Wisent enables businesses to unlock AI’s full potential through representation engineering. This innovative technology allows you to see inside AI models, understand their behavior, and precisely modify their capabilities. By mapping and editing internal neural activations, Wisent enhances AI functions, making them more aligned with your goals. Whether you need creative AI for content generation, personalized experiences for different user segments, or safer and more compliant AI systems, Wisent provides the tools to achieve these efficiently. Their adaptive LLMs can be integrated with existing models, offering rapid and cost-effective enhancements without extensive retraining.

Chatbot-Grok provides a modular AI Agent framework written in Python, designed to simplify development of conversational bots. It supports multi-turn dialogue management, retains chat memory across sessions, and allows users to define custom prompt templates. The architecture is extensible, letting developers integrate various LLMs including Grok, and connect to platforms such as Telegram or Slack. With clear code organization and plugin-friendly structure, Chatbot-Grok accelerates prototyping and deployment of production-ready chat assistants.

The Controllable RAG Agent framework provides a modular approach to building Retrieval-Augmented Generation systems. It allows you to configure and chain retrieval components, memory modules, and generation strategies. Developers can plug in different LLMs, vector databases, and policy controllers to adjust how documents are fetched and processed before generation. Built on Python, it includes utilities for indexing, querying, conversation history tracking, and action-based control flows, making it ideal for chatbots, knowledge assistants, and research tools.