MAROKO133 Breaking ai: Echelon's AI agents take aim at Accenture and Deloitte consult

📌 MAROKO133 Update ai: Echelon's AI agents take aim at Accenture and Deloitte

Echelon, an artificial intelligence startup that automates enterprise software implementations, emerged from stealth mode today with $4.75 million in seed funding led by Bain Capital Ventures, targeting a fundamental shift in how companies deploy and maintain critical business systems.

The San Francisco-based company has developed AI agents specifically trained to handle end-to-end ServiceNow implementations — complex enterprise software deployments that traditionally require months of work by offshore consulting teams and cost companies millions of dollars annually.

"The biggest barrier to digital transformation isn't technology — it's the time it takes to implement it," said Rahul Kayala, Echelon's founder and CEO, who previously worked at AI-powered IT company Moveworks. "AI agents are eliminating that constraint entirely, allowing enterprises to experiment, iterate, and deploy platform changes with unprecedented speed."

The announcement signals a potential disruption to the $1.5 trillion global IT services market, where companies like Accenture, Deloitte, and Capgemini have long dominated through labor-intensive consulting models that Echelon argues are becoming obsolete in the age of artificial intelligence.

Why ServiceNow deployments take months and cost millions

ServiceNow, a cloud-based platform used by enterprises to manage IT services, human resources, and business workflows, has become critical infrastructure for large organizations. However, implementing and customizing the platform typically requires specialized expertise that most companies lack internally.

The complexity stems from ServiceNow's vast customization capabilities. Organizations often need hundreds of "catalog items" — digital forms and workflows for employee requests — each requiring specific configurations, approval processes, and integrations with existing systems. According to Echelon's research, these implementations frequently stretch far beyond planned timelines due to technical complexity and communication bottlenecks between business stakeholders and development teams.

"What starts out simple often turns into weeks of effort once the actual work begins," the company noted in its analysis of common implementation challenges. "A basic request form turns out to be five requests stuffed into one. We had catalog items with 50+ variables, 10 or more UI policies, all connected. Update one field, and something else would break."

The traditional solution involves hiring offshore development teams or expensive consultants, creating what Echelon describes as a problematic cycle: "One question here, one delay there, and suddenly you're weeks behind."

How AI agents replace expensive offshore consulting teams

Echelon's approach replaces human consultants with AI agents trained by elite ServiceNow experts from top consulting firms. These agents can analyze business requirements, ask clarifying questions in real-time, and automatically generate complete ServiceNow configurations including forms, workflows, testing scenarios, and documentation.

The technology delivers a significant advancement from general-purpose AI tools. Rather than providing generic code suggestions, Echelon's agents understand ServiceNow's specific architecture, best practices, and common integration patterns. They can identify gaps in requirements and propose solutions that align with enterprise governance standards.

"Instead of routing every piece of input through five people, the business process owner directly uploaded their requirements," Kayala explained, describing a recent customer implementation. "The AI developer analyzes it and asks follow-up questions like: 'I see a process flow with 3 branches, but only 2 triggers. Should there be a 3rd?' The kinds of things a seasoned developer would ask. With AI, these questions came instantly."

Early customers report dramatic time savings. One financial services company saw a service catalog migration project that was projected to take six months completed in six weeks using Echelon's AI agents.

What makes Echelon's AI different from coding assistants

Echelon's technology addresses several technical challenges that have prevented broader AI adoption in enterprise software implementation. The agents are trained not just on ServiceNow's technical capabilities but on the accumulated expertise of senior consultants who understand complex enterprise requirements, governance frameworks, and integration patterns.

This approach differs from general-purpose AI coding assistants like GitHub Copilot, which provide syntax suggestions but lack domain-specific expertise. Echelon's agents understand ServiceNow's data models, security frameworks, and upgrade considerations—knowledge typically acquired through years of consulting experience.

The company's training methodology involves elite ServiceNow experts from consulting firms like Accenture and specialized ServiceNow partner Thirdera. This embedded expertise enables the AI to handle complex requirements and edge cases that typically require senior consultant intervention.

The real challenge isn't teaching AI to write code — it's capturing the intuitive expertise that separates junior developers from seasoned architects. Senior ServiceNow consultants instinctively know which customizations will break during upgrades and how simple requests spiral into complex integration problems. This institutional knowledge creates a far more defensible moat than general-purpose coding assistants can offer.

The $1.5 trillion consulting market faces disruption

Echelon's emergence reflects broader trends reshaping the enterprise software market. As companies accelerate digital transformation initiatives, the traditional consulting model increasingly appears inadequate for the speed and scale required.

ServiceNow itself has grown rapidly, reporting over $10.98 billion in annual revenue in 2024, and $12.06 billion for the trailing twelve months ending June 30, 2025, as organizations continue to digitize more business processes. However, this growth has created a persistent talent shortage, with demand for skilled ServiceNow professionals — particularly those with AI expertise — significantly outpacing supply.

