About Aruku
Architecture-Led Machine Learning Studio
We are a lean, distributed machine learning studio focused on recommendation systems.
Built on strong software engineering foundations and shaped by developing our own recommendation products, we approach personalisation as a systems engineering problem that has to work within the constraints of real products.
Aruku operates as an architecture-led team working remotely across countries. We collaborate through contract-based engagements, assembling the right expertise for each project.
No office. No overhead theatre. Just focused engineering and structured delivery.
How We Work
Clearly Defined Sprints
Each sprint has a defined scope, timeline, and goal. This keeps delivery focused and results easy to evaluate.
Lean by Design
Our model is intentionally lean. Small teams, clear ownership, and minimal overhead keep the work fast and focused.
Work Within Real Constraints
Live platforms have constraints. We design systems to work within them, fitting your product, your data, and the way your platform actually works.
Good Fit For
Content-Rich Platforms
Tourism sites, event discovery platforms, entertainment guides, and media libraries where users face overwhelming choice.
Small Product Teams
Teams that need expert ML capability without building an entire data science function in-house.
Low-Data Environments
Cold start scenarios, sparse user interactions, or small user bases where pattern-based methods fall short.
Underperforming Personalisation
Platforms where search, ranking, or recommendation logic needs evaluation, tuning, or redesign.
Let’s look at your platform
Choose a structured engagement: 30-day pilot or signal assessment