Le Chat
The multilingual AI assistant powered by Europe's premier frontier models.
The first Large Language Model purpose-built for human-to-human conversational intelligence.
Nebula is a specialized Large Language Model (LLM) developed by Symbl.ai, architected specifically for the nuances of human conversation. Unlike general-purpose LLMs, Nebula is trained on massive datasets of multi-party dialogues, telephonic interactions, and video conferencing data, allowing it to excel in tasks like action item extraction, sentiment nuance, and intent detection without the 'hallucination' risks associated with standard creative models. In the 2026 market, Nebula positions itself as the core infrastructure for 'Conversation-as-a-Service,' providing low-latency inference for real-time applications. Its architecture supports RAG (Retrieval-Augmented Generation) out-of-the-box, enabling enterprises to ground model outputs in their own private knowledge bases. By focusing on the 'operational' side of conversation rather than just chat-style interaction, Nebula enables automated CRM updates, compliance monitoring, and real-time agent coaching with high precision. It is designed to be model-agnostic in its deployment, offering both cloud-based APIs and VPC deployment options for data-sensitive industries such as finance and healthcare.
Nebula uses a specialized decoder architecture to generate summaries without needing specific examples per industry.
The multilingual AI assistant powered by Europe's premier frontier models.
The industry-standard framework for building context-aware, reasoning applications with Large Language Models.
Real-time, few-step image synthesis for high-throughput generative AI pipelines.
Professional-grade Generative AI for Landscape Architecture and Site Design.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Integrates diarization data directly into the LLM context to attribute actions to specific individuals.
Built-in identification and masking of sensitive entities (credit cards, SSN) before LLM processing.
Allows Nebula to query external knowledge bases while maintaining the flow of a conversation.
WebSocket-based model processing that provides partial results with sub-500ms latency.
Processes audio features (tone, pitch) alongside text transcripts to detect true sentiment.
Enterprise-level ability to adjust model weights based on industry-specific jargon.
Manually auditing 1% of calls leaves 99% of customer interactions unmonitored for compliance.
Registry Updated:2/7/2026
Sales reps spend 20% of their time manually typing notes into Salesforce/HubSpot.
Junior agents struggle with complex technical questions on live support calls.