Mirix-AI/MIRIX

Features

• Stateful Agent Orchestrators - Functions as a stateful orchestrator for managing agent personas, system prompts, and persistence in multi-step processes.
• Observation Ingestion Pipelines - Ingests continuous screen captures and audio to transform real-time visual activity into structured long-term memories.
• Multi-Tier Memory Systems - Implements a multi-tier memory system that separates data into core, episodic, semantic, and procedural stores.
• Long-term Memory Stores - Implements persistent storage mechanisms that allow AI agents to retain context and recall facts across multiple sessions.
• Agent Memory Categorization - Uses specialized agents to categorize user activities into structured episodic, semantic, and procedural memory types.
• Screen Activity Classifiers - Processes periodic screenshots of desktop activity to classify events and build a chronological memory of user actions.
• Context-Aware Conversation Managers - Orchestrates multi-turn dialogues by combining language models with retrieved memory to provide contextually relevant assistance.
• Context Memory Management - Directs multi-modal inputs to specialized memory components to maintain a structured context for the AI.
• Embedding Models - Provides configurations for embedding models to support semantic search and long-term memory retrieval.
• Episodic Event Recording - Captures context-specific activities and behaviors to serve as a chronological summary of events.
• Persistent Context Management - Maintains persistent agent context by storing key facts and decisions across multiple user sessions.
• Procedural Knowledge Capture - Records step-by-step instructions and operational patterns required to accomplish recurring tasks.
• Visual Activity Knowledge Bases - Monitors desktop activity and converts visual observations into a searchable long-term memory store.
• Visual Context Monitors - Analyzes desktop activity in real-time to provide AI assistance based on current visual context.
• Desktop Activity Tracking - Monitors desktop activity in real-time to build a structured, searchable history of user actions.
• Hybrid Vector and Full-Text Search - Combines vector similarity and full-text keyword matching to optimize the recall of long-term memories.
• Conversation Memory Retrieval - Fetches relevant stored memories based on current conversation state to provide historical context for AI interactions.
• Knowledge Management - Stores abstracted concepts and factual information in a dedicated knowledge management system independent of specific events.
• Local-First Storage - Implements local-first storage strategies to ensure user data sovereignty and manages information via retention policies.
• Multi-Modal Memory Stores - Processes text, voice, and screen captures into a unified multi-modal memory store for richer AI context.
• Multi-Modal RAG Pipelines - Analyzes text, images, and voice simultaneously through a RAG pipeline to extract information from multi-modal inputs.
• Vector Memory Stores - Manages AI memories using a hybrid of vector similarity and keyword indexing with customizable retention policies.
• Screen Capture Tools - Captures continuous visual data from the screen to be consolidated into structured AI memories.
• Multi-Agent Coordination Systems - Integrates a unified memory pipeline across multiple agents to enable state sharing and collaborative knowledge access.
• Agent Persona Configurations - Defines assistant behaviors and system prompts while maintaining consistent user personas and identity facts.
• Custom Tool Registrations - Implements mechanisms for registering and attaching custom user-defined functions as tools that agents can execute.
• OpenAI-Compatible APIs - Integrates with OpenAI-compatible API endpoints to leverage both fine-tuned and self-hosted models.
• Persona Configurations - Provides configuration settings and prompt templates to define the personality and behavioral constraints of the AI agent.
• Editable User Persona Memory - Maintains structured and editable storage of user preferences and identity facts to personalize agent interactions.
• Per-User Memory Isolation - Queries memories across an organization while using strict isolation to ensure user-specific data remains private.
• Memory Decay Policies - Controls information longevity by marking memories as inactive or deleting them after a set duration.
• System Prompt Overrides - Allows overriding default agent behaviors by modifying or appending instructions via custom system prompts.
• Model Selection Tools - Offers utilities for selecting specific large language models based on performance and cost requirements for different tasks.
• Procedural Memory Retrievals - Implements specialized querying of structured arrays of step-by-step instructions to recall specific workflows.
• Hybrid Search Methods - Combines full-text BM25 ranking with vector similarity search and relational filters for optimized memory recall.
• Knowledge Structuring - Organizes core facts and procedures into structured components with configurable retention and decay policies.
• Risk-Based Classifications - Categorizes sensitive information by risk level to prevent the accidental exposure of high-security data.
• Chat Query Engines - Implements a chat-based query engine to answer natural-language questions based on recorded historical information.
• Local Database Security - Ensures long-term memories are stored on local infrastructure using database-level security and encryption.
• Multi-Backend Storage Management - Supports multiple storage backends, including scalable vector search and lightweight fallbacks, through a unified management layer.
• Pluggable Database Backends - Decouples the memory pipeline from the storage layer, allowing interchangeable local or hosted database backends.
• Cross-Category Memory Search - Retrieves relevant information using unified queries across different memory categories.
• Multi-Pass Query Strategies - Executes a sequence of search strategies, moving from high-precision matches to broader retrievals to optimize recall.
• Agent Session Recovery - Saves and reloads agent memory states to preserve knowledge and context across different sessions.
• Sandboxed Execution Environments - Executes custom tool functions and API integrations within an isolated environment for safe agent extension.
• Temporal Activity Filters - Provides capabilities to restrict memory retrieval results based on specific timestamp ranges or time offsets.
• Procedural Memory Captures - Records step-by-step workflows and recurring task patterns to create a searchable library of operational instructions.
• Memory Entry Lifecycles - Automatically manages memory lifecycles by archiving old entries, merging duplicates, and expiring outdated credentials.
• Multi-Modal Memory Routing - Routes incoming text, images, and voice to the specific memory components that require updating.
• Credential Vaults - Provides a protected vault for the secure storage of sensitive credentials and contacts.
• Local Privacy Solutions - Provides architectural patterns for local-only data storage to ensure user memories remain private and under personal control.
• Sensitive Data Access Controls - Restricts the retrieval of memories based on security levels to ensure only cleared information is accessed.
• Data Sensitivity Classifications - Categorizes data by security risk levels to restrict retrieval of sensitive credentials based on permission scopes.
• Shared Knowledge Graph Memory - Integrates a unified memory pipeline across multiple agents to maintain a shared knowledge base.

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