If you don’t have labeled data, you can still start your NLP project because an nlp consultant is trained to handle this situation in a practical way. Professional nlp consultants use methods like unsupervised learning, where models find patterns in raw text without labels, and pre-trained language models that already understand language structure, so they work well even with very little data. An experienced nlp consultant can also help you create labels step by step using simple rules, keyword-based tagging, or semi-automatic tools where the system suggests labels and your team only reviews and corrects them. This reduces time, effort, and cost. In many cases, nlp consultants set up active learning and human-in-the-loop workflows, where you only label the most important or unclear examples instead of your entire database. For some use cases like routing tickets, grouping feedback, sorting emails, or matching FAQs, an nlp consultant may design a hybrid system that combines rules with machine learning so you get reliable results even without a large labeled dataset. So, not having labeled data is not a blocker; with the right nlp consultant and clear business goals, you can still build useful, accurate NLP solutions for your organization.