Stepan artificial intelligence startup that automates enterprise software deployments, emerged today by stealth with $4.75 million in seed funding led by Bain Capital Venturespointing to a fundamental change in the way companies implement and maintain critical business systems.
The San Francisco-based company has developed AI agents specifically trained to handle end-to-end. Service now Implementations: Complex enterprise software implementations that traditionally require months of work by offshore consulting teams and cost companies millions of dollars annually.
"The biggest barrier 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 an AI-powered IT company. Moveworks. "AI agents are removing that constraint entirely, allowing companies to experiment, iterate, and implement platform changes at unprecedented speed."
The announcement signals a possible disruption of the $1.5 Trillion Global IT Services Marketwhere companies like accent, Deloitteand capgemini have long dominated through labor-intensive consulting models that Echelon says are becoming obsolete in the age of artificial intelligence.
Why ServiceNow Deployments Take Months and Cost Millions
Service nowA cloud-based platform used by businesses to manage IT services, human resources and business workflows, it has become critical infrastructure for large organizations. However, implementing and customizing the platform typically requires specialized expertise that most companies lack internally.
The complexity arises from ServiceNow’s extensive customization capabilities. Organizations often need hundreds of "catalog items" – digital forms and workflows for employee requests, each of which requires specific configurations, approval processes and integrations with existing systems. According to Echelon research, these deployments frequently extend well 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 real work begins." the company stated in its Analysis of common implementation challenges.. "A basic application form turns out to be five applications rolled into one. We had catalog items with 50+ variables, 10 or more UI policies, all connected. Update one field and something else breaks."
The traditional solution involves hiring offshore development teams or expensive consultants, creating what Echelon describes as a problematic cycle: "A question here, a delay there, and suddenly you’re weeks behind."
How AI agents are replacing expensive offshore consulting teams
Echelon approach replaces human consultants with elite-trained AI agents Service now experts from the main consulting firms. These agents can analyze business requirements, ask clarifying questions in real time, and automatically generate complete ServiceNow configurations, including forms, workflows, test scenarios, and documentation.
The technology offers a significant advancement over general-purpose artificial intelligence 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 align with enterprise governance standards.
"Instead of sending each entry through five people, the business process owner directly uploaded his 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 third? The kind of thing an experienced developer would ask. With AI, these questions arose instantly."
Early customers report enormous time savings. A financial services company saw a service catalog migration project that was estimated to take six months. completed in six weeks using Echelon’s artificial intelligence agents.
What makes Echelon AI different from coding assistants?
Echelon’s technology addresses several technical challenges that have prevented broader 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 business requirements, governance frameworks, and integration patterns.
This approach differs from general-purpose AI coding assistants like GitHub CopilotThey provide syntax suggestions but lack expertise in a specific domain. Echelon agents understand ServiceNow data models, security frameworks, and upgrade considerations, knowledge typically gained through years of consulting experience.
The company’s training methodology involves elite ServiceNow experts from consulting firms such as accent and ServiceNow Specialist Partner Third. This integrated expertise allows AI to handle complex requirements and edge cases that typically require the intervention of a senior consultant.
The real challenge is not teaching AI how to write code, but capturing the intuitive experience that separates junior developers from seasoned architects. Senior ServiceNow consultants instinctively know which customizations will be broken during upgrades and how simple requests turn into complex integration issues. This institutional knowledge creates a much more defensible moat than general-purpose coding wizards can offer.
$1.5 Trillion Consulting Market Faces 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 appears increasingly inadequate for the speed and scale required.
ServiceNow itself has grown rapidly, reporting more than $10.98 billion in annual revenue by 2024and $12.06 billion for the trailing twelve months ended June 30, 2025, as organizations continue to digitize more business processes. However, this growth has created a persistent talent shortage, with demand for trained ServiceNow professionals (particularly those with AI expertise) significantly outstripping supply.
The startup’s approach could fundamentally alter the economics of enterprise software implementation. Traditional consulting contracts often involve large teams working for months, and costs increase linearly with the complexity of the project. AI agents, on the other hand, can handle multiple projects simultaneously and apply learned knowledge across clients.
Rak Garg, the Bain Capital Ventures partner who led Echelon’s funding round, sees this as part of a broader shift toward AI-powered professional services. "We see the same trend with other BCV companies such as Security Prophetthat automates security operations, and Crosbythat automates legal services for startups. AI is rapidly becoming the delivery layer for multiple functions."
Scale beyond ServiceNow while maintaining business reliability
Despite initial success, Echelon faces significant challenges in expanding its approach. Enterprise customers prioritize reliability over speed, and any AI-generated configuration must meet strict security and compliance requirements.
"Inertia is the biggest risk," Garg acknowledged. "IT systems should never fail, and businesses lose thousands of hours of productivity with each outage. Demonstrating reliability at scale and leveraging repeatable results will be critical for Echelon."
The company plans to expand beyond ServiceNow to other enterprise platforms, including SAP, sales forceand work day — each of which creates significant additional market opportunities. However, each platform requires developing new domain knowledge and training models on platform-specific best practices.
Step It also faces potential competition from established consulting firms that are developing their own AI capabilities. However, Garg sees these companies as potential partners rather than competitors, and notes that many have already approached Echelon about collaboration opportunities.
"They know that AI is changing their business model in real time." said. "Customers are putting immense pricing pressure on larger companies and asking tough questions, and these companies can use Echelon agents to accelerate their projects."
How AI agents could reshape all professional services
The funding of Echelon and its emergence from stealth marks an important milestone in the application of AI to professional services. Unlike consumer AI applications that primarily improve individual productivity, enterprise AI agents like those from Echelon directly replace skilled labor at scale.
The company’s approach—training AI systems with expert knowledge rather than just technical documentation—could serve as a model for automating other complex professional services. Legal research, financial analysis, and technical consulting involve similar patterns of applying specialized knowledge to unique client requirements.
For enterprise customers, the promise extends beyond cost savings to strategic agility. 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 far beyond ServiceNow implementations. If AI agents can master the complexities of enterprise software implementation (one of the most complex and relationship-dependent areas of professional services), few knowledge work domains can remain immune to automation.
The question is not whether AI will transform professional services, but how quickly human expertise can translate into autonomous digital workers who never sleep, never leave the competition, and get smarter with every project they complete.
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