Tieran artificial intelligence startup that automates enterprise software deployments, emerged from stealth mode today with $4.75 million in seed funding led by Bain Capital Venturesaiming for a fundamental change in the way companies deploy 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 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 the technology – it’s 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 eliminating this constraint entirely, enabling companies to experiment, iterate, and deploy platform changes with unprecedented speed.”
The announcement signals a possible interruption in $1.5 trillion global IT services marketwhere companies like Accenture, Deloitteand Capgemini Labor-intensive consulting models have long dominated, which 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 companies 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 knowledge that most companies do not have in-house.
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 research, these implementations often 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 noted in its analysis of common implementation challenges. “A basic request form consists of five requests rolled into one. We had catalog items with 50+ variables, 10+ 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: “A question here, a delay there and suddenly you’re weeks behind schedule.”
How AI Agents Replace Expensive Offshore Consulting Teams
Echelon’s approach replaces human advisors with elite-trained AI agents Service now experts from leading consulting companies. 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 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 aligned with corporate governance standards.
“Instead of routing each input through five people, the business process owner directly uploaded their requirements,” Kayala explained, describing a recent customer implementation. “The AI developer analyzes 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 dramatic time savings. A financial services company saw a service catalog migration project that was expected to take six months completed in six weeks using Echelon AI agents.
What Makes Echelon AI Different From Coding Assistants
Echelon’s technology addresses several technical challenges that have hindered the broader adoption of AI in enterprise software implementation. Agents are trained not only on ServiceNow’s technical capabilities, but also on the accumulated experience of senior consultants who understand complex business requirements, governance structures and integration patterns.
This approach differs from general-purpose AI coding assistants like GitHub Copilotthat provide syntax suggestions but lack domain-specific knowledge. 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 Accenture and specialized partner ServiceNow Third. This built-in expertise allows AI to handle complex requirements and edge cases that would typically require the intervention of a senior consultant.
The real challenge is not teaching AI to write code, but rather capturing the intuitive knowledge that separates junior developers from experienced architects. ServiceNow senior consultants instinctively know which customizations will break during upgrades and how simple requests turn into complex integration problems. This institutional knowledge creates a much more defensible moat than general-purpose coding wizards can offer.
The $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 increasingly appears 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 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 qualified ServiceNow professionals – especially those with AI experience – significantly outpacing supply.
The startup’s approach could fundamentally change the economics of implementing enterprise software. Traditional consulting engagements often involve large teams working for months, with costs increasing linearly with the complexity of the project. AI agents, on the other hand, can handle multiple projects simultaneously and apply the learned knowledge to customers.
Rak Garg, a partner at Bain Capital Ventures who led Echelon’s funding round, sees this as part of a larger shift toward AI-powered professional services. “We see the same trend with other BCV companies such as Prophet’s Securitythat automates security operations, and Crosbythat automates legal services for startups. AI is quickly becoming the delivery layer for multiple functions.”
Go beyond ServiceNow and maintain enterprise reliability
Despite early success, Echelon faces significant challenges in scaling its approach. Enterprise customers prioritize reliability over speed, and any AI-generated configurations must meet strict security and compliance requirements.
“Inertia is the biggest risk,” Garg acknowledged. “IT systems should never go down, and companies lose thousands of man-hours of productivity with each outage. Proving reliability at scale and developing 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 creating substantial additional market opportunities. However, each platform requires the development of new domain knowledge and training models on platform-specific best practices.
Tier 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 many have already approached Echelon about collaboration opportunities.
“They know AI is changing their business model in real time,” he said. “Customers are putting immense price 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
Echelon’s funding and exit from stealth marks a significant milestone in the application of AI to professional services. Unlike consumer AI applications, which primarily improve individual productivity, enterprise AI agents like Echelon directly replace skilled labor at scale.
The company’s approach – training AI systems based on 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 involve similar patterns of applying specialized knowledge to specific client needs.
For business customers, the promise goes 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 noted, “This opens up a completely different approach to business agility and competitive advantage.”
The implications go far beyond ServiceNow implementations. If AI agents can master the complexities of enterprise software deployment – 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 knowledge can be converted into autonomous digital workers who never sleep, never leave for competitors, and get smarter with every project they complete.
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