Natural Language Processing
Natural Language Processing (NLP) is the field of AI focused on enabling computers to understand, interpret, and generate human language — the technology underlying everything from email classification to LLMs.
What is Natural Language Processing?
NLP has been around for decades, but the field transformed with the transformer-architecture LLMs of the late 2010s. Modern NLP for GTM applications covers tasks like reply classification (positive, negative, opt-out), intent detection (meeting request vs info request), entity extraction (pulling company names and titles from unstructured text), and language generation (drafting personalized emails). The strategic role: NLP is what makes AI Revenue Agents possible — without it, agents can't read replies, understand context, or write in brand voice.
Why it matters
- Enables agents to read and act on unstructured text — the bulk of revenue work.
- Reply classification at scale is impractical without NLP.
- Modern LLM-powered NLP is dramatically more accurate than rule-based predecessors.
Use cases
- Reply classification. Automatically categorize replies as positive, neutral, negative, opt-out.
- Entity extraction. Pulling structured fields from unstructured text (call transcripts, free-form notes).
- Personalized generation. Drafting contextually-appropriate outreach in brand voice.
How turgo helps
turgo's agents are built on modern NLP — classifying every reply, extracting context from unstructured signals, and generating drafts that pass brand-voice and claim-restriction checks.
See turgo in action →