The startup's approach could fundamentally alter the economics of enterprise software implementation. Traditional consulting engagements often involve large teams working for months, with costs scaling linearly with project complexity. AI agents, by contrast, can handle multiple projects simultaneously and apply learned knowledge across customers.

Rak Garg, the Bain Capital Ventures partner …

Konten dipersingkat otomatis.

🔗 Sumber: venturebeat.com

📌 MAROKO133 Breaking ai: Suspect Fantasized About Arson on ChatGPT Before Setting

A man who has been arrested on suspicion of starting the deadly Palisades Fire that destroyed thousands of homes and killed a dozen people in Los Angeles last year allegedly used ChatGPT to generate images of burning forests and cities, according to law enforcement officials.

The suspect in custody, 29-year-old Jonathan Rinderknecht, was arrested near his home in Florida on Tuesday for destruction of property by means of fire, acting US Attorney Bill Essayli told reporters at a press conference on Wednesday.

Federal prosecutors allege that Rinderknecht started an initial eight acre blaze, called the Lachman fire, in the early hours of New Year’s Day. Firefighters initially put out the fire, but it rekindled days later, which prosecutors say eventually grew into the even larger inferno that devoured the Pacific Palisades hillside, causing numerous deaths and hundreds of billions of dollars in damages.

That night before the New Year, Rinderknecht had been working as an Uber driver, prosecutors say in a complaint. Two of his passengers told investigators that he seemed angry and agitated. After dropping off his last customer in the Palisades, Rinderknecht drove to the Skull Rock trailhead, and then walked to a clearing on the hilltop that a friend said he frequently visited. Cell data confirmed his location, the complaint said. While there, he took videos with his iPhone and listened to a French rap song called “Un Zder, Un The,” per the LA Times.

Soon, Rinderknecht turned to an AI chatbot for advice. Shortly after starting the fire after midnight, prosecutors allege, he tried calling 911 several times because of bad reception to report the fire. When he finally got through to an operator, he typed a question into ChatGPT, OpenAI’s chatbot.

“Are you at fault if a fire is [lit] because of your cigarettes,” Rinderknecht allegedly asked the AI model, per an affidavit quoted by the Los Angeles Times.

ChatGPT’s response: “Yes.”

After running from the fire, Rinderknecht claimed he returned to offer firefighters help with the blaze. But investigators argue that he had an ulterior motive. They allegedly found videos on his phone he had taken of firefighters trying to put out the fire, and a screen recording of his phone as he tried to call 911.

The videos and his ChatGPT question suggest “he wanted to create evidence regarding a more innocent explanation for the cause of the fire,” the complaint said, per the BBC.

The investigation also dug into Rinderknecht’s past interactions with ChatGPT. In July 2024, he asked the chatbot to generate an image of a “dystopian painting” that showed a crowd of people running away from a burning forest and trying “to get past a gigantic gate with a big dollar sign on it.”

“On the other side of the gate and the entire wall is a conglomerate of the richest people,” the prompt continues. “They are chilling, watching the world burn down, and watching the people struggle. They are laughing, enjoying themselves, and dancing.”

The resulting images vary, but all of the ones shared in the complaint show either a forest or a city engulfed in flames. One month before the fire, Rinderknecht also confided in ChatGPT that he felt “amazing” and “liberated” after burning a Bible, per the BBC’s coverage.

“You could see some of his thought process in the months leading up, where he was generating some really concerning images up on ChatGPT,” Essayli said at the conference, per ABC News.

Essayli, however, avoided answering questions about Rinderknecht’s possible motives. He also strongly emphasized that the the rap track the suspect was listening to had a music video featuring several objects like a metal trash barrel set on fire — which feels like a stretch, not to mention sounding like the age-old scapegoat of blaming rap music for crime. It also doesn’t appear that Rinderknecht’s prompts asked ChatGPT to depict a burning city; they only described a “burning forest.” The AI, it seems, generated scenes of burning cities on its own.

But if the allegations are true, this wouldn’t be the only time that AI chatbots have been used in deadly crimes. The Green Beret soldier who blew himself up in a Cybertruck outside the Trump Towers hotel in Las Vegas at the beginning of the year — the same day that Rinderknecht allegedly started the fire, in fact — asked ChatGPT to help plan his attack.

The news also comes during mounting concern over reports of “AI psychosis,” disturbing mental episodes in which a person who’s been interacting extensively with an AI chatbot develops severe delusions and suffers breaks with reality. Some of these episodes have ended in trips to the hospital, suicide, and murder, including a man who allegedly killed his mother after ChatGPT strengthened his conviction that she was part of a conspiracy to surveil him.

At this time, just how extensive Rinderknecht’s alleged interactions with the OpenAI product remain unclear — as are his motives.

More on ChatGPT: 13-Year-Old Arrested for Asking ChatGPT How to Kill His Friend

The post Suspect Fantasized About Arson on ChatGPT Before Setting Deadly Fire That Killed 12, Prosecutors Say appeared first on Futurism.

🔗 Sumber: futurism.com