Rocket-fuelled Software Engineering.

Our services help you build, maintain and scale your backend systems with best-in-class engineering practices.

We have built modular monoliths and decoupled microservices alike. We apply the best practices in software engineering to write clean maintainable code. We help you continue shipping new features without letting tech debt slow you down.

Tech stack we use.

Web Frameworks
Big Data tools
Cloud Platforms
Messaging Systems

Our services.

Group 2366

Own a service/component

Our team will own a particular microservice or a component in your systems. We will architect, build and manage it on production for you.

On demand Software Engineering team

We can embed into your existing team. Our engineers have expertise in Golang, Java, Python, Ruby and web frameworks in these languages.

Refactoring as a service

We can come in like a specialized team and help live-refactor overall system architecture while minimizing downtime and avoiding data loss.

How we do Software Engineering.

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Express intent with code

Focus on design principles

We believe that code should be written for humans to understand first, and then for computers to execute. We strive hard to keep the code clean and maintainable. We do this by following SOLID design principles and borrowing best ideas from Functional and Object oriented programming.

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Close collaboration

Discuss before you build

We like to understand the context in which we operate. This helps us sustain and increase velocity in the long run by avoiding rework. We collaborate closely with the product, business, and operations team to understand requirements better.

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Faster feedback through pairing

Peer-reviewed system design

We create technical design documents to get feedback before writing code. It enforces clarity of thought and creates a shared understanding of the system within the team.

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Use boring and proven technology

Build on stable abstractions

We avoid incidental complexity by building on proven, battle tested components like relational databases, message queues, caches, and practices such as test automation, continuous integration. This helps minimise unknown unknowns.

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It’s not done until it’s on production

Understand systems end to end

We believe in iterating on software that’s in production, used by real users. This eliminates the guesswork in feature building, focus on the requirements end to end and iterate on customer feedback.

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Continuous improvement

Be better than yesterday

We invest in continuous learning and in practicing our craft. We do this through knowledge sharing sessions, meetups, conferences, and learning from fellow community members.

Case studies.


AutoScaling eKYC Machine Learning workloads to 2M+ req/day



Homogenous Monitoring across Cloud and On-premise