TextPilot AI Content Detector
Uncover the machine behind the message with forensic-grade linguistic analysis.
Aiquavit is a sophisticated AI orchestration platform designed for the 2026 enterprise landscape, where the intersection of generative AI utility and regulatory compliance is a critical operational frontier. Its technical architecture serves as a secure middleware layer between internal corporate data and various Large Language Model (LLM) providers like OpenAI, Anthropic, and Mistral. By abstracting the model layer, Aiquavit prevents vendor lock-in while providing a high-performance Retrieval-Augmented Generation (RAG) framework that scales across global infrastructures. The platform is engineered with a 'Secure-by-Design' philosophy, specifically addressing the stringent requirements of the EU AI Act and GDPR. It features advanced PII masking, automated auditing, and a centralized prompt management system that ensures brand and policy alignment across all AI-driven workflows. As organizations move from experimental AI to production-grade deployment, Aiquavit provides the necessary governance tools to manage model latency, token costs, and output reliability within a single, unified interface.
Dynamically routes requests to specific LLMs based on intent analysis, cost-efficiency, or latency requirements.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Uses NLP-based NER (Named Entity Recognition) to identify and mask sensitive data before it reaches public LLM endpoints.
Combines dense vector embeddings with sparse keyword search for superior context retrieval accuracy.
A centralized repository for system prompts with versioning, rollback capabilities, and A/B testing.
Real-time monitoring and logging of AI interactions to meet upcoming EU regulatory reporting requirements.
Caches responses based on semantic similarity to avoid redundant LLM calls for similar queries.
Low-code interface to build complex multi-step AI agents that can interact with external tools.
Law firms need to query thousands of private contracts without exposing data to external training sets.
Registry Updated:2/7/2026
Reducing human agent workload by providing accurate, company-specific answers to technical queries.
Identifying potential regulatory breaches in internal communications at scale.