Your Technical Partner Beyond the Code

Project timelines vary based on scope and complexity. A simple MVP might take 6-8 weeks, while a full enterprise application could take 4-6 months. During our initial consultation, we'll provide a detailed timeline based on your specific requirements.

We lead with fixed-price, productized engagements rather than open-ended hourly billing. Most clients start with a paid AI Readiness Audit — a fixed-price engagement that delivers a concrete, buildable plan you own, whether or not you go on to build it with us. From there, integration and build work is quoted as a fixed-scope proposal, with most engagements falling between $10,000 and $100,000+ depending on scope. You'll know what you're paying before we start — no open-ended retainers required.

Yes, we offer comprehensive post-launch support including bug fixes, feature enhancements, security updates, and performance optimisation. We can set up monthly retainer agreements or provide support on an as-needed basis.

Absolutely. We frequently collaborate with in-house teams, either augmenting their capacity or bringing specialised expertise. We're flexible in our approach and can adapt to your existing workflows and tools.

Our core stack includes React, Next.js, TypeScript, Node.js, Python, and cloud platforms like AWS and GCP. We also build AI-powered products using OpenAI, Anthropic Claude, LangChain, and vector databases like Pinecone and pgvector. We're technology-agnostic and always choose the right tool for the job — including React Native for mobile.

Scope changes are normal — especially in fast-moving businesses. We use agile workflows with regular checkpoints, so we can adapt quickly without derailing timelines or budgets. We'll flag trade-offs early so you can make informed decisions.

Seriously. We sign NDAs before every engagement and all intellectual property belongs to you. We've worked with publicly listed companies and early-stage startups alike — discretion is non-negotiable.

We build for that outcome. Clean, documented code with proper handover processes. Our goal is to make you stronger, not dependent. Many clients transition to in-house teams using the foundations we built.

AI integration is the core of what we do. We've shipped LLM features, AI agents, and RAG pipelines in our own production products — which is why we know the difference between a demo that works once and something that survives real users. Using OpenAI, Anthropic Claude, LangChain, and related tooling, we make AI work inside real systems, not just in a notebook. Whether you need to add AI to an existing product or build an AI-native application from scratch, we scope it, build it, and stand behind it.

Yes — this is one of the most common ways clients come to us. Founders and teams prototype the first 80% themselves, then hit the wall: it won't integrate, won't scale, leaks secrets, or can't be debugged because no one fully understands the generated code. We take it from there and make it production-grade — clean architecture, proper testing, and documentation your team can own. You keep the momentum; we remove the risk.