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Agentmemory VS Keylight.dev

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

Agentmemory

Persistent memory for Claude Code, Codex & coding agents

No screenshot yet
Rating
0 reviews
Alternatives Is it good?
Keylight.dev

The simplest way to license your app.

Rating
5.0 · 1 review
Pricing
Open source Freemium $19 / Monthly (Up to 2000 licenses active.)
Alternatives Is it good?
Snapveil
The easiest way to collect photos from weddings, parties, and events. Guests scan a QR code and upload pictures directly into your private gallery. Secure, fast, and powered by AI magic. sponsored

Which is more popular?

Based on our record, Keylight.dev seems to be more popular. It has been mentioned 4 times since March 2021.

social mentions
0 vs 4
Developer Tools popularity
86% vs 14%
alternatives listed
50 vs 1

Base details

Website, pricing, platforms and company facts side by side.

Agentmemory
Keylight.dev
Website agent-memory.dev keylight.dev
Pricing —
Open source Freemium $19 / Monthly (Up to 2000 licenses active.) Official pricing
Platforms —
Web
Company — Startup from Belgium · 1 - 9 employees · 2026
Listed in
AI Developer Tools Productivity Utilities +1
Developer Tools Software Development License Management Productivity Tech Web App Tool +4

About Agentmemory and Keylight.dev

In their own words, as submitted to SaaSHub.

Agentmemory
Keylight.dev

No description of Agentmemory yet.

Keylight sits between your payment provider and your app. Licenses, activations, customers, and usage all live here. Switch providers, or run several, without shipping a new build.

Read more about Keylight.dev

Features and specs

What each product offers, as listed by its team.

Agentmemory 5 features
Keylight.dev 16 features
  • 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

  • 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.
  • License Management
    Create, validate, revoke, and manage software licenses from one dashboard.
  • Device Activations
    Limit how many devices can use a license and manage individual activations.
  • Offline Access
    Keep apps working securely without a constant internet connection using signed offline leases.
  • License States
    Handle trial, free, paid, expired, limited, and grace-period access through one consistent state.
  • Payment Provider Integrations
    Connect Stripe, Paddle, Lemon Squeezy, Polar, Gumroad, and other payment platforms.
  • Provider Independence
    Change payment providers or use multiple providers without rebuilding your app’s licensing system.
  • Swift SDK Integration
    Add licensing to macOS and iOS apps using a native Swift package.
  • Secure License Validation
    Protect license data with cryptographic signatures and tamper-resistant validation.
  • Trials and Free Tiers
    Configure trials, free plans, fallbacks, and upgrade paths without building custom logic.
  • Customer Dashboard
    View licenses, customers, devices, activations, plans, and access status in one place.
  • License Analytics
    Track activations, active licenses, usage, and customer activity.
  • Key Rotation
    Rotate SDK signing keys without breaking older application versions.
  • Webhook Synchronization
    Convert payment, renewal, refund, cancellation, and subscription events into license updates.
  • Device-Bound Storage
    Store license data securely on the customer’s device without unnecessary Keychain prompts.
  • REST API
    Connect custom backends, checkout systems, and internal tools to Keylight.
  • Agentic Orchestration
    CLI usable by AI Agents to run the whole setup and more.

Analysis

An editorial look at what each product does well and who it suits.

Agentmemory
Keylight.dev

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

Overall verdict

  • I don't have verified, up-to-date information about Keylight.dev specifically, so I can't confirm its quality, features, or reliability. It may be a newer or niche tool that isn't well-documented in my training data. I'd recommend checking recent user reviews, the official website's documentation, and community forums (like GitHub, Reddit, or Twitter) for firsthand feedback before making a decision.

Why this product is good

  • Unable to verify specific features, pricing, or performance claims for this product
  • No confirmed user reviews or independent testing data available
  • Cannot confirm company legitimacy, support quality, or security practices without direct verification

Recommended for

  • Users willing to conduct their own due diligence by visiting the official site directly
  • Developers who can test the product via a free trial or demo before committing
  • Anyone who checks third-party review sites, GitHub issues, or community discussions for real user experiences

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Agentmemory
Keylight.dev
86% 86%
Developer Tools
14% 14%
0% 0%
Web App
100% 100%
100% 100%
AI
0% 0%
79% 79%
Productivity
21% 21%

Questions & Answers

As answered by people managing Agentmemory and Keylight.dev.

What makes your product unique?

Keylight.dev's answer:

Keylight keeps app licensing separate from payments. You can use Stripe, Paddle, Lemon Squeezy, Polar, Gumroad, or your own checkout without tying your app to one provider.

It handles license keys, device activations, trials, free tiers, offline access, grace periods, and signed license state through one SDK.

Why should a person choose your product over its competitors?

Keylight.dev's answer:

My goal is to make all apps work with Keylight. So all of your licenses, from any types of apps, is going through Keylight for analytics, customer portal, support, ...

Most licensing tools are bundled into a payment provider. Keylight is built as an independent licensing layer.

That means you can change payment providers, sell through multiple platforms, or change your pricing model without rebuilding licensing inside your app.

It also gives developers a ready-made SDK and dashboard instead of requiring them to build and maintain their own licensing backend.

How would you describe the primary audience of your product?

Keylight.dev's answer:

Keylight is primarily built for independent developers and software companies selling apps directly to customers.

Its main audience includes:

macOS and iOS developers Web app and SaaS developers Developers selling outside app stores Teams migrating from a payment provider’s built-in licensing Developers who need trials, device limits, offline access, and license analytics

What's the story behind your product?

Keylight.dev's answer:

Keylight started because I kept rebuilding the same licensing systems for different apps: license keys, trials, activations, offline access, device changes, and all the edge cases that come with them.

I also did not want licensing to be controlled by whichever payment provider an app happened to use.

So I built Keylight as a standalone layer between the app and the payment provider. Payment platforms send events to Keylight, and the app receives one consistent license state through the SDK.

Who are some of the biggest customers of your product?

Keylight.dev's answer:

That's confidential.

Which are the primary technologies used for building your product?

Keylight.dev's answer:

Swift and Swift Package Manager for the Apple SDK Rust SDK / JS SDK / C# SDK / C++ SDK TypeScript React Next.js Stripe Connect and payment-provider webhooks Cryptographic signatures for secure, offline-capable licenses REST APIs for application and provider integrations

User comments

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Agentmemory no reviews yet
Keylight.dev 5.0 · 1 review

We have no reviews of Agentmemory yet. Be the first one to post

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Agentmemory 0 mentions
Keylight.dev 4 mentions

Tracking Agentmemory since Jun 2026.

  • How offline license activation actually works
    You don't want to hand-roll Ed25519 and lease parsing. Most licensing SDKs hide this behind a couple of calls. With Keylight, for example, the offline path collapses to: activate once, then a local checkOnLaunch() that verifies the lease... - Source: dev.to / 3 months ago
  • I compared the licensing tools for my indie Mac app — the honest breakdown
    Full disclosure: I now build Keylight, so weigh this accordingly — I'm telling you the seam it's designed for, not that it wins every row. - Source: dev.to / 3 months ago
  • How to add license keys to a SwiftUI macOS app (in under an hour)
    Full docs and the free tier are at keylight.dev. If you're on Tauri or Electron instead of native Swift, the same SDK pattern exists in JS/Rust. - Source: dev.to / 3 months ago

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Alternatives to Agentmemory and Keylight.dev

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

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