About

Founder-led consulting for businesses that need systems they can actually use.

boolat is built by data engineers and product-minded builders. We help small and medium businesses improve operations through practical data and digital systems.

Founder introduction

I work directly with businesses to design systems that are practical, usable, and built for real operations.

Our background spans Azure data engineering, analytics, AI/ML work, startup development, and practical business systems. That mix helps us solve both technical and operational problems without overcomplicating delivery.

How we solve business problems

Start with operations
We map how your team currently works, where time is lost, and where decisions get blocked.
Build what gets used
Dashboards, pipelines, and tools are shaped around real workflows, not slideware requirements.
Keep systems practical
We avoid unnecessary complexity so your team can maintain and evolve what we deliver.
Measure outcomes
Success is tracked through reporting speed, data trust, and decision quality.

Why this consultancy exists

Many SMEs sit on useful data but still run key decisions on fragmented spreadsheets and disconnected tools. We started this consultancy to close that gap with practical systems that improve day-to-day execution.

You work directly with the people designing and building the solution. That keeps communication clear, timelines realistic, and outcomes aligned with your business.

Direct founder involvement from planning to delivery
Clear scope and pragmatic implementation
Documentation and handover your team can use
At a glance
Leadership modelFounder-led delivery
Typical focusData + operations
Client typeSmall and medium businesses
Working style
  • Clear communication over consultancy jargon.
  • Useful outputs over impressive complexity.
  • Steady progress with measurable milestones.
R&D mindset

Built on real data experience.

Our analytical approach is grounded in work on AI-related health data that required combining sensor, activity, and environmental data under real-world constraints.

Real-world inputs

Worked with sensor, activity, and environmental data across different quality levels.

Practical modeling

Balanced model ambition with data constraints, reliability, and usability.

Meaningful outputs

Kept focus on decision-support outputs that people can interpret and act on.

We apply the same discipline in SME consulting: practical data foundations, realistic system design, and reporting that supports better business decisions.

Ready to strengthen your data and systems foundation?

Share your current data, reporting, and integration challenges. We will define a practical first phase with clear technical and business outcomes.

Outcome-first
Business outcomes tied to technical execution.
Engineering rigor
Reliable pipelines, integration, and reporting workflows.
Operational fit
Designed for SME teams, cloud or on-premise.