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Agentmemory VS Orbator

Compare Agentmemory VS Orbator and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Reviews
  3. ยป Alternatives

Agentmemory logo Agentmemory

Persistent memory for Claude Code, Codex & coding agents

Orbator logo Orbator

See whether ChatGPT, Claude, Gemini, Perplexity & Grok recommend you in your category โ€” and what to do about it. Run a free AI-visibility check.
Not present
  • Orbator Are you recommended in AI search?
    Are you recommended in AI search? //
    2026-08-06

Orbator reveals whether ChatGPT, Claude, Gemini, Perplexity, and Grok recommend your product in your categoryโ€”and delivers actionable insights on how to fix it. Most visibility tools measure SEO rankings; Orbator measures what actually matters now: AI assistant recommendations. Run a free visibility check to see real queries and which sources AI cited. Weekly tracking shows how AI answer recommendations drift 40โ€“60% monthly, so you stay informed of changes. The platform handles directory placements, citation opportunities, and proof-of-placement receipts. Free tier includes the visibility check and a 50+ directory match. Paid tiers range from weekly monitoring ($39/mo) to done-for-you optimization and managed placement fulfillment. Local businesses use it to become the AI answer for their category in their city; SaaS founders track multi-channel AI visibility. No SEO expertise required; Orbator's team manages placement for higher plans. Built on the open-source AI Recommendation Index, tracking 13,779 products across 293 categories weekly.

Agentmemory

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

Orbator

Website
orbator.io
Pricing URL
Official Orbator Pricing
$ Details
freemium $39.0 / Monthly ("Visibility","10 tracked prompts","Weekly")
Platforms
Web
Release Date
2026 June
Startup details
Country
United States
State
FL
City
Miami
Founder(s)
Henrik Telle
Employees
1 - 9
Edit details

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.

Orbator features and specs

  • AI Visibility Scan
    Runs your buyers questions across ChatGPT, Claude, Gemini, Perplexity and Grok and shows whether each unique recommends you. First scan is Free.
  • Tracked Buyer Prompts
    Neutral "best X for Y" questions tracked per product, never your own name, so results reflect what a stranger is actually told.
  • Weekly Rechecks & Drop Alerts
    Every tracked prompt is re-asked weekly. You're alerted the week an engine drops you from its answers.
  • Competitor Answer Breakdowns
    See who each engine recommends instead of you, and how answers differ engine by engine.
  • Citation Source Map
    The exact sites each engine read before answering, labeled vendor-owned vs independent.
  • Done-For-You-Submissions
    Get listed on the AI-cited sources you're missing from. The chrome extension autofills the forms from your launch kit.

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 Agentmemory and Orbator)

Agentmemory

Orbator

AI
86 86%
AI
14% 14
AI Visibility
0 0%
AI Visibility
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
SaaS
0 0%
SaaS
100% 100

Questions & Answers

As answered by people managing Agentmemory and Orbator.

What makes your product unique?

Orbator's answer:

Orbator measures whether AI assistants actually recommend your product. When buyers ask ChatGPT, Claude, Gemini, Perplexity or Grok for the best tool in a category, most founders have no idea if they are in the answer.

Orbator:

  • runs the exact questions your buyers ask, across all five engines
  • shows who gets recommended and who gets skipped
  • reveals which sources each engine read before answering
  • gets you listed on the sources AI actually cites

Most tools track Google rankings. Orbator tracks the AI answers where a growing share of buying research now starts.

Why should a person choose your product over its competitors?

Orbator's answer:

Three reasons.

  • Methodology. Orbator only asks neutral buyer questions, never your product name. A forced mention is not a recommendation, so reports show what a stranger would actually be told.
  • Evidence. Full answers are retained and every citation is resolved to its source. Any number in a report can be traced, and the methodology is public.
  • Action. Measurement alone moves nothing. Every scan comes with the fix list, the specific AI-cited sources you are missing from, and Orbator does the submissions for you.

The first scan is free, so the honest pitch is simple: run it and see where you stand before spending anything.

How would you describe the primary audience of your product?

Orbator's answer:

Founders and small software teams who sell to people that research with AI, plus local businesses (restaurants, med spas, dentists, law firms) whose customers ask for the best option near them in a chat window instead of a search box.

The typical user is a founder who just discovered ChatGPT recommends their competitor and wants to know why, and what to do about it.

What's the story behind your product?

Orbator's answer:

Orbator is built by a solo founder who runs both a restaurant and several small software products, so he sits on both sides of the problem. The trigger was watching buyers quietly switch from googling to asking AI assistants, and realizing there was no honest instrument for the obvious question: when someone asks AI for what I sell, am I the answer?

Existing SEO tools measure Google. Orbator was built to measure the answers themselves. It is also self-measuring: Orbator uses its own index to track whether AI recommends Orbator.

Which are the primary technologies used for building your product?

Orbator's answer:

  • Backend: Node.js and Express
  • Frontend: Next.js and React
  • Data: PostgreSQL, including a citation index with full retained answer texts
  • Infrastructure: self-hosted with Docker on European cloud servers
  • AI engines: official APIs of OpenAI, Anthropic, Google, Perplexity and xAI, with web search enabled
  • Submission assistant: Chrome extension (Manifest V3)

User comments

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What are some alternatives?

When comparing Agentmemory and Orbator, you can also consider the following products

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

Am I Visible on AI - Wondering 'am I visible on AI?' Find out instantly. Free tool analyzes if ChatGPT, Claude & GEmini can access your website with detailed optimization tips (e.g. site structure, content, LLMs.text, etc.)

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

BrandPin.ai - The AI Visibility Measurement & GEO Tracking Platform. See whether ChatGPT, Gemini and Claude name and recommend your brand when buyers ask - Share of Voice, Competitor Gap, every number traceable to a real AI answer.

Memori - Persistent memory from agent trace, not just conversation

Ahrefs - Ahrefs is a toolset for SEO and marketing. We have tools for backlink research, organic traffic research, keyword research, content marketing & more. Give Ahrefs a try!

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