Alternatives to LangMem
Compare LangMem alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to LangMem in 2026. Compare features, ratings, user reviews, pricing, and more from LangMem competitors and alternatives in order to make an informed decision for your business.
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1
Cognee
Cognee
Cognee is an open source AI memory engine that transforms raw data into structured knowledge graphs, enhancing the accuracy and contextual understanding of AI agents. It supports various data types, including unstructured text, media files, PDFs, and tables, and integrates seamlessly with several data sources. Cognee employs modular ECL pipelines to process and organize data, enabling AI agents to retrieve relevant information efficiently. It is compatible with vector and graph databases and supports LLM frameworks like OpenAI, LlamaIndex, and LangChain. Key features include customizable storage options, RDF-based ontologies for smart data structuring, and the ability to run on-premises, ensuring data privacy and compliance. Cognee's distributed system is scalable, capable of handling large volumes of data, and is designed to reduce AI hallucinations by providing AI agents with a coherent and interconnected data landscape.Starting Price: $25 per month -
2
Agno
Agno
Agno is a lightweight framework for building agents with memory, knowledge, tools, and reasoning. Developers use Agno to build reasoning agents, multimodal agents, teams of agents, and agentic workflows. Agno also provides a beautiful UI to chat with agents and tools to monitor and evaluate their performance. It is model-agnostic, providing a unified interface to over 23 model providers, with no lock-in. Agents instantiate in approximately 2μs on average (10,000x faster than LangGraph) and use about 3.75KiB memory on average (50x less than LangGraph). Agno supports reasoning as a first-class citizen, allowing agents to "think" and "analyze" using reasoning models, ReasoningTools, or a custom CoT+Tool-use approach. Agents are natively multimodal and capable of processing text, image, audio, and video inputs and outputs. The framework offers an advanced multi-agent architecture with three modes, route, collaborate, and coordinate.Starting Price: Free -
3
LangChain
LangChain
LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability. -
4
LangGraph
LangChain
Gain precision and control with LangGraph to build agents that reliably handle complex tasks. Build and scale agentic applications with LangGraph Platform. LangGraph's flexible framework supports diverse control flows – single agent, multi-agent, hierarchical, sequential – and robustly handles realistic, complex scenarios. Ensure reliability with easy-to-add moderation and quality loops that prevent agents from veering off course. Use LangGraph Platform to templatize your cognitive architecture so that tools, prompts, and models are easily configurable with LangGraph Platform Assistants. With built-in statefulness, LangGraph agents seamlessly collaborate with humans by writing drafts for review and awaiting approval before acting. Easily inspect the agent’s actions and "time-travel" to roll back and take a different action to correct course.Starting Price: Free -
5
EverMemOS
EverMind
EverMemOS is a memory-operating system built to give AI agents continuous, long-term, context-rich memory so they can understand, reason, and evolve over time. It goes beyond traditional “stateless” AI; instead of forgetting past interactions, it uses layered memory extraction, structured knowledge organization, and adaptive retrieval mechanisms to build coherent narratives from scattered interactions, allowing the AI to draw on past conversations, user history, or stored knowledge dynamically. On the benchmark LoCoMo, EverMemOS achieved a reasoning accuracy of 92.3%, outperforming comparable memory-augmented systems. Through its core engine (EverMemModel), the platform supports parametric long-context understanding by leveraging the model’s KV cache, enabling training end-to-end rather than relying solely on retrieval-augmented generation.Starting Price: Free -
6
Backboard
Backboard
Backboard is an AI infrastructure platform that provides a unified API layer giving applications persistent, stateful memory and seamless orchestration across thousands of large language models, built-in retrieval-augmented generation, and long-term context storage so intelligent systems can remember, reason, and act consistently over extended interactions rather than behave like one-off demos. It captures context, interactions, and long-term knowledge, storing and retrieving the right information at the right time while supporting stateful thread management with automatic model switching, hybrid retrieval, and flexible stack configuration so developers can build reliable AI systems without stitching together fragile workarounds. Backboard’s memory system consistently ranks high on industry benchmarks for accuracy, and its API lets teams combine memory, routing, retrieval, and tool orchestration into one stack that reduces architectural complexity.Starting Price: $9 per month -
7
Papr
Papr.ai
