Question 1

What does Inqodo specialize in?

Accepted Answer

Inqodo is an AI SaaS development agency that builds production-ready, full-stack web applications powered by AI. We specialize in custom LLM integrations, SaaS platforms, MVP development, and enterprise AI automation — primarily for founders and startups in the US, UK, and Europe.

Question 2

What types of AI applications does Inqodo build?

Accepted Answer

We build AI chatbots, RAG (Retrieval-Augmented Generation) pipelines, document processing tools, AI companion apps, automated workflows, computer vision systems, and full SaaS platforms with OpenAI and Anthropic API integrations.

Question 3

How much does it cost to build an AI SaaS product?

Accepted Answer

The cost to build an AI SaaS depends on scope, features, and complexity. A lean MVP typically starts from $3,000–$8,000. A production-ready SaaS with auth, payments, AI integration, and admin dashboard typically ranges from $8,000–$25,000. We provide detailed scoping estimates before any work begins.

Question 4

How long does it take to build an AI SaaS MVP?

Accepted Answer

A focused MVP with core features typically takes 3–6 weeks from kickoff to deployment. More complex platforms with multiple AI pipelines, third-party integrations, and enterprise-grade infrastructure take 8–16 weeks. We work in 2-week agile sprints with live staging links throughout.

Question 5

What are the monthly running costs of an AI SaaS application?

Accepted Answer

Monthly infrastructure costs for a typical AI SaaS range from $50–$500/month depending on user volume, AI API usage, and hosting setup. A small MVP on Vercel and Supabase with moderate OpenAI usage can run under $100/month. We help clients optimize API costs and choose the right infrastructure from the start.

Question 6

How do I hire Inqodo to build my AI product?

Accepted Answer

Start by booking a free strategy call through our consultation page. We'll review your idea, ask the right questions, scope the project, and send a detailed proposal within 48 hours. No commitment required for the initial call.

Question 7

Does Inqodo work with non-technical founders?

Accepted Answer

Yes — the majority of our clients are non-technical founders with a product idea but no engineering team. We handle the full technical lifecycle: architecture, development, deployment, and post-launch support. You don't need to know how to code to work with us.

Question 8

Can Inqodo integrate AI into my existing product?

Accepted Answer

Yes. We regularly integrate OpenAI, Anthropic Claude, and other LLM APIs into existing platforms. Whether you need a chatbot, document analyzer, AI-generated content feature, or automated workflow — we can build the integration without rebuilding your entire product.

Question 9

Do you offer ongoing maintenance and support after launch?

Accepted Answer

Yes. We offer monthly retainer plans that cover feature updates, bug fixes, server monitoring, and infrastructure scaling. Most clients continue with us post-launch as their outsourced technical team.

Question 10

What tech stack does Inqodo use to build AI SaaS products?

Accepted Answer

Our core stack is Next.js, TypeScript, Supabase (PostgreSQL), Clerk for authentication, Stripe for payments, and Vercel for deployment. For AI we work primarily with Anthropic Claude and OpenAI APIs, LangChain for agent workflows, and custom RAG pipelines for enterprise data.

Question 11

Where is Inqodo based and what time zones do you work in?

Accepted Answer

Inqodo is headquartered in the UK with clients primarily in the US, UK, and Europe. Our team operates across flexible hours with guaranteed overlap during US Eastern and UK business hours. All communication is in English and we use Slack, Notion, and GitHub for full project transparency.

Question 12

How is Inqodo different from hiring a freelancer on Fiverr or Upwork?

Accepted Answer

A freelancer delivers code. Inqodo delivers a product. We handle architecture decisions, infrastructure setup, deployment, security, scalability, and post-launch support — not just the front-end UI. We've shipped 30+ live AI products and our clients typically come back for Phase 2 because the foundation we build is solid enough to scale on.

Question 13

Why does Inqodo use Supabase instead of Firebase or AWS?

Accepted Answer

Supabase gives us the speed of a managed BaaS with the power of a real relational PostgreSQL database — critical for complex SaaS data models. It's open source, scales well, and avoids vendor lock-in. For enterprise clients we also deploy on AWS and Oracle Cloud.

Inqodo Blog

Next.js for SaaS Development: Pros and Cons in 2026

White Label SaaS Development Guide: Build & Scale in 2026

AI SaaS Development Guide for Startups in 2026

Supabase vs Firebase for SaaS Development: 2026 Guide

What Is an MVP? Minimum Viable Product Explained for Founders

How to Validate Your SaaS Idea Before Building in 2026

SaaS Churn Rate: How to Reduce It in 2026 (Proven Tips)

SaaS Architecture Design for Non-Technical Founders Guide

SaaS Onboarding Best Practices: 12 Proven Strategies

SaaS Pricing Models: Which One Is Right for Your Product?

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