Software Alternatives, Accelerators & Startups
Register | Login

OpenMemory VS Underscore Done

Compare OpenMemory VS Underscore Done and see what are their differences

boldrouter
A unified, OpenAI-compatible gateway to every major LLM provider. One endpoint, one key, one bill - with automatic routing and failover. sponsored
Contents:
  1. ยป Base Details
  2. ยป Reviews
  3. ยป Alternatives

OpenMemory logo OpenMemory

Give AI agents long-term memory.

Underscore Done logo Underscore Done

Real-world tasks your agent can't do alone.
Not present
  • Underscore Done Main Screen
    Main Screen //
    2026-08-09

Underscore Done (_done) is a suite of pay-per-call utility APIs built for AI agents. No API keys, no subscriptions - agents pay per request with USDC via the x402 protocol

OpenMemory

Website
github.com
Pricing URL
-
$ Details
-
Release Date
-
Edit details

Underscore Done

Website
underscoredone.com
Pricing URL
Official Underscore Done Pricing
$ Details
paid $0.01 (Per api call)
Release Date
2026 July
Startup details
Country
United States
State
texas
City
Austin
Edit details

OpenMemory features and specs

  • Open Source
    OpenMemory is an open-source project, allowing developers to freely use, modify, and distribute the software according to their needs.
  • Community Support
    Being hosted on GitHub, OpenMemory benefits from a community of contributors who can provide support, improvements, and bug fixes.
  • Free Access
    The project is available for free, lowering the barrier to entry for individuals and organizations looking to incorporate memory management solutions.
  • Transparency
    The open-source nature ensures transparency in how memory is managed, which can help in security reviews and performance optimization.
  • Customizability
    Users and developers can tailor the system to better fit their specific requirements due to the customizable nature of open-source software.

Possible disadvantages of OpenMemory

  • Lack of Official Support
    As an open-source project, there may be no official customer support, making it potentially challenging for users to resolve issues without community help.
  • Variable Quality
    Contributions from multiple sources can lead to inconsistencies in code quality and documentation, which might affect reliability.
  • Potential Security Risks
    Open-source projects can be subject to security vulnerabilities if not regularly monitored and updated by the community.
  • Complexity
    The system might require a level of technical expertise to implement, customize, and maintain, which can be a barrier for less-experienced users.
  • Limited Documentation
    Open source projects sometimes suffer from sparse or outdated documentation, which can hinder user understanding and implementation.

Underscore Done features and specs

No features have been listed yet.

Analysis of OpenMemory

Overall verdict

  • OpenMemory is a solid open-source memory layer for AI applications, offering a self-hostable, privacy-focused way to give LLMs persistent, portable memory across sessions and tools.

Why this product is good

  • Open-source and self-hostable, giving you full control over your data and avoiding vendor lock-in
  • Provides persistent, portable memory that can be shared across different AI apps and LLM clients
  • Privacy-focused design keeps sensitive memory data local rather than sending it to third-party services
  • Integrates with popular protocols like MCP (Model Context Protocol), making it compatible with many AI tools
  • Active community and transparent development typical of open-source projects allow for customization and contributions

Recommended for

  • Developers building AI applications that need long-term or cross-session memory
  • Privacy-conscious users who want to keep AI memory data on their own infrastructure
  • Teams wanting a vendor-neutral, portable memory layer shared across multiple LLM clients
  • Hobbyists and tinkerers comfortable with self-hosting and open-source tooling
  • Projects using MCP-compatible AI assistants that require persistent context

Category Popularity

0-100% (relative to OpenMemory and Underscore Done)

OpenMemory

Underscore Done

AI
80 80%
AI
20% 20
AI Agents
0 0%
AI Agents
100% 100
Productivity
100 100%
Productivity
0% 0
Developer Tools
100 100%
Developer Tools
0% 0

Questions & Answers

As answered by people managing OpenMemory and Underscore Done.

What makes your product unique?

Underscore Done's answer:

We provide data and actions that AI cannot achieve.

Also we don't require accounts, registration, api keys. And we charge per usage and never charge monthly subscriptions.

How would you describe the primary audience of your product?

Underscore Done's answer:

Ai Agents that work on behalf of people.

User comments

Share your experience with using OpenMemory and Underscore Done. For example, how are they different and which one is better?
Log in or Post with

What are some alternatives?

When comparing OpenMemory and Underscore Done, you can also consider the following products

Supermemory - ai second brain for all your saved stuff

AgentGatePay - Enable AI agents to make autonomous payments with AP2 mandates and X402 protocol. Multi-chain crypto, budget controls, instant settlement.

Mem - Capture and access information from anywhere

x402 - An open protocol for internet-native payments from Coinbase

Byterover - Memory layer for smarter AI coding agents

Mengram - AI memory API with 3 types: facts, events, and workflows

Loading...