Agentic AI in 2026 looks very different from what most businesses experimented with just a year or two ago. This is no longer about deploying a chatbot or automating a single task. Agentic AI reasons across goals, makes decisions in context,…
Language Understanding Systems
Extract meaning, surface intelligence, automate insight
The foundational layer of any NLP deployment — models that read, classify, extract, and structure unstructured text at scale. We build these as production systems connected to your data sources, not standalone analytics tools.
- Named Entity Recognition (NER) — identify entities, relationships, and events across millions of documents with up to 80% reduction in manual extraction effort
- Sentiment and intent analysis — real-time signals from customer interactions, support tickets, clinical notes, and compliance documents
- Text classification and intelligent routing — automatically categorize and route documents, emails, claims, and cases
- Semantic search — enable employees and systems to query unstructured data in natural language across knowledge bases
- Domain-specific fine-tuning — 85–95% enterprise accuracy vs. 70–75% with generic models, trained on your terminology











