Velway AI Solutions

BACKGROUND

Introduce your business and what you do there.

I’m the CEO of Pitaya, a swimwear brand with its own manufacturing in Ukraine.

OPPORTUNITY / CHALLENGE

What challenge were you trying to address with Velway AI Solutions?

We needed more than an e-commerce tool. We run our own production, and standard ERPs didn’t fit how a small on-demand garment manufacturer actually works. Our goal was to build one operating system for the whole company instead of running production, inventory, and sales through separate spreadsheets and manual tracking.
Specifically, we wanted a single source of truth for production and warehouse data, less manual data entry for the team, and a structure that supports our on-demand production model as we scale — without adding admin headcount.

SOLUTION

What was the scope of their involvement?

Velway AI Solutions has designed and built our internal operating system. The work started with a discovery phase, mapping our production, warehouse, and sales processes end-to-end. Based on that, the team has designed and built a custom web-based ERP covering production planning, inventory and warehouse accounting, and sales analytics, with automation replacing most of the manual data entry.
Velway AI Solutions has also handled the process redesign around the system, not only the software itself. The architecture and product logic of the system were defined on our side — I acted as the product owner, and the operating model behind it is ours.
Velway AI Solutions has handled the implementation, starting with the production module, which is the core of our on-demand model, followed by raw materials warehouse accounting. Further modules on our roadmap — finance and P&L, task tracking linked to payroll, and marketing analytics — build on that foundation, and we continue developing the platform as part of our internal roadmap.

What is the team composition?

We’ve worked with 2–5 teammates from Velway AI Solutions.

How did you come to work with Velway AI Solutions?

I worked directly with Dariia (CEO) on building our internal operating system for production, and she later co-founded Velway AI Solutions.

What is the status of this engagement?

We started working with Velway AI Solutions in September 2025, and our engagement is ongoing.

RESULTS & FEEDBACK

What evidence can you share that demonstrates the impact of the engagement?

The production module is now used by our team in day-to-day work, and it has replaced a large part of the manual tracking we did before. The main outcome so far is structural: we have one system as the foundation for the next modules, instead of scattered spreadsheets. We’re still in the process of building on it, so it’s early to give final numbers.
Since moving our operations into our internal system, our internal estimates show production errors down by around 30%, raw materials stock planning roughly 35% more predictable, and logistics dispatch about three times faster thanks to automation. We’ve also brought HR tracking into the system, as well as finance, which previously ran on an external service.
It’s still early — several modules are in their final rollout phase — so these are internal estimates rather than a formal audit. Two examples of improvements are order changes and B2B documentation. Order changes — size, color, or pattern — used to reach the cutting team through messengers or verbally, so updates sometimes got lost, and we ended up re-sewing items.
Now, order data flows directly into production, so the team works from the current version. Regarding B2B documentation, invoices used to be built manually in Word or Excel, with product descriptions translated into English by hand and customs codes added each time. Now, commercial and logistics invoices are generated from the order automatically, with English descriptions and customs codes already in place.

How did Velway AI Solutions perform from a project management standpoint?

Communication is open, and the work is organized around a shared roadmap with clear module priorities. Some timelines have shifted along the way — partly because the scope has grown as we’ve discovered new requirements in live production, which is natural for a custom system like this. For us, the important part is that priorities have stayed transparent, and we can adjust the plan together.

What did you find most impressive about them?

Their business-first approach is impressive. Dariia always starts from processes and how the team actually works, not from technology. She maps the workflow first and only then discusses what to build. Dariia also asks uncomfortable but useful questions: who the end user is, what problem a feature really solves, and whether something is worth building at all. For a custom system in a live production environment, that kind of thinking matters more than coding speed.

Are there any areas they could improve?

Nothing major comes to mind. The collaboration has been constructive throughout, and whenever something needs adjusting, we work it out together quickly. I’d happily continue working with this kind of approach.