Reviewed by Harsh Desai · Last reviewed:
Hebbrix
An AI memory layer that injects long-term context into every LLM conversation automatically
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What does Hebbrix do?
- •5-layer hybrid search combines vector similarity, BM25 keywords, knowledge graph traversal, time decay, and ONNX reranking for precise retrieval.
- •3-tier memory system uses short-term, mid-term, and long-term tiers with automatic promotion between layers.
- •Knowledge graph engine supports entity relationships, temporal reasoning, and automatic contradiction detection.
- •OpenAI-compatible API serves as drop-in replacement for chat completions with automatic context injection.
- •Media ingestion handles PDF, DOCX, audio, video uploads up to 100MB with automatic transcription and extraction.
- •Fact extraction automatically builds user profiles including preferences and relationships from conversations.
- •160+ REST endpoints covers memories, search, chat, and full management via comprehensive API.
- •Streaming responses delivers real-time outputs while injecting relevant memories on the fly.
- •Temporal reasoning tracks time-based events and evolves knowledge graphs with new information.
- •Automatic promotion moves important facts from short-term to long-term memory without manual rules.
- •Analytics dashboard tracks memory usage, retrieval quality, and agent performance in Pro tier.
- •Hybrid Reranking Leverages ONNX models to rerank results from 5-layer hybrid search combining vector similarity, BM25, graph traversal and time decay.
- •Automatic Tier Promotion smoothly moves important facts across short-term, mid-term and long-term memory tiers based on usage patterns and relevance.
- •Entity Contradiction Detection Scans knowledge graph relationships during queries to identify and flag conflicting information within user profiles and memories.
- •Context Injection API Serves as drop-in replacement for OpenAI chat completions with automatic injection of relevant memories from 160+ REST endpoints.
Pricing:
- •Free $0/mo includes 1,000 credits per month and community support.
- •Starter $19/mo provides 25K credits, bring-your-own-key, and priority support.
- •Pro $99/mo delivers 200K credits, 99.9% SLA, advanced analytics and is most popular.
- •Scale $399/mo offers 1M credits, full knowledge graph, and team collaboration features.
- •Enterprise Custom enables pay-as-you-go, dedicated infrastructure, and SOC2/HIPAA compliance.
What are Hebbrix's limitations?
- •100MB upload limit restricts file sizes for PDF, video, and other media ingestion.
- •Model restriction lower tiers are limited to GPT-5-nano only with no access to larger models.
- •Tiered features full knowledge graph and RL training available only in higher paid tiers.
- •Credit system requires frequent upgrades for high-volume production deployments and heavy usage.
Our Verdict
For the Vibe Builder, Hebbrix functions as an intuitive persistent memory system that lets AI agents develop genuine personality continuity across sessions, turning one-off interactions into evolving relationships that feel alive and contextually aware. Its Hebbian-inspired learning creates natural memory strengthening through repeated interactions, allowing agents to reference past conversations with emotional nuance and contextual depth that generic memory stores simply cannot replicate. This makes it ideal for creators building companion experiences, storytelling agents, or brand personas that need to maintain consistent character voice without constant retraining or prompt engineering. The credit system and tiered access further support experimentation at the free level before scaling into more sophisticated memory-driven applications.
For the Developer, Hebbrix offers clean APIs and BYOK support in the Starter tier, enabling smooth integration into existing agent frameworks while the higher Pro and Scale plans open up advanced analytics and knowledge graph capabilities for production systems. The persistent memory architecture reduces context window bloat and token costs by intelligently retrieving only relevant historical data, which translates to more efficient and coherent agent behavior over long-running deployments. Priority support and SLA guarantees in paid tiers provide confidence for commercial applications, while the ability to train with reinforcement learning in upper tiers allows sophisticated memory optimization that adapts to specific use cases. Documentation and community resources help accelerate implementation even for teams new to persistent memory concepts.
The primary drawbacks include a strict 100MB maximum file upload limit and lower tiers being restricted to the GPT-5-nano model, which constrains experimentation for complex document-heavy projects. Advanced features like the full knowledge graph and RL training are locked behind the more expensive Pro, Scale, and Enterprise plans, while the credit-based system often forces upgrades for any meaningful high-volume production use. Overall the platform earns a 7.5/10 because it delivers solid persistent memory foundations yet feels gated for developers who need unrestricted scale or model choice from day one.
Skip it if you need unrestricted model access or large document handling from the start and consider Mem0 instead.
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Frequently Asked Questions
What is Hebbrix memory system?
Hebbrix memory system is a knowledge graph based long term memory layer designed specifically for AI agents that stores contextual information from conversations and interactions to enable more coherent and personalized responses over time. It uses vector embeddings combined with graph relationships to retrieve relevant memories efficiently during agent operations. This setup helps agents maintain continuity across sessions without losing important details from previous interactions.
How much does Hebbrix cost in 2026?
Hebbrix offers several pricing options including the Starter plan at $19 the Pro plan at $99 and the Scale plan at $399 along with a free tier at $0 per month and an Enterprise custom option. The Pro plan is the most popular choice for many users. These prices provide different levels of credits and features to match various usage needs.
Who should use Hebbrix for AI agents?
Developers building autonomous AI agents that need persistent memory across multiple interactions should use Hebbrix. It works particularly well for customer service bots personal assistants or research agents that benefit from recalling past context accurately. Teams looking for scalable knowledge management in their AI workflows also find it valuable.
What is the difference between Hebbrix and Mem0?
Hebbrix and Mem0 both provide memory solutions for AI but Hebbrix focuses more on full knowledge graph capabilities and enterprise compliance features while Mem0 emphasizes simpler vector based storage. Hebbrix includes advanced analytics SLA guarantees and team collaboration tools that set it apart for larger deployments. The choice often depends on whether you need basic memory or a more comprehensive system like what Hebbrix delivers.
Does Hebbrix have a free plan as an alternative?
Yes Hebbrix has a free tier at $0 per month that includes 1000 credits and community support as a solid alternative to test the system. This plan lets you evaluate the memory features before committing to paid options. It is a good starting point for individual developers or small projects.
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