Research measured in days
Investigating current state and recommending a solution took analysts days, before a single build began.
Customer StoryHow a leading CRM platform made its ServiceNow engineers 5× faster with Echelon.
The company's ServiceNow team turned days of research into minutes and reached 100% analyst adoption. With an AI agent that understands their instance, their strongest engineers could work five times faster.
Inside the ServiceNow team
Company
A leading CRM platformCustomer platform / CRM software
Team model
Hybrid7 engineers2–4 contractors4 dedicated + 10–15 matrixed analysts30+ citizen developers
ServiceNow's role
The front doorCentral intake for every employee across the business
Modules live
ITSMITOMITAMProcurementHRSecOpsLegalSales Ops
The results
What the team achieved with Echelon.
5x
Faster engineering output for all engineers in the team
100%
Analyst adoption almost overnight
Days → mins
Research turnaround to investigate a problem end-to-end
“
[We asked the team], would you rather
renew Echelon or hire another person? Almost without question, renew Echelon.
Stephen Sturdevant
ServiceNow & Enterprise Service Delivery
ServiceNow & Enterprise Service Delivery
The challenge
A mounting backlog on a
decade-old, customized instance.
ServiceNow is the front door for employees across the company, and demand never stops. But a decade-old, heavily customized instance meant research was slow, the backlog kept growing, and budget made “just hire another engineer” a hard sell.
More backlog than headcount
A growing backlog against a budget-capped team meant simply adding headcount was not an option.
A customized instance, 30+ builders
Years of customization: rules, scripting patterns, and naming conventions 30+ builders all had to follow consistently.
“
Context awareness is the thing Echelon has that's genuinely hard to replicate. It knows our instance. That's what everything else is built on top of.
Stephen SturdevantServiceNow & Enterprise Service Delivery
Proving Echelon's worth
Instance-awareness was the unlock.
Echelon first mapped the company's ServiceNow instance. The team then added their standards and internal documentation, giving the agent the context it needed to work within their environment. That understanding gave the team confidence to use Echelon throughout a task, from research through implementation.
Research & discovery
Pulls current state and recommends a solution for a given problem, in minutes, not days.
Builds update sets
Turns the recommendation into clean update sets that follow the team's naming and scripting conventions.
Traceable to production
Every task maps to an update set the team can track from in-progress to pushed to prod.
Who it's for
Unlocking every team member.
Business analysts
Research and build, safely
- Instance research that once took days now takes minutes
- No more queuing for engineers to answer questions
- Self-serve building without learning every instance nuance
- Every change held to the same best-practice standards
Engineers
Accelerate a strong team
- An AI teammate embedded in every workflow
- Troubleshooting, instance questions, and real build work across all modules
- 5x engineering velocity without adding headcount
“
Catalog it has locked down.”
Stephen SturdevantServiceNow & Enterprise Service Delivery
With 30+ citizen developers editing the catalog, their changes often surfaced as problems in testing, pulling engineers into support and rework. Echelon changed who makes those edits, and how cleanly they land.
Before
- Citizen developers make edits or changes to the catalog.
- Those changes surface to the engineering team during testing.
- Engineers spend time supporting and making fixes.
After
- Citizen developers ask Echelon to make the edits.
- Echelon follows the exact instance conventions.
- Engineers make almost zero reviews or revisions.
Adoption across the team
Analysts100%
Adopted fully once research dropped from days to minutes.
Engineers~50%
Climbing as skeptical veterans see the results firsthand.
Team-driven adoption
Analysts went all-in. Then the skeptics came around.
The first real jump came with the analysts: research on a given problem (current state, recommended solution) that used to take days came back in minutes. They adopted it 100%.
Engineers, who've seen automated coding disappoint before, were a tough crowd, but as adoption climbed past 50% and the strongest developers now found themselves moving five times faster, usage accelerated.
Proving it to leadership
Usage you can map to real work shipped.
Exec teams always ask what they're getting for the money. Echelon's dashboards go beyond token counts to show the kind of work being done (research vs. generated code) and map it to the update sets that were actually created.
In the research module, the team can see which pieces Echelon built, which update sets are completed vs. in progress, and whether they've been pushed to production.
“That visibility is what makes the conversation with leadership concrete.”
Work delivered this month
Research & discovery 58%Generated code 42%
41Update sets created
27Pushed to production
Update sets
VPN access requestCatalog item
Pushed to prodOnboarding rescind fixBusiness rule
Pushed to prodAsset intake flowFlow
CompletedAccess review policyUI policy
In progressContinuing to unlock more value
60–40 today, with constant improvements.
Like any AI, the team checks its work. Today, 60% of the work is approved first time, while 40% still needs a small review or revision.
60% great as-is40% review / revise
Catalog edits on autopilotInstance & standards awareness
“
Some of our really strong engineers said this makes them probably five times faster than they would be without it.
Stephen Sturdevant
ServiceNow & Enterprise Service Delivery
ServiceNow & Enterprise Service Delivery
Put Echelon on your instance.
Start with a scoping call. We'll learn your environment, your conventions, and where you want to be, then show you what context-aware AI looks like on your ServiceNow.