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When you build backend systems across dozens of startups, patterns start to emerge.
At TLVTech, speed matters—but so does stability. Startups need to ship fast, iterate without breaking things, and scale without rebuilding their entire backend from scratch.
We’ve refined a tech stack that consistently delivers all three. It’s not about hype—it’s about choosing tools that get out of the way and let teams focus on product.
Here’s the stack we use, why it works, and where we adjust based on use case.
We default to Node.js with TypeScript for most backend services.
Why it works:
We’ll use Python for ML/data pipelines or Go for high-performance cases—but Node/TS is our go-to for API-centric products.
NestJS gives us the best of both worlds: fast setup + enterprise-level structure.
Why it works:
For simpler services, we may go with Express. But NestJS hits the sweet spot for most production backends.
Postgres is rock solid. It's our default unless the use case says otherwise.
Why it works:
We may bring in Redis for caching, MongoDB for unstructured data, or DynamoDB for specific scaling needs—but Postgres carries most of the load.
We build everything container-first.
Why it works:
We adapt based on team size, traffic needs, and deployment maturity—but the principles stay the same.
Simple, integrated, and customizable.
Why it works:
We keep pipelines fast and predictable. Every commit should be shippable. No manual deploys, no broken main branches.
You can’t fix what you can’t see.
Why it works:
We build dashboards that give teams visibility from day one. No waiting for a fire to realize you need alerts.
Startups don’t have time to experiment with unproven tools. This stack lets us move fast, stay clean, and grow without surprises.
If you're building something and want backend speed without technical debt, let’s talk.
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- Agile methodology is a flexible, user-oriented approach to software development, emphasizing teamwork, feedback, and short work cycles called sprints. - Adopted in 2001, Agile's principles prioritize people and interactions over tools, working software over documentation, embracing change, and sustainable work pace. - Agile's lifecycle includes defining a vision, developing a roadmap broken into features, then allocating features to a backlog for development during sprints. User stories help shape features from a user's perspective. - Agile differs from traditional waterfall and CMM methodologies, focusing on adaptability and continuous iteration. - Agile methods include Scrum, Kanban, Lean, Extreme Programming, and Feature-Driven Development. - Real-life examples of Agile implementation include Spotify and Philips in healthcare. Amazon uses Agile in developing their AWS services. - Transitioning to Agile involves training, starting small and communicating continually. For scaling Agile, practices like the Scrum of Scrums and frameworks like SAFe are effective. - Agile tools aid in tracking progress and fostering teamwork. They utilize techniques like Test-Driven Development and aid in creating estimates using burn-down charts. - Agile proves effective in improving product quality, reducing risks, increasing customer satisfaction, and providing faster ROI.
