We engineer systems thatcompound value.Your growth is our only metric.
Good Faith Labs exists because complex software systems require more than code—they demand architectural thinking, deep domain expertise, and partners who build for longevity, not exits.
Complex problems require deep domain expertise, not just technical skill.
Generic solutions fail when confronted with real-world domain complexity. Understanding the problem space—its constraints, edge cases, and operational realities—matters more than knowing the latest framework. Without domain depth, even excellent code solves the wrong problems.
We invest in understanding your domain before proposing solutions.
What we do
Engineer production-grade systems with proper architecture, scalability planning, and operational excellence. We think in terms of failure modes, edge cases, and maintenance burden—not just happy-path demos.
What we don't
Ship MVP prototypes as “enterprise-ready.” Ignore performance implications until production. Treat technical debt as someone else's problem.
Cross-disciplinary systems thinking
Our technical leads combine software engineering with legal training—an unusual background that creates unique advantages. Law teaches systematic thinking: identifying edge cases, anticipating failure modes, and building robust frameworks that handle exceptions gracefully.
This cross-disciplinary perspective shapes how we architect systems. We approach technical problems with the same rigor lawyers apply to contract design: clear specifications, explicit error handling, and documentation that stands the test of time.
We build what works.
Our software solutions reflect our philosophy: identify genuine problems, build thoughtful solutions, deliver real value.
Slotly
NP-hard constraint optimization at scale
Academic timetabling is a constraint satisfaction problem with exponential complexity. Slotly's AI-powered optimization engine handles multi-dimensional constraints to generate conflict-free schedules in minutes, not weeks. Serving 10,000+ users daily across multiple institutions.
Visit SlotlyJiffy
Domain-specific LLM orchestration for education
Purpose-built AI system with retrieval-augmented generation (RAG) architecture, fine-tuned language models, and multilingual support (English, Hindi, regional languages). Handles admission queries at scale with context-aware response generation and conversation state management.
Express interestWe work with organizations that need engineering depth, not just development speed.
This approach isn't for everyone. If you need an MVP shipped in weeks or want the latest framework trend, we're not the right fit.
But if you're tackling complex technical problems that require architectural thinking, domain expertise, and systems that must perform reliably at scale—then let's talk.
Complex systems require engineers who think aboutfailure modes before writing the first line of code.