How to find warm Telegram leads instead of collecting another list of users
Good parsing is not about exporting as many rows as possible. It is about a short, transparent path from a conversation to a person who actually needs your product.
1. Start with the right source
Choose a group, channel or chat history that already contains the right context. Chat history is the right mode when you search by what people wrote: developers, investors or someone asking for a solution.
2. Understand the limits
The matching contacts limit is how many results you receive. The AI checks limit is how many profiles the model can evaluate. For AI searches, the system reserves the possible volume and releases the unused part when the job finishes.
3. Use two filtering stages
Keywords remove obvious noise quickly. Then AI sees only the remaining candidates and answers your semantic request. This is faster, cheaper and easier to understand than sending the whole chat to a model.
Before you run
The result
When the job finishes, you see the number of contacts, status and errors, and can download a CSV. If AI is temporarily unavailable, the system exposes the problem and does not charge unused AI checks.