AI Development Review from Dmytro Semonov
As an AI company, we're constantly balancing product development, customer feedback, and market demands. The prior challenge is turning generated ideas into working product releases without slowing the team down. We partnered with Goodface to help develop and expand AIter, our AI-powered marketing platform. The scope covered product development, UX/UI improvements, infrastructure, integrations, QA, and ongoing platform enhancements.What made the collaboration productive was their approach to SDLC. Product requirements, design decisions, development tasks, and QA activities were connected through a single workflow. That meant fewer clarification cycles, fewer stalled discussions, and less time spent coordinating work between teams.Goodface used an AI-orchestrated development model, and the tech behind it wasn't the key. But the team mindset and outcome-driven roadmap. We had visibility into priorities, active workstreams, and upcoming releases without relying on constant status meetings or manual follow-ups. When priorities changed, the team adapted quickly and kept delivery moving.Over the course of the engagement, we increased the pace of product releases while reducing rework between planning and implementation. Features moved through the pipeline with fewer revisions, and our internal team spent more time on product strategy and customer needs instead of managing development processes.Another thing we appreciated was their approach to software delivery. Rather than treating development as a sequence of isolated phases, they built a process where product, design, engineering, and QA could move in parallel. That shortened feedback loops and helped maintain momentum across multiple initiatives.Goodface became an extension of our team rather than an external vendor. The collaboration was transparent, organized, and easy to manage from start to finish.
AI Development Review from Sergio Shanin
We partnered with Goodface to accelerate the development of Pluspoint, our SaaS platform for multi-location businesses and franchise networks.The platform combines review management, directory synchronization, customer engagement, and marketing automation, so maintaining delivery speed while expanding the product requires a disciplined development process.What stood out about Goodface was their AI-orchestrated delivery model. Rather than relying on constant meetings, repeated handoffs, or extensive management oversight, they structured the work so that product requirements, development, QA, and releases remained aligned throughout the project. This reduced the number of clarification cycles, limited rework, and helped us maintain momentum across multiple initiatives.Their team contributed across custom software development, infrastructure, QA, integrations, and ongoing product improvements. We always had visibility into priorities, progress, and upcoming milestones, which made collaboration straightforward for both tech and non-tech stakeholders.As a result, we launched new functionality faster, spent less time revisiting completed work, and maintained a predictable release cadence while continuing to expand the platform.Goodface brought a practical combination of product thinking, engineering discipline, and AI orchestration to the engagement. They didn't just execute tickets; they helped create a delivery process that let our team focus more on product strategy and customer needs, rather than on day-to-day coordination.
AI Development Review from Yaroslav Semeniuk
Goodface served as an accountable software development partner embedded in our delivery process, handling front-end, back-end, QA, and DevOps for a complex eSports platform. Their structured approach to end-to-end product development using AI orchestration reduced rework and overspending, minimized designdev misalignment, and kept delivery on schedule without constant supervision. We had clear visibility into each project stage and could exchange feedback at any time, without the need for frequent meetings or micromanagement. Execution was well-organized, and overall, we achieved greater efficiency and better outcomes with such an AI-orchestrated framework than with previous vendors. We would confidently recommend them.
4.8
4.8
Proposals