Why are you 30% cheaper than market? Is quality compromised?
Two reasons: fully remote with no office or sales-team overhead, and mature codebases across all 28 AI tracks so we never bill you to reinvent the wheel. Core members come from OpenAI, Google and top-tier Chinese tech; every delivery includes internal review plus a 60-day bug-fix warranty.
Is the quote final? Any mid-project price increases?
No. Before signing we break requirements into a feature list written into the contract at a fixed all-in price. New requirements added mid-project are quoted separately and only proceed with your approval.
Who owns the source code and IP?
You do, 100%. Delivery includes complete source code, deployment docs and technical docs, with the GitHub repo created under your own organization.
Payment methods?
USD settlement or bank transfer. Standard schedule is 30-40-30: signing, mid-project demo, acceptance.
How long does delivery take?
Validation demo in as fast as 12 hours; marketing sites 1-2 weeks, AI product MVP 4-8 weeks, private deployment or model training quoted per scope. Every project starts with a written schedule and milestone-based payments.
What is the relationship between kaifaai.app and 51kaifa.app?
Sister sites: kaifaai.app builds AI products only (agents, RAG, fine-tuning, digital humans, AI MVPs — 28 directions with upfront pricing); Web3 full-stack work (chains, wallets, contracts, dApps) lives on 51kaifa.app. The two sites can cross-deliver. kaifaai.app is invested in by Chainfir Capital.
How do you keep AI agent projects from going off the rails?
Every agent project ships with an eval set: accuracy, hallucination rate and refusal boundaries are all quantified, and delivery includes a reproducible quality report. An agent without evals is superstition — we don't ship superstition.
Can you build small tools like an AI mock-interview app?
Yes. A validation demo takes as fast as 12 hours; single small tools are priced in the $3,800-$9,800 band. Start small, scale once it clicks.
How much does LLM fine-tuning cost?
From $18,800, covering data cleaning, training, evaluation and private deployment — LoRA or full fine-tuning on Llama, Qwen or DeepSeek. Market average is around $28,000.
Fine-tune or RAG — which one do I need?
Fine-tune when you want the model to absorb your phrasing, style and terminology. Use RAG when it must cite documents you keep updating. For most products RAG first is the better deal; fine-tuning usually comes later, once RAG is running well but still falls short. We run both on your real data and let the evaluation scores decide.
How much data does fine-tuning need, and how long does it take?
For style and terminology, a few hundred to a few thousand high-quality samples is enough; for task capability, expect several thousand to tens of thousands. With data in hand, a first evaluable checkpoint lands in 1–2 weeks and an iteration fit to ship in 3–5 weeks. If your data is not organised yet, we handle the cleaning and construction.
How much does it cost to build LLM Fine-Tuning (LoRA / Full)?
$18,800+ (Market $28,000). Fixed scope, fixed price — no surprise add-ons. Written quote within 48 hours.
What exactly does LLM Fine-Tuning (LoRA / Full) cover?
Often you don't need fine-tuning; solid RAG gets there cheaper. When it is the right call, we train Llama / Qwen / DeepSeek on your data and deploy privately, terminology and tone included.
