, now with agents Modernization has been on the CIO agenda since CIOs were invented. What changed, is that frontier AI does not mix with data and processes trapped inside sixty-year-old systems. But even worse: if AI lets you build faster, it also lets you fill Alan Trefler’s famous “application graveyard” faster than ever. The Lotus Notes graveyard of the 2000s simply reopens as an agent graveyard, or a Claude graveyard; take your pick of tombstone. Healy does not dodge this. He cites the now-familiar numbers on AI-generated code: roughly eight times more duplicated blocks, double the code churn,...
The Agentic AI Mirage: Why Your ‘Personalized’ Assistant is Working for the Vendor, Not You

The Agentic AI Mirage: Why Your ‘Personalized’ Assistant is Working for the Vendor, Not You

The Ghost of Cluetrain In 1999, the Cluetrain Manifesto famously declared that “markets are conversations.” It was an inspiring, romantic notion that promised to democratize commerce, wresting power from faceless corporate monoliths and handing it back to a sovereign consumer. Fast forward to today, and that conversation has been thoroughly co-opted. What was supposed to be a bilateral dialogue has devolved into an automated, highly-optimized monologue. The emergence of agentic AI, which features autonomous software agents supposedly operating on our behalf, promises a return to that original democratic vision. But let us be honest: is this actually a revolutionary shift, or is it just another iteration of vendor-controlled slop designed to monetize our decisions before we even make them? The dream of conversational commerce was simple: technology enables humans to speak to other humans at scale. Instead, the vendor community realized that humans are expensive, inconsistent, and prone to demanding fair treatment. The corporate response was to replace them with IVR systems, chatbots, and automated messaging. These tools were never designed to foster actual conversations; they were designed to create efficient deflection barriers. Now, we are told that generative AI and agentic systems will change all this by acting as our personal proxies. But will it come true? TL;DR If you want to watch the full CRMKonvo, please go ahead here (optimized for smartphones) or here (optimized for tablets/computers). Else, be my guest and continue to read. Or do both … The Illusion of Agentic Agency During our recent CRMKonvo with Dan Miller, founder of Opus Research, we wrestled with this paradox. We have been apocaloptimists when it comes...
Usage-Based Pricing for Copilot Is Good for Microsoft’s Investors. Read That Sentence Again.

Usage-Based Pricing for Copilot Is Good for Microsoft’s Investors. Read That Sentence Again.

TheStreet ran a piece this week arguing that, of Microsoft’s two Copilot announcements, the shift to usage-based pricing matters more to investors than the DeepSeek flirtation. That read is correct. It is also the tell. Here is what Microsoft actually did. Copilot Cowork, the agent that reaches across Microsoft 365 to run multi-step work on your data, is coming off the flat per-seat add-on and moving onto consumption billing the company calls “Copilot Credits.” Charles Lamanna, who runs Copilot, told Axios the product could not be offered on an unlimited-use basis. The users he pointed to are the ones doing hundreds of tasks a week. He called them “way productive.” And then he said the part vendors normally keep off the slide: their costs go very high. So the most productive users are the expensive ones. Hold that thought, because the whole argument lives there. What “good for investors” is really saying A pricing model earns the label “good for investors” when three things are true. Revenue starts to track cost-to-serve. Revenue scales with consumption instead of sitting flat per seat. And the vendor stops eating the margin on its heaviest users. All three are true here. None of them is a statement about whether a customer got value. That is the gap I want to sit in for a minute. Usage-based pricing meters an input. Tokens, compute, credits, whatever the unit. The customer does not buy tokens because they want tokens. They want a finished report, a resolved ticket, a reconciled spreadsheet. The token count is the cost of producing the outcome, not the outcome. And the relationship...
Don’t Step Into The Platform Trap: What Microsoft Build 2026 Could Mean for Your Next AI Stack Decision

Don’t Step Into The Platform Trap: What Microsoft Build 2026 Could Mean for Your Next AI Stack Decision

Microsoft Build 2026 produced two announcements that, read together, describe something more interesting than the usual conference launch cadence: a plausible scenario in which enterprise AI stack decisions made in the next 12 months could become significantly harder to reverse. The operative word is “could”. Several pieces of the announced architecture are not fully shipping yet. But the direction is clear. The News Microsoft delivered two related announcements at Build 2026. The first came from Jay Parikh, EVP of CoreAI: the model is not the differentiator; the system governing it is. Microsoft’s answer is a six-step loop. Agents are built in GitHub, contextualized with Microsoft IQ, which grounds them in enterprise data from Microsoft 365, core business systems, knowledge bases, and the web, run in Foundry, governed via Agent 365, and continuously improved through a hill-climbing optimization cycle. Agent 365, combined with Entra, Purview, and Defender, catalogues every agent in the estate, regardless of where it was built, and lets IT enforce policy across all of them. The second came from Mustafa Suleyman, CEO of Microsoft AI: seven new MAI models built from scratch, with no distillation from third-party models. MAI-Thinking-1, the flagship reasoning model at 35 billion active parameters, benchmarks at parity with Anthropic’s Claude Sonnet 4.6 on software engineering tasks at significantly lower per-token cost. MAI-Code-1-Flash is integrated natively into GitHub Copilot. MAI-Transcribe-1.5 claims leading accuracy across 43 languages at five times the speed of competing models. Image and voice models complete the family. Alongside the models, Microsoft introduced Frontier Tuning: enterprises can train MAI models on their own workflow data using reinforcement learning environments. The model...