November 5, 2025
Redefining what’s possible with Maia
What if a two-person data team could outdeliver a department of ten – without hiring, without consultants, and without burning out? Edmund Optics proved it's possible.
TL;DR
Edmund Optics’ two-person data team was struggling with a critical marketing pipeline that stalled for a year, cost $50K in failed efforts and left marketing waiting on critical ROI visibility to guide their campaigns.
By leveraging Maia, the AI Data Automation platform, the team were finally able to build a fully functional pipeline in hours instead of weeks, 3x output, and avoided hiring an extra engineer. With Maia on the team, they’re now able to take-on bigger challenges, including supporting a major upcoming ERP system migration – while reducing consulting spend by $100K.
Lean teams can now deliver enterprise-scale outcomes faster, smarter, and more efficiently.
Challenge
Edmund Optics, a global manufacturer of precision optical components and imaging products, powers cutting-edge technologies across industries – from autonomous vehicles and barcode scanners to biomedical research and industrial automation.
With 34,000 SKUs and a significant digital marketing budget, every data decision counts.
Supporting this high-velocity business is a lean but ambitious analytics team led by Daniel Adams, Global Analytics Manager, and Anthony Wheatley, Analytics Engineer. Their mission: enable better decisions across marketing, sales, and operations, optimizing marketing spend, providing accurate forecasts, and delivering insights to executives – all with just two engineers.
“We were a small team trying to move at enterprise speed,” says Daniel. “I was planning to bring in new engineers just to keep up. Then we started using Maia.”
Challenge
The Breaking Point: A Critical Pipeline That Wouldn’t Ship
The team faced a year-long roadblock: a marketing automation pipeline that should have unified every digital channel, connected spend to revenue, and guided smarter investment. Instead, it stalled repeatedly:
- Internal build #1 – ran for a week, then failed
- Consultants – delivered after four weeks, ran for a month, then broke
- Specialist vendor – partial data only, high ongoing cost
The total wasted investment was roughly $50,000, with no usable dataset. On top of that, always-on campaigns continued to spend budget while the team waited for the visibility to fine-tune performance. Without this pipeline, Daniel says, “we were flying without much vision or foresight as to where our dollars were best spent.”
Resolving it would allow the team to optimize marketing spend, improve efficiency, reduce waste, and generate actionable insights for the leadership team.
Approach
From Experimental to Essential
Daniel and Anthony had already seen the promise of AI with earlier Matillion product enhancements, but Maia – a fully agentic, context-aware AI Data Automation platform– changed the game.
Maia doesn’t just generate code, it explains logic, documents pipelines, iterates, and debugs. “It handles all of the boring, time-consuming elements of data engineering for you and allows you to focus on the really difficult parts of the job,” adds Anthony.
By the end of the afternoon, a pipeline that had been a year-long obstacle was fully operational thanks to Maia. “Something that would have taken him a week or two is taking him a day or even just an afternoon,” Daniel notes.
Approach
The Freedom to Do More (Without Growing Headcount)
For data leaders under pressure to deliver more with less, this is the new reality: AI doesn’t replace engineers – it amplifies them.
By using Maia to automate the heavy lifting, Daniel’s team saw:
- 2–3x productivity boost across pipeline development
- 10x speed increase for their senior engineer
- $100K saved in consultancy and service spend
- Faster delivery of new data products
- No additional headcount required
“We’re easily able to triple or quadruple our output in terms of data engineering pipelines. Just one experienced engineer in that tool can do the work of a team of five or ten people,” Daniel explains.
Results
Enabling Strategic Business Outcomes
The results aren’t just operational – they’re strategic. With Maia, Daniel and Anthony can tackle projects previously deemed out of reach.
For example, their next challenge: a major systems migration – a massive undertaking with hundreds of existing SQL stored procedures and code that needs to be rewritten, pipelines that need to be rebuilt, and reports that need to be repointed. Before Maia this would have been outsourced at enormous cost. Now, it’s within their control.
“Maia gives us the confidence to tackle the biggest projects this company has faced from a data perspective in the last decade,” says Daniel.
And Maia hasn’t just changed workflows; it’s changed perception. Internally, Daniel’s team is now seen as the one that can “figure things out and get things done.”
Their success highlights a bigger shift happening across data organizations: AI-augmented engineering is enabling small, agile teams to achieve enterprise-scale results.
Results
Why Maia Performs Differently
For Edmund Optics, Maia stands apart because it's not a feature; it’s a platform:
- Maia Team: AI agents that autonomously build, modify, optimize, and maintain pipelines.
- Context Engine: Captures business rules, architecture standards, and governance requirements so automation stays aligned with enterprise reality.
- Maia Foundation: The secure, governed infrastructure where autonomous execution happens with enterprise rigor.
“Maia is like having a team of junior data engineers who never sleep”, Daniel notes.With its visual interface, Maia lets humans collaborate with AI in real time, seeing, adjusting, and perfecting pipelines instantly – turning hours of coding into minutes of clear, manageable work.
Key Takeaway for Data Leaders
The real value isn’t just in faster pipelines – it’s in shifting the role of data engineering itself. “Maia’s supercharged our data team. We can get more done, tackle more complex projects, and unlock more data for more people,” says Daniel. Edmund Optics proves what’s possible when small, agile teams are augmented by AI: higher productivity, faster delivery, and strategic influence – all powered by Maia.
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