Alternatives
Products that do what MemoriGraph does
Build AI with contextual memory using knowledge graphs.
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- 3GL
Hey HN! We're Paul, Preston, and Daniel from Zep. We've just open-sourced Graphiti, a Python library for building temporal Knowledge Graphs using LLMs. Graphiti helps you create and query graphs that evolve over time. Knowledge Graphs have been explored extensively for information retrieval. What makes Graphiti unique is its ability to build a knowledge graph while handling changing relationships and maintaining historical context. At Zep, we build a memory layer for LLM applications. Developers use Zep to recall relevant user information from past conversations without including the entire…
2024 · github.com
- 4MO
Hey HN! I'm Arindam, part of the team behind Memori (https://memori.gibsonai.com/). Memori adds a stateful memory engine to AI agents, enabling them to stay consistent, recall past work, and improve over time. With Memori, agents don’t lose track of multi-step workflows, repeat tool calls, or forget user preferences. Instead, they build up human-like memory that makes them more reliable and efficient across sessions. We’ve also put together demo apps (a personal diary assistant, a research agent, and a travel planner) so you can see memory in action. Current LLMs are stateless…
2025 · github.com
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I've been working on this tool that lets you build a personal knowledge graph from articles, blog posts, podcasts, YouTube videos, and other content you find interesting online. You can safely forget everything and trust that Recall will resurface it when something new that is related comes up. Looking forward to your thoughts and feedback on how it could be improved! The original version of Recall was posted last year nov on HN: https://news.ycombinator.com/item?id=33425947 Since then I have pivoted to a browser extension.
2023 · recall.wiki
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Hi HN, We’re Daniel and Mark, the creators of TrustGraph (https://github.com/trustgraph-ai/trustgraph). TrustGraph is an open source, full end-to-end AI infrastructure that automates knowledge graph building and querying along with modular agent integration. A unique aspect of TrustGraph is that the graph building is a one-time process that builds reusable knowledge cores that can be stored, shared, and reloaded. You can read more about TrustGraph knowledge cores here (https://trustgraph.ai/docs/cores/). Throughout our careers, we’ve been faced…
2024 · github.com
- 12MC
Hi HN, I’ve been building AI agents and copilots, and kept running into a frustrating problem: they don’t fail loudly, they forget things quietly. Users re-explain preferences, agents contradict earlier responses, and context resets without any clear visibility into why. I built Memograph CLI as a debugging tool to analyze conversation transcripts and show: - what the agent forgot - where continuity broke - contradictions and repeated context - estimated token waste due to re-prompting It works locally and supports plain text or JSON transcripts. Example: $ memograph Output: Cognitive Drift…
Feb 2026
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I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video:…
2025 · github.com
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Hey HN - Paul, Preston, and Daniel from Zep here. We’re excited to show you graphiti, a library for building and searching dynamic, temporally aware knowledge graphs. https://git.new/graphiti With graphiti, you can model complex, evolving relationships between entities over time. graphiti ingests both unstructured and structured data and the resulting graph may be queried using a fusion of time, full-text, semantic, and graph algorithm approaches. With graphiti, you can build LLM applications such as: - Assistants that learn from user interactions, fusing personal knowledge…
2024
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2022 · memgraph.com
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Captures and stores your chat from various AI platforms
Mar 2026 · ai-memory-beta.vercel.app
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Connect Itsuki once with one key. It extracts structured memories from any of 26 connected tools — assistants, agents, workflows — links each to the words it came from, and serves them back across all the rest.
Jul 2026 · uml.gpmai.workers.dev
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TrustGraph now supports automatic knowledge graph construction guided by OWL ontologies. You provide an ontology (OWL/Turtle format or build one in the Workbench editor), point it at your documents, and it extracts entities and relationships that conform to your schema. The problem this solves: generic GraphRAG approaches extract whatever relationships an LLM thinks are relevant, which often misses domain-specific semantics. If you're working in healthcare, finance, or intelligence analysis, you likely already have ontologies (or can adapt standards like SOSA, FIBO, etc.) that define…
Nov 2025
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Hi HN, There’s been a lot of discussion lately around context graphs, decision traces, and how AI systems reason. One thing we kept running into: when AI agents make real decisions, the why behind those decisions often disappears. The context is scattered across prompts, tools, policies, and approvals. Logs show what happened, but not why it was allowed. TraceMem is an attempt to make decision context durable. It records the reasoning, authority, and context behind AI actions as a system of record, not as monitoring data, but as memory. Happy to share more details or answer questions. - Tommi
Jan 2026 · tracemem.com
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Memora gives AI the ability to recall memories during interactions, just like humans do subconsciously. For now, it’s just text-based memories, but our vision extends to the full spectrum of human memory: emotions, audio, video. Key Features: Built-in multi-tenancy for managing multiple organizations, users, and agents. Time-stamped memories to track how information evolves over time. Scalable, modular, and developer-friendly design. GitHub: https://github.com/ELZAI/memora Install: pip install memora-core We’re looking for feedback and contributions, let’s change how we…
2025 · github.com
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