Product Strategy
We define the product vision, core user journeys, feature roadmap, and monetization architecture before development begins — aligning engineering with business outcomes.
From MVP validation to enterprise-grade platform — Lumo designs, engineers, and ships B2B SaaS products with AI-native features, clean architecture, and the growth infrastructure to scale ARR.
What We Do
Most SaaS products fail not because of bad technology but because of wrong assumptions about what users need. Lumo's SaaS practice starts with product strategy — defining the jobs-to-be-done, the monetization architecture, and the minimum viable feature set that gets to revenue fastest — before writing a line of code.
We build full-stack SaaS applications using modern, scalable architectures: Next.js frontends, Node.js or Python backends, PostgreSQL or Supabase databases, Stripe for billing, and AI feature layers using OpenAI, Anthropic, or Google model APIs. Every decision in our stack is made with maintainability, performance, and cost efficiency in mind.
AI-native features are a standard part of our SaaS builds. Whether that is an AI writing assistant embedded in your product, an intelligent data analysis layer, an automated workflow engine, or a recommendation system — we design the AI architecture as part of the core product, not as a bolted-on afterthought.
Growth infrastructure is built alongside the product. We implement in-app analytics, feature flagging, A/B testing frameworks, user feedback loops, and the observability tooling your team needs to make product decisions based on data. We ship software that teams can measure, improve, and grow over time.
How It Works
We define the product vision, core user journeys, feature roadmap, and monetization architecture before development begins — aligning engineering with business outcomes.
We engineer a clean, scalable full-stack architecture with authentication, billing, database design, and AI feature layers built to production standards from day one.
We ship a focused MVP in 8-12 weeks, get it in front of real users, and collect the feedback data needed to validate assumptions and prioritize the next build cycle.
We analyze usage data, run product experiments, build new features based on user evidence, and scale the infrastructure as your ARR and user base grow.
Common Questions
We build with Next.js, React, Node.js or Python, PostgreSQL/Supabase, and Stripe for billing. AI features use OpenAI, Anthropic Claude, or Google Gemini depending on the use case. We use proven, maintainable technologies rather than bleeding-edge frameworks that create technical debt.
A focused MVP with core user flows, authentication, billing, and 1-2 primary features typically launches in 8-12 weeks. The key to hitting this timeline is disciplined product scoping in our strategy phase — which we require before any development begins.
Yes. AI-native features are a standard part of our SaaS practice. We integrate LLM-powered writing assistants, intelligent data analysis, automated workflow engines, recommendation systems, and custom AI tools as core product features.
Yes. We handle codebase audits, technical debt cleanup, architecture migrations, and new feature development on existing products. We always start with a technical audit to understand the current state before quoting scope.
We design for scalability from day one. Our architectures use serverless functions for elastic scaling, efficient database indexing, CDN-cached assets, and queue-based async processing for heavy workloads. We've built products that scale from 10 to 10,000+ concurrent users without architectural rewrites.
Ready to Build?
Tell us your product vision. We'll turn it into a shipping product with AI-native features and growth infrastructure built in.