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Multi-LLM Support

Support for OpenAI, Azure OpenAI, Ollama, Mistral AI, and LM Studio. Separate API key management and dynamic model selection for each provider.

Multi-Agent System

Unlimited agent creation with custom system prompts and settings for each agent. Agent selection and orchestration strategies.

Advanced RAG

Vector search, keyword search, hybrid search, and re-ranking. Powerful document search with Qdrant, Pinecone, and Milvus support.

Plugin System

Built-in, OpenAPI, DLL, and External plugin support. Dynamic plugin loading/unloading and hot reload capabilities.

Features

Enterprise-grade AI
with advanced capabilities

ChattyFire is an enterprise-grade AI assistant platform. It provides powerful AI chat and document management with multi-LLM provider support, advanced RAG features, flexible plugin system, and multi-agent orchestration.

100
+
Concurrent Users
5
+
LLM Providers
500
ms
Search Response
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Multi-Agent Orchestration
for Complex Workflows

ChattyFire supports official orchestration patterns. Manage complex workflows with Sequential, Concurrent, Handoff, Group Chat, and Magentic orchestration strategies.

  • Orchestration Strategies

    Sequential, Concurrent, Handoff, Group Chat ve Magentic orkestrasyon desenleri ile esnek iş akışı yönetimi.

  • Dynamic Agent Selection

    Automatic agent selection based on message content. Each agent can use a different LLM provider and model.

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Enterprise Security
& Document Management

ChattyFire provides enterprise-grade security features and advanced document management system. PBKDF2 password hashing, JWT authentication, role-based access control, and user-based document isolation.

  • Smart Document Processing

    Support for PDF, DOCX, TXT, and Markdown. Advanced processing with Docling integration. Adaptive chunking and token-based optimization.

  • Enterprise Security

    PBKDF2 password hashing, JWT authentication, RBAC, IP ban, rate limiting ve data protection ile tam güvenlik.

Why Choose ChattyFire?

"We quickly set up our enterprise AI assistant with ChattyFire. Multi-LLM support and RAG features allow us to intelligently query our documents."

Enterprise AI Solution

Multi-LLM & RAG Support

"The plugin system allowed us to easily integrate our external APIs. The automatic plugin creation from OpenAPI specs really saved us time."

Flexible Integration

OpenAPI & DLL Plugins

"Security features and user-based document isolation allow us to meet our enterprise requirements. A production-ready platform."

Enterprise Security

RBAC & Document Isolation
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faq

Frequently Asked Questions

ChattyFire supports many LLM providers including OpenAI, Azure OpenAI, Ollama, Mistral AI, and LM Studio. You can manage separate API keys and dynamic model selection for each provider. Ollama support is also available for local LLMs.

ChattyFire supports vector databases like Qdrant, Pinecone, and Milvus. You can intelligently query your documents with vector search, keyword search, hybrid search, and re-ranking features. It supports PDF, DOCX, TXT, and Markdown formats and performs automatic chunking.

ChattyFire offers enterprise-grade security features: PBKDF2 password hashing, JWT authentication, role-based access control (RBAC), API key management, IP ban, rate limiting, and user-based document isolation. All sensitive information is masked in logs.

ChattyFire supports Built-in, OpenAPI, DLL, and External plugin types. You can automatically create plugins from OpenAPI spec files, load DLL plugins, and add or remove plugins at runtime. Hot reload support is also available.

LLM stands for Large Language Model. These are AI models trained on vast amounts of text data to understand and generate human-like text. LLMs can perform various natural language tasks such as answering questions, generating content, translation, summarization, and more. Popular examples include GPT-4, Claude, Llama, and Mistral. ChattyFire supports multiple LLM providers, allowing you to choose the best model for your specific use case.

MCP stands for Model Context Protocol. It is a standardized protocol that enables AI models to access and interact with external data sources, tools, and services. MCP allows AI assistants to retrieve real-time information, perform actions, and maintain context across different interactions. ChattyFire integrates with MCP to provide enhanced context management and enable seamless connections with various external systems and data sources.

A plugin is an extension that adds specific functionality to ChattyFire without modifying the core system. Plugins can integrate external APIs, add new capabilities, or extend existing features. ChattyFire supports multiple plugin types: Built-in plugins for core functionality, OpenAPI plugins created from API specifications, DLL plugins for compiled code, and External plugins for web services. Plugins can be loaded, unloaded, and updated at runtime, providing flexibility and extensibility to the platform.

Location

Kozyatağı İçerenköy Mh.
Topçu İbrahim Sk. No:8-10d
34752 Ataşehir, İstanbul

Make a Call

+90 216 255 16 00

Email

info@protoyazilim.com

Have Questions?
Get in Touch!

Advanced Capabilities

Real-time Streaming

Real-time response streaming with Server-Sent Events (SSE). Intelligent chat experience with chat history and context management.

Vector Database Support

Support for Qdrant, Pinecone, Milvus, and Elasticsearch. Automatic collection management based on embedding dimensions.

OpenAI Compatible API

OpenAI API format compatible endpoint. RESTful API, Swagger documentation, and programmatic access support.