Whales Officer is an AI service for automated KYC.
Whales Officer is an AI service for automated KYC/Compliance client verification through video interviews with a live AI avatar.
The scenario is as follows:
The client arrives via a link or through the main page with parameters name, language, country, gender, age.
Frontend creates an interview through the Next.js API route.
Backend creates a user, generates an access_token, saves the interview state in Redis, and basic information in PostgreSQL.
Frontend creates a LiveAvatar/HeyGen context with a KYC prompt.
The client engages in a conversation with the AI compliance officer, who asks mandatory KYC questions:
source of funds;
purpose of the account and expected transaction volume;
beneficial ownership / who controls the account.
During the session, the frontend records the user's video, microphone, and avatar sound, cuts the recording into chunks, and sends them to the backend.
Backend places the chunks in a Redis queue.
A worker assembles the .webm, pulls the transcript, generates a summary via OpenAI, sends the video to an external Whales API/S3 flow, and updates the call record.
Thus, the product is not just a chatbot, but a KYC video-interview pipeline: the AI avatar conducts a regulated interview, and the system saves the evidential record, transcript, and summary for further compliance processing.
The scenario is as follows:
The client arrives via a link or through the main page with parameters name, language, country, gender, age.
Frontend creates an interview through the Next.js API route.
Backend creates a user, generates an access_token, saves the interview state in Redis, and basic information in PostgreSQL.
Frontend creates a LiveAvatar/HeyGen context with a KYC prompt.
The client engages in a conversation with the AI compliance officer, who asks mandatory KYC questions:
source of funds;
purpose of the account and expected transaction volume;
beneficial ownership / who controls the account.
During the session, the frontend records the user's video, microphone, and avatar sound, cuts the recording into chunks, and sends them to the backend.
Backend places the chunks in a Redis queue.
A worker assembles the .webm, pulls the transcript, generates a summary via OpenAI, sends the video to an external Whales API/S3 flow, and updates the call record.
Thus, the product is not just a chatbot, but a KYC video-interview pipeline: the AI avatar conducts a regulated interview, and the system saves the evidential record, transcript, and summary for further compliance processing.