Skip to main content
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in

Stay Ahead in the AI Revolution

Weekly digest — EPI pulse, top intelligence, fresh lineage. Free, no account.

Follow Angestrom
Global source network
Synced every 5 minutes

Continuous sync from primary AI sources — indexed, enriched, and queryable in real time.

arXivHugging FaceGitHubOpenAIAnthropicDeepMindReutersBBC TechHacker NewsReddit MLVerified feedsFunding
ANGESTROM

The Intelligence Layer of Humanity. Everything AI. All in One Place.

Angestrom connects every piece of the AI ecosystem — data, models, research, companies, tools, and people.

info@angestrom.comwww.angestrom.comLucknow, Uttar Pradesh, India

Product

  • AI Search
  • AI Models
  • Research Papers
  • Companies
  • News & Events
  • GitHub Explorer
  • APIs & Tools
  • Datasets
  • Benchmarks
  • Model lifecycle
  • Funding graph
  • Contributors
  • AI Agents

Resources

  • Weekly digest
  • Documentation
  • Tutorials
  • Guides
  • News
  • Help / Start
  • Community

Company

  • About
  • Contact
  • Privacy Policy
  • Terms of Service
  • Acceptable Use

Enterprise

  • Pricing
  • Workspace
  • Contact Sales

Developer

  • Developer Hub
  • API docs
  • GitHub

Learn

  • Learning Academy
  • Roadmaps
  • Glossary
  • AI for Beginners

Popular Topics

Loading topics…
View All Topics →
© 2026 Angestrom Intelligence Private Limited. All rights reserved.
English
Theme
Angestrom home
SearchPapersModelsLive AIIntelligence
Search⌕⌘K
EnterprisePricingSign in
  1. Home
  2. /Repositories
  3. /maximem-ai/maximem_synap_sdk
Read original ↗
repoGitHubTrust 82 · PrimaryPublished 13d agoLive · 13d ago

maximem-ai/maximem_synap_sdk

Maximem Synap is the memory layer that makes AI agents remember. 92% LongMemEval, 93.2% on LOCOMO. Works natively with LangChain, LlamaIndex, CrewAI, Google ADK, AutoGen, OpenAI Agents, Semantic Kernel, Haystack, and Pydantic AI.

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 57%MemSyco-Bench: Benchmarking Sycophancy in Agent Memory →
  • PossiblePossibly related (embedding) · 55%Anatomy of Persistent Memory's 3 Layers: Comparing ContextNest, Mem0 and Zep →
  • PossiblePossibly related (embedding) · 53%Selective Memory Retention for Long-Horizon LLM Agents →
  • PossiblePossibly related (embedding) · 51%AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents →
  • PossiblePossibly related (embedding) · 50%Choosing the Right AI Agent Memory Strategy: A Decision-Tree Approach →

Implements

paperMemSyco-Bench: Benchmarking Sycophancy in Agent MemorypaperSelective Memory Retention for Long-Horizon LLM AgentspaperAgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents

Covers

newsAnatomy of Persistent Memory's 3 Layers: Comparing ContextNest, Mem0 and Zep

Covers (incoming)

newsChoosing the Right AI Agent Memory Strategy: A Decision-Tree Approach

Related across the graph

paperAgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM AgentsnewsAnatomy of Persistent Memory's 3 Layers: Comparing ContextNest, Mem0 and ZepnewsChoosing the Right AI Agent Memory Strategy: A Decision-Tree ApproachpaperSelective Memory Retention for Long-Horizon LLM AgentspaperMemSyco-Bench: Benchmarking Sycophancy in Agent Memory
Knowledge path·PAgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents→NAnatomy of Persistent Memory's 3 Layers: Comparing ContextNest, Mem0 and Zep→NChoosing the Right AI Agent Memory Strategy: A Decision-Tree Approach→Rmaximem-ai/maximem_synap_sdk

Topics

agent-memoryaiai-agentsai-memoryautogencontextconversational-aicrewaigoogle-adkhaystack

Explore

Search similar →Knowledge graph →All repos →Full intelligence feed →
Graph trust82Primary
Graph score32