Papr is an AI-native memory and context intelligence platform that provides a predictive memory layer combining vector embeddings with a knowledge graph through a single API, enabling AI systems to store, connect, and retrieve context across conversations, documents, and structured data with high precision. It lets developers add production-ready memory to AI agents and apps with minimal code, maintaining context across interactions and powering assistants that remember user history and preferences. Papr supports ingestion of diverse data including chat, documents, PDFs, and tool data, automatically extracting entities and relationships to build a dynamic memory graph that improves retrieval accuracy and anticipates needs via predictive caching, delivering low latency and state-of-the-art retrieval performance. Papr’s hybrid architecture supports natural language search and GraphQL queries, secure multi-tenant access controls, and dual memory types for user personalization.Starting Price: $20 per month -
8
Crewship
Crewship
Crewship is the developer-first platform for deploying AI agent workflows. Deploy your CrewAI, LangGraph, and LangGraph.js agents with a single command and watch them execute in real-time. Key features include one-command deployment, real-time execution streaming, artifact management, auto-scaling, version control, and encrypted secrets management. Crewship handles infrastructure so developers can focus on building great AI agents. Multi-framework support with AutoGen, Pydantic AI, smolagents, OpenAI Agents, Mastra, and Agno coming soon.Starting Price: Free -
9
Membase
Membase
Membase is a unified AI memory layer platform designed to help AI agents and tools share and persist context so they “understand you” across sessions without forced repetition or isolated memory silos, enabling consistent conversational experiences and shared knowledge across AI assistants. It provides a secure, centralized memory layer that captures, stores, and syncs context, conversation history, and relevant knowledge across multiple AI agents and integrations with tools such as ChatGPT, Claude, Cursor, and others, so all connected agents can access a common context and avoid repeating user intents. Designed as a foundational memory service, it aims to maintain consistent context across your AI ecosystem, reducing friction and improving continuity in multi-tool workflows by keeping long-term context available and shared rather than locked within individual models or sessions, and letting users focus on outcomes instead of re-entering context for each agent request. -
10
PromptLayer
PromptLayer
The first platform built for prompt engineers. Log OpenAI requests, search usage history, track performance, and visually manage prompt templates. manage Never forget that one good prompt. GPT in prod, done right. Trusted by over 1,000 engineers to version prompts and monitor API usage. Start using your prompts in production. To get started, create an account by clicking “log in” on PromptLayer. Once logged in, click the button to create an API key and save this in a secure location. After making your first few requests, you should be able to see them in the PromptLayer dashboard! You can use PromptLayer with LangChain. LangChain is a popular Python library aimed at assisting in the development of LLM applications. It provides a lot of helpful features like chains, agents, and memory. Right now, the primary way to access PromptLayer is through our Python wrapper library that can be installed with pip.Starting Price: Free -
11
Letta
Letta
Create, deploy, and manage your agents at scale with Letta. Build production applications backed by agent microservices with REST APIs. Letta adds memory to your LLM services to give them advanced reasoning capabilities and transparent long-term memory (powered by MemGPT). We believe that programming agents start with programming memory. Built by the researchers behind MemGPT, introduces self-managed memory for LLMs. Expose the entire sequence of tool calls, reasoning, and decisions that explain agent outputs, right from Letta's Agent Development Environment (ADE). Most systems are built on frameworks that stop at prototyping. Letta' is built by systems engineers for production at scale so the agents you create can increase in utility over time. Interrogate the system, debug your agents, and fine-tune their outputs, all without succumbing to black box services built by Closed AI megacorps.Starting Price: Free -
12
ByteRover
ByteRover
ByteRover is a self-improving memory layer for AI coding agents that unifies the creation, retrieval, and sharing of “vibe-coding” memories across projects and teams. Designed for dynamic AI-assisted development, it integrates into any AI IDE via the Memory Compatibility Protocol (MCP) extension, enabling agents to automatically save and recall context without altering existing workflows. It provides instant IDE integration, automated memory auto-save and recall, intuitive memory management (create, edit, delete, and prioritize memories), and team-wide intelligence sharing to enforce consistent coding standards. These capabilities let developer teams of all sizes maximize AI coding efficiency, eliminate repetitive training, and maintain a centralized, searchable memory store. Install ByteRover’s extension in your IDE to start capturing and leveraging agent memory across projects in seconds.Starting Price: $19.99 per month -
13
Hyperspell
Hyperspell
