AI credits payment model

How the system works: Credits as AI currency 1 credit = 1 USD. Every AI action consumes a certain number of credits.

Factors and parameters affecting credits and cost:

• LLM Model: Gemini 2.5 Flash, GPT 5.0, Claude Sonnet 4.5, etc. The more powerful the model, the more credits are consumed.

  • Example: Gemini 2.5 Flash may spend around $0.01 per session, while GPT 5.0 may spend $0.04 per session.

• LLM Model Instructions: These are pre-written instructions used by the model automatically in every session. The more detailed the instructions for the assistant, the more credits are consumed.

You are the AI shopping assistant for a tech e-commerce website. 
Your role is to help customers with questions about smartphones and prices. Do not answer off-topic questions, always try to talk about smartphones.

Rules:
- Always give clear, friendly, and professional answers. 
- Answer in the same language the customer uses (Georgian or English).
- If you don’t know something (like real-time stock or prices), politely say so and suggest 
the customer check the website or contact support. 
- Keep answers short and to the point (2–5 sentences). 
- Do not invent product details or prices that are not provided. 
- If a customer asks something not related to the shop (like history of iPhones), 
you may answer briefly (Really short answer), but always guide them back to shopping context.
- Avoid unnecessary long texts, use concise explanations.

Input Tokens – The length of the user’s message.

• Example: A longer message consumes more tokens, and therefore more credits.

Output Tokens – The length of the AI-generated response.

• Example: Longer responses consume more credits.

Knowledge Base Size –

• Example: This can be a short description of the company and frequently asked questions, or for e-commerce, a full product database with quantities, prices, etc.

• The larger the knowledge base, the more tokens are used, which affects credit consumption.

Example of Usage – How the Price is Calculated

Scenario:

• An organization with 1000 chat sessions per month

• Each chat averages 5–10 user questions

• Selected model: Gemini 2.5 Flash (fast, balanced in cost and quality)

• Integrated knowledge base: contains FAQs, team info, products, and company description

Result:

• Each chat session consumes approximately 0.10–0.15 credits (i.e., $0.10–$0.15)

• Monthly cost for 1000 chats: approximately $100–$150

• This price is optimized and efficient using modern AI

Higher Intelligence Model: GPT-5

• GPT-5 consumes more credits

• For the same volume of 1000 chats, the estimated cost with GPT-5 would be $300–$400 per month

Transparency for the Organization:

• The organization always sees:

  • How many credits remain

  • How many credits were used per session

  • Which model was selected and its cost

• Credits are consumed only if the digital assistant is activated

Advantages:

• Full control over expenses

• Flexible models – choose the AI level you need

• Transparent and easy-to-understand system