How Long Does It Take to Build an AI App?

LLM integration, RAG, and streaming — AI product development timelines.

Start your project →

Week-by-week timeline

LLM integration

Week 1

✓OpenAI / Anthropic API integration
✓Streaming response setup
✓System prompt engineering
✓Token usage tracking

🏁 Working LLM integration in staging

Product features

Week 2

✓RAG pipeline (if needed)
✓Conversation history persistence
✓Usage limits per plan
✓Stripe billing integration

🏁 Full product working

Production

Week 3

✓Rate limiting and abuse protection
✓Cost monitoring and alerts
✓Caching for repeated prompts
✓Production deployment

🏁 Live AI product

What affects the timeline

RAG complexity

Simple Q&A with documents: 3–5 days. Multi-source RAG with hybrid search: 1–2 weeks. Complex knowledge graph retrieval: 3–4 weeks.

Streaming

Server-Sent Events for streaming: 1–2 days. Non-streaming (waiting for full response) is simpler but produces poor UX for long responses.

Document processing

PDF/DOCX parsing: 1–2 days. OCR for scanned documents: 3–5 days. Enterprise document formats (Excel, PowerPoint): 3–5 days each.

Multi-modal

Image inputs with GPT-4 Vision: 1–2 days. Voice input/output (Whisper + TTS): 2–4 days. Video analysis: 1–2 weeks.

Timeline comparison

Option	Timeline	Notes
Our agency (specific use case)Us	2–3 weeks	Focused AI SaaS with billing and usage limits
Freelancer	1–3 months	AI expertise varies widely
No-code AI builders (Voiceflow, etc.)	1–3 days	Limited to their templates — not a real product
In-house ML team	3–6 months	Custom models — overkill for LLM wrappers

Frequently asked questions

How much does it cost to run an AI app in production?

GPT-4o costs ~$2.50/1M input tokens + $10/1M output tokens. At 1,000 users doing 10 queries/day of ~1,000 tokens total: $0.005 × 10 × 1,000 = $50/day = $1,500/month. Price subscriptions at $20–$50/month to cover API costs + margin. Use our API cost calculator to model your exact numbers.