For 17 years, Monetate has helped global brands personalize digital experiences. Billions of events move through their platform daily, shaping how customers see and engage.
As AI became central to Monetate’s next phase of growth, the team saw an opportunity to move faster and deliver more value to customers.
For CTO Austin Rochford, the question was straightforward: “How do we expand engineering capacity in a way that increases velocity, not complexity?”
Hiring internally would take time. Expanding through traditional offshore models could add coordination overhead. At Monetate’s scale, even small inefficiencies can slow momentum.
Austin was not looking for additional developers. He was looking for a partner who could embed into the team, accelerate AI and UI initiatives, and help the organization move forward with confidence.
That search led to AccelOne.
Monetate initially engaged AccelOne to accelerate delivery across AI and UI initiatives. The scope was defined. The expectation was timely execution against an existing roadmap.
Onboarding moved quickly. Within two weeks, senior engineers were embedded across teams.
As integration began, something shifted.
Rather than simply delivering against the initially scoped plans, AccelOne engineers reviewed the architecture, sequencing, and assumptions behind the work. They asked practical questions, suggested alternatives, and identified ways to further streamline execution while improving long-term maintainability.
Austin describes it this way:
“Very quickly as they were onboarding, they surveyed our project plans and gave feedback that improved them. Like If we do these things differently, we can get to market faster. Or if we take a different approach here, it will result in delivering higher quality software to your customers.”
That early collaboration changed the trajectory.
Initiatives that had been forecasted for late this year, or even early next year, are now on track to ship in weeks. The improvement was measurable. It also reshaped how work was planned going forward.
The engagement shifted from added capacity to embedded engineering leadership.
Speed of onboarding helped. Seniority helped.
But the operating model really made the difference.
AccelOne’s nearshore teams in Latin America work in the same time zones as Monetate’s U.S.-based teams. Architecture discussions happen during shared working hours. Feedback loops stay tight. Decisions move forward without delay.
As Austin notes:
“Time zone alignment means we can be more agile and nimble, make decisions quickly and execute on them.”
That alignment translated into integration. Engineers did not feel external. They felt part of the team.
Even Monetate engineers who were not directly working with AccelOne began seeing their own roadmaps move faster.
When asked to summarize the partnership, Austin put it simply:
“Joined at the hip to drive outcomes for our customers.”
The result was not just faster delivery, but stronger alignment around how Monetate builds and evolves its platform.
For Monetate, AI was not a side initiative. It was becoming central to how the platform will continue to evolve.
The partnership extended beyond individual features and expanded into how the software was created. Together, the teams accelerated work across the development lifecycle. AI was applied where it created leverage, while enterprise guardrails remained firmly in place.
AI supported engineering teams in:
Front-end framework migrations
Writing first-draft tests
Reviewing pull requests
Generating code suggestions
Handing off these tasks to AI allowed senior engineers to focus more time on architecture, edge cases, and customer-impacting decisions.
Quality remained non-negotiable.
AI-generated code makes QA more important than it ever was before. Companies still require enterprise-grade guardrails.
AI also began supporting the QA function directly. Automation expanded and testing cycles tightened. Human reviewers could then focus on nuanced scenarios that require their judgment.
As Austin puts it:
“AI helps our QA team get from zero to 85 percent of their job much faster, so they can focus on the 15 percent where they add real value.”
The outcome enabled operational acceleration without sacrificing discipline.
The results were visible quickly.
Initiatives that had been forecasted for delivery later this year or beyond are now progressing in weeks. Hiring cycles have compressed from six to eight weeks internally down to only two weeks through AccelOne’s senior talent network.
More importantly, the impact was structural:
Lower coordination overhead
Real-time collaboration across time zones
Faster AI adoption across teams
Greater leverage per engineer
Monetate influences billions of customer interactions every day. Improvements move through the system quickly. So do inefficiencies.
By embedding senior engineers who could contribute strategically from day one, Monetate increased velocity without increasing management complexity.
As the early AI and UI initiatives gained traction, the collaboration expanded. AccelOne is now contributing not only to delivery, but to roadmap planning across AI, machine learning, and user experience initiatives.
Austin describes the ongoing dialogue as productive and forward-looking:
“As we work through these initial projects, having the teams weigh in on what the roadmap should look like next has been very productive. We’ve gained a great set of partners and feedback voices inside of AccelOne.”
The partnership now operates at two levels:
Accelerating current initiatives
Informing future direction
For a platform operating at this level of complexity, that alignment matters.
Monetate’s goal was simple: Accelerate AI and UI initiatives without slowing the organization down.
What ultimately emerged was a partnership that increased leverage across the entire business.
Senior engineers were embedded quickly. Roadmaps moved faster. AI became part of daily workflows. Collaboration tightened across teams and time zones.
The engagement reduced friction and increased output.
And the relationship continues to expand, with AccelOne contributing to long-term direction beyond the initial delivery.
At this level of complexity, sustainable acceleration is not about adding more people. It’s about embedding partners who raise the standard of how the work gets done.