MindVault
Give your AI systems persistent, structured memory that grows smarter over time. MindVault combines semantic vector storage with a knowledge graph layer, enabling your AI to store facts, recall context, traverse relationships, and build institutional knowledge that persists across sessions and scales across teams.
Key Features
Everything you need to integrate MindVault into your production systems.
Semantic Storage
Store knowledge as richly-typed entities with embeddings, metadata, and relationship links. Supports text, structured data, documents, and multimodal content with automatic embedding generation.
Graph Queries
Traverse knowledge relationships using graph queries. Find connections between entities, discover implicit relationships, and answer questions that require multi-hop reasoning.
Contextual Recall
Retrieve the most relevant memories based on semantic similarity, recency, importance, and access frequency. Automatically surfaces the right context for any conversation or task.
Memory Analytics
Monitor knowledge growth, identify gaps, track usage patterns, and measure recall quality. Dashboards show what your AI knows, what it is learning, and where it needs more information.
API Reference
Production-ready REST API. All requests require a valid API key via Authorization header.
/api/v1/mindvault/storeStore a new memory with content, metadata, and optional relationship links. Automatically generates embeddings and indexes for semantic search.
/api/v1/mindvault/recallRecall memories relevant to a query. Uses hybrid semantic and graph search to find the most relevant stored knowledge.
/api/v1/mindvault/graphExecute a graph traversal query. Find entities connected by specific relationship types, discover paths between entities, and aggregate knowledge across relationship chains.
/api/v1/mindvault/statsGet memory statistics including total entities, relationships, storage usage, query volume, and knowledge growth trends.
curl -X POST https://api.bolorintelligence.com/api/v1/mindvault/store \
-H "Authorization: Bearer bolor_sk_..." \
-H "Content-Type: application/json" \
-d '{
"content": {"text": "Customer prefers monthly billing", "source": "support_chat"},
"memory_type": "semantic",
"tags": ["customer", "billing", "preferences"],
"importance": 0.8
}'Use Cases
See how teams are using MindVault in production today.
Enterprise Knowledge Management
Large organizations use MindVault as the memory layer for internal AI assistants. Every answered question, resolved ticket, and documented decision becomes searchable institutional knowledge.
AI Assistant Memory
Customer-facing AI assistants use MindVault to remember conversation history, customer preferences, past issues, and resolution patterns. Each interaction makes the assistant more helpful.
Research Databases
Research teams store experimental results, literature findings, and hypotheses in MindVault. The graph layer connects related findings across papers, surfacing insights missed in traditional document stores.
Explore More Products
MindVault works even better with the rest of the platform.
Start Building with MindVault
Get your API key and make your first call in under 5 minutes. Free tier includes 100 API calls per month.