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Fissible.dev VS Agentmemory

Compare Fissible.dev VS Agentmemory and see what are their differences

Thalam
OpenAI-compatible API gateway for GPT, Claude, Gemini, DeepSeek, Qwen, Kling and more. One key, one endpoint, one bill. Pay per token, no lock-in. sponsored
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Contents:
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Fissible.dev logo Fissible.dev

Self-hosted CMS and API platform with enforced approvals and contract validation.

Agentmemory logo Agentmemory

Persistent memory for Claude Code, Codex & coding agents
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Fissible Station is a self-hosted Laravel CMS built for agencies managing multiple client sites from a single install. It enforces client approval before anything goes live, isolates each tenant's content and users, and backs every action with a full audit log, so "the client approved this" is never just an assumption.

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Fissible.dev

Website
fissible.dev
$ Details
Release Date
2026 April
Startup details
Country
United States
State
CT
City
Old Saybrook
Employees
1 - 9
Edit details

Agentmemory

Website
agent-memory.dev
$ Details
-
Release Date
-
Edit details

Fissible.dev features and specs

No features have been listed yet.

Agentmemory features and specs

  • Simple API
    Agentmemory provides a straightforward and minimal API for creating, searching, updating, and deleting memories, making it easy for developers to integrate memory capabilities into AI agents without dealing with complex configurations.
  • Built on ChromaDB
    It leverages ChromaDB as its underlying vector database, providing reliable semantic search and embedding capabilities out of the box without requiring developers to set up separate infrastructure.
  • Lightweight and Easy to Install
    Agentmemory is a lightweight Python package that can be installed via pip with minimal dependencies, making it quick to get started with and easy to incorporate into existing projects.
  • Category-Based Memory Organization
    Memories can be organized into categories (topics), allowing agents to store and retrieve information in a structured way, which helps with context management and retrieval accuracy.
  • No Server Required
    Agentmemory can run entirely locally without needing a separate server or cloud service, making it suitable for development, prototyping, and privacy-sensitive applications where data should stay on the local machine.

Possible disadvantages of Agentmemory

  • Limited Ecosystem and Community
    Agentmemory is a relatively niche and small project with a limited community compared to more established memory and vector database solutions, which means fewer resources, tutorials, and community support are available.
  • Basic Feature Set
    While simplicity is a strength, the library may lack advanced features such as sophisticated memory consolidation, decay mechanisms, importance scoring, or complex querying capabilities that more mature memory frameworks offer.
  • Tight Coupling to ChromaDB
    Being built specifically on ChromaDB means developers are locked into that particular vector store and cannot easily swap it out for alternatives like Pinecone, Weaviate, or FAISS without significant refactoring.
  • Limited Scalability
    As a locally-run, lightweight solution, Agentmemory may not scale well for production applications that require handling large volumes of memories, high concurrency, or distributed deployments.
  • Sparse Documentation and Examples
    The project's documentation, while covering the basics, may lack comprehensive examples, best practices, and advanced usage patterns that developers need when building complex agent-based systems.

Analysis of Fissible.dev

Overall verdict

  • I don't have verified information about Fissible.dev in my training data, so I can't confirm its quality, features, or reputation with confidence. Before trusting or using this service, I'd recommend independently verifying its legitimacy, checking recent user reviews, and researching the company behind it.

Why this product is good

  • No reliable or verifiable data available about this specific product/service in my knowledge base
  • Cannot confirm claims, features, pricing, or user satisfaction without current information
  • Domain names can change ownership/purpose over time, making pre-existing knowledge potentially outdated or inaccurate
  • Unable to assess security, reliability, or trustworthiness without direct verification

Recommended for

  • Users should conduct their own due diligence including checking recent reviews, company registration, and community feedback
  • Consider looking up the site on trust/scam-check platforms and forums like Reddit or Trustpilot
  • Verify through official channels or direct testing before committing time or money
  • Best to consult recent, up-to-date sources rather than relying on this assessment

Analysis of Agentmemory

Overall verdict

  • AgentMemory (agent-memory.dev) appears to be a solid, purpose-built solution for developers who need persistent memory management in AI agent applications, offering a focused feature set for storing, retrieving, and managing contextual data across agent sessions.

Why this product is good

  • Provides dedicated memory persistence for AI agents, enabling context retention across sessions and conversations
  • Designed specifically for the agentic AI use case, which can simplify development compared to building custom memory layers
  • Likely offers developer-friendly APIs and SDKs to integrate memory capabilities quickly
  • Can improve agent performance by allowing recall of past interactions, user preferences, and long-term context
  • Reduces boilerplate work for teams building conversational or autonomous AI systems

Recommended for

  • Developers building AI agents or LLM-powered applications that require long-term memory
  • Teams creating conversational assistants that need to remember user context across sessions
  • Startups and companies prototyping autonomous or multi-step agent workflows
  • Engineers seeking a managed memory layer instead of building persistence infrastructure from scratch
  • Projects involving personalized AI experiences that depend on retained user data and history

Category Popularity

0-100% (relative to Fissible.dev and Agentmemory)

Fissible.dev

Agentmemory

CMS
100 100%
CMS
0% 0
AI
0 0%
AI
100% 100
APIs
100 100%
APIs
0% 0
Developer Tools
0 0%
Developer Tools
100% 100

User comments

Share your experience with using Fissible.dev and Agentmemory. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, Fissible.dev seems to be more popular. It has been mentiond 1 time since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Fissible.dev mentions (1)

  • Your API contract belongs in CI
    I run a company called Fissible and build a product called Station, a self-hosted Laravel CMS and workflow platform. Station ships with a Platform Core that lets focused modules (CMS, Flow, Forms, an API module, more on the way) dock in and share auth, navigation, search, and admin UI. - Source: dev.to / 4 months ago

Agentmemory mentions (0)

We have not tracked any mentions of Agentmemory yet. Tracking of Agentmemory recommendations started around Jun 2026.

What are some alternatives?

When comparing Fissible.dev and Agentmemory, you can also consider the following products

CMS - Enterprise IT Management Suites

ChainMemory - Portable, verifiable memory for AI agents — works across ChatGPT, Claude, Gemini and any MCP client

Elemeno - A modern API based content management platform

Mem0 - Your private, local memory layer for all AI tools

Grafbase - Unify the data layer with GraphQL

Memori - Persistent memory from agent trace, not just conversation

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