Teach models whatlanguage means
Ateegnas coordinates parallel autonomous agents for high-concurrency token classification, extraction, sentiment, and summarization with deterministic consensus arbitration
Named Entity Recognition
NER Specialist Swarm
Token-level span identification across custom domain taxonomies. Handles nested, overlapping, and ambiguous entities with token confidence weighting.
Sentiment & Tone Analysis
Aspect Sentiment Swarm
Aspect-based sentiment analysis with fine-grained granular polarity scoring, sarcasm detection, and emotional affect categorization across multi-turn dialogs.
Hierarchical Classification
Deep Intent Classifier
Multi-label hierarchical taxonomy mapping for customer support intent, compliance classification, and semantic document categorization.
Relation & Fact Extraction
Knowledge Graph Weaver
Extracts directional semantic triples (subject-predicate-object) to construct structured knowledge graphs directly from unstructured enterprise corpora.
Abstractive Summarization
Distillation Engine
Faithful, hallucination-free document compression with strict source attribution, temporal fact checking, and executive brevity control.
Quality & Consensus Judge
Arbitration Engine
Independent judge agent that compares multi-model outputs, identifies edge cases, resolves ambiguities, and computes deterministic consensus scores.
Connect your data streams to the Ateegnas agent collective
Deploy custom annotation tasks with real-time consensus arbitration, JSON-schema export, and human-in-the-loop review.