Drivingan AI startup that automates enterprise software implementations, today emerged from stealth mode with $4.75 million in seed funding led by Bain Capital Ventureswhich targets a fundamental shift in how companies deploy and maintain business-critical systems.
The San Francisco-based company has developed artificial intelligence agents specially trained for end-to-end engagement Service now Implementation – Complex enterprise software deployments that traditionally require months of work by external consulting teams and cost companies millions of dollars annually.
"The biggest obstacle to digital transformation is not the technology, but the time it takes to implement it." said Rahul Kayala, founder and CEO of Echelon, who previously worked at the AI-powered IT company Moveworks. "AI agents completely remove this limitation, allowing organizations to experiment, iterate, and deploy platform changes at unprecedented speed."
This announcement indicates the possibility of disruption in $1.5 trillion global IT services marketWhere you like companies Accenture, Deloitteand Capgemini They have long been dominated by labor-intensive consulting models that Echelon says have become obsolete in the age of artificial intelligence.
Why ServiceNow deployments take months and cost millions
Service nowa cloud platform used by organizations to manage IT services, HR, and business workflows, has become a critical infrastructure for large enterprises. However, implementing and customizing the platform typically requires specialized expertise that most companies lack internally.
The complexity stems from the extensive customization capabilities that ServiceNow provides. 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 research, these applications often extend 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 indicated in its report Analysis of common implementation challenges. "The basic order form turns out to be five orders stuffed into one. We had catalog items with over 50 variables, and 10 or more UI policies, all connected. Update one field, and something else breaks."
The traditional solution involves hiring external 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 external consulting teams
Echelon’s approach replaces human advisors with elite-trained AI agents Service now Experts from major consulting companies. These agents can analyze business requirements, ask clarifying questions in real-time, and automatically create complete ServiceNow configurations including models, workflows, test scenarios, and documentation.
This technology provides a significant advance over general-purpose AI tools. Instead of providing generic code suggestions, Echelon agents understand ServiceNow’s specific architecture, best practices, and common integration patterns. They can identify gaps in requirements and propose solutions that comply with enterprise governance standards.
"Instead of routing each piece of input through five people, the business process owner uploads their requirements directly," Kayala explained, describing a recent client implementation. "The AI developer analyzes it and asks follow-up questions like: “I see a process flow that has 3 branches, but only 2 operators.” Should there be a third? The kinds of things an experienced developer might ask for. With artificial intelligence, these questions came immediately."
Early customers reported significant time savings. A financial services company experienced a service catalog migration project that was expected to take six months It was completed in six weeks Using Echelon AI agents.
What makes Echelon’s AI different from programming assistants?
Echelon’s technology addresses many of the technical challenges that have prevented wider adoption of AI in enterprise software implementation. Agents are trained not only in the technical capabilities of ServiceNow but also in the accumulated experience of senior consultants who understand complex enterprise requirements, governance frameworks, and integration patterns.
This approach differs from general-purpose AI coding assistants such as Github copilotwhich provides syntax suggestions but lacks domain-specific expertise. Echelon agents understand the data models, security frameworks, and upgrade considerations of ServiceNow, knowledge typically gained through years of consulting experience.
The company’s training methodology includes elite ServiceNow experts from consulting companies such as Accenture And a dedicated ServiceNow partner Therdira. This built-in expertise allows AI to handle complex requirements and edge cases that typically require intervention from senior consultants.
The real challenge isn’t teaching AI how to write code, but rather capturing the intuitive expertise that separates novice developers from seasoned architects. Senior ServiceNow consultants instinctively know which customizations will be broken during upgrades and how simple requests can turn into complex integration issues. This institutional knowledge creates a moat that is much more defensible than what general-purpose programming assistants can provide.
The $1.5 trillion consulting market is facing disruption
The emergence of Echelon reflects broader trends that are 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, providing reporting $10.98 billion annual revenue in 2024and $12.06 billion for the trailing twelve months ending June 30, 2025, as organizations continue to digitize more business processes. However, this growth has led to an ongoing talent shortage, as demand for skilled ServiceNow professionals — especially those with AI experience — has dramatically outpaced supply.
The startup approach can fundamentally change the economics of implementing enterprise software. Traditional consulting engagements often involve large teams working for months, with costs increasing linearly with project complexity. In contrast, AI agents can handle multiple projects simultaneously and apply knowledge gained across clients.
Rak Garg, the Bain Capital Ventures partner who led Echelon’s funding round, sees this as part of a larger shift toward AI-driven professional services. "We see the same trend with other BCV companies e.g The safety of the Prophetwhich automates security operations, and Crosbywhich automates legal services for startups. AI is quickly becoming the delivery layer across multiple functions."
Expand beyond ServiceNow while maintaining enterprise reliability
Despite early success, Echelon faces significant challenges in scaling up its approach. Enterprise customers prioritize reliability above speed, and any AI-generated configurations must meet stringent security and compliance requirements.
"Inertia is the greatest danger," Garg admitted. "IT systems should never go down, and businesses lose thousands of productive hours with each outage. Proving reliability at scale and building on repeatable results will be critical for Echelon."
The company plans to expand beyond ServiceNow to other enterprise platforms including Sub, Sales forceand Work day —each creating significant additional market opportunities. However, each platform requires the development of new domain expertise and platform-specific best practice training modules.
Driving It also faces potential competition from established consulting firms that are developing their own AI capabilities. However, Garg views these companies as potential partners rather than competitors, noting that several have already approached Echelon about collaboration opportunities.
"They know that AI is changing their business model in real time," He said. "Clients put enormous pricing pressure on big companies and ask tough questions, and these companies can use Echelon agents to speed up their projects."
How AI agents can reshape all professional services
Echelon’s funding and emergence from stealth represents a major milestone in the application of AI to professional services. Unlike consumer AI applications that primarily improve individual productivity, enterprise AI agents like Echelon’s directly replace skilled labor at scale.
The company’s approach — training AI systems with specialized knowledge rather than just technical documentation — could serve as a model for automating other complex professional services. Legal research, financial analysis, and technical consulting all involve similar patterns of applying specialized expertise to meet unique client requirements.
For enterprise customers, the promise extends beyond cost savings to strategic flexibility. Organizations that can quickly implement and modify business processes gain competitive advantages in markets where customer expectations and regulatory requirements change frequently.
As Kayala pointed out, "This opens up a completely different approach to business agility and competitive advantage."
The implications extend beyond ServiceNow applications. If AI agents can master the complexities of enterprise software deployment—one of the most complex and relationship-dependent areas of professional services—some areas of knowledge work may remain immune to automation.
The question is not whether AI will transform professional services, but how quickly it will transform human expertise into autonomous digital workers who never sleep, never leave for competitors, and become smarter with every project they complete.
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