Hyperspell is an end-to-end memory and context layer for AI agents that lets you build data-powered, context-aware applications without managing the underlying pipeline. It ingests data continuously from user-connected sources (e.g., drive, docs, chat, calendar), builds a bespoke memory graph, and maintains context so future queries are informed by past interactions. Hyperspell supports persistent memory, context engineering, and grounded generation, producing structured or LLM-ready summaries from the memory graph. It integrates with your choice of LLM while enforcing security standards and keeping data private and auditable. With one-line integration and pre-built components for authentication and data access, Hyperspell abstracts away the work of indexing, chunking, schema extraction, and memory updates. Over time, it “learns” from interactions; relevant answers reinforce context and improve future performance. -
14
Convo
Convo
Kanvo provides a drop‑in JavaScript SDK that adds built‑in memory, observability, and resiliency to LangGraph‑based AI agents with zero infrastructure overhead. Without requiring databases or migrations, it lets you plug in a few lines of code to enable persistent memory (storing facts, preferences, and goals), threaded conversations for multi‑user interactions, and real‑time agent observability that logs every message, tool call, and LLM output. Its time‑travel debugging features let you checkpoint, rewind, and restore any agent run state instantly, making workflows reproducible and errors easy to trace. Designed for speed and simplicity, Convo’s lightweight interface and MIT‑licensed SDK deliver production‑ready, debuggable agents out of the box while keeping full control of your data.Starting Price: $29 per month -
15
Maximem
Maximem
Maximem is an AI context management and memory platform designed to give generative AI systems a persistent, secure memory layer that retains and organizes information across conversations, applications, and models. Large language models typically operate with limited session memory, meaning they lose context between interactions and require users to repeatedly provide the same background information. Maximem addresses this limitation by creating a private memory vault that stores relevant context, preferences, historical data, and workflow information so AI systems can reference it in future interactions. It operates between AI models and applications, ensuring that conversations, knowledge, and user data are consistently available across different tools and sessions. This persistent memory allows AI assistants to deliver responses that are more personalized, accurate, and context-aware because the system can retrieve previously stored information. -
16
MemU
NevaMind AI
MemU is an intelligent memory layer designed specifically for large language model (LLM) applications, enabling AI companions to remember and organize information efficiently. It functions as an autonomous, evolving file system that links memories into an interconnected knowledge graph, improving accuracy, retrieval speed, and reducing costs. Developers can easily integrate MemU into their LLM apps using SDKs and APIs compatible with OpenAI, Anthropic, Gemini, and other AI platforms. MemU offers enterprise-grade solutions including commercial licenses, custom development, and real-time user behavior analytics. With 24/7 premium support and scalable infrastructure, MemU helps businesses build reliable AI memory features. The platform significantly outperforms competitors in accuracy benchmarks, making it ideal for memory-first AI applications. -
17
BrainAPI
Lumen Platforms Inc.
BrainAPI is the missing memory layer for AI. Large language models are powerful but forgetful — they lose context, can’t carry your preferences across platforms, and break when overloaded with information. BrainAPI solves this with a universal, secure memory store that works across ChatGPT, Claude, LLaMA and more. Think of it as Google Drive for memories: facts, preferences, knowledge, all instantly retrievable (~0.55s) and accessible with just a few lines of code. Unlike proprietary lock-in services, BrainAPI gives developers and users control over where data is stored and how it’s protected, with future-proof encryption so only you hold the key. It’s plug-and-play, fast, and built for a world where AI can finally remember.Starting Price: $0 -
18
MemMachine
MemVerge
An open-source memory layer for advanced AI agents. It enables AI-powered applications to learn, store, and recall data and preferences from past sessions to enrich future interactions. MemMachine’s memory layer persists across multiple sessions, agents, and large language models, building a sophisticated, evolving user profile. It transforms AI chatbots into personalized, context-aware AI assistants designed to understand and respond with better precision and depth.Starting Price: $2,500 per month -
19
OpenMemory
OpenMemory
OpenMemory is a Chrome extension that adds a universal memory layer to browser-based AI tools, capturing context from your interactions with ChatGPT, Claude, Perplexity and more so every AI picks up right where you left off. It auto-loads your preferences, project setups, progress notes, and custom instructions across sessions and platforms, enriching prompts with context-rich snippets to deliver more personalized, relevant responses. With one-click sync from ChatGPT, you preserve existing memories and make them available everywhere, while granular controls let you view, edit, or disable memories for specific tools or sessions. Designed as a lightweight, secure extension, it ensures seamless cross-device synchronization, integrates with major AI chat interfaces via a simple toolbar, and offers workflow templates for use cases like code reviews, research note-taking, and creative brainstorming.Starting Price: $19 per month -
20
Memories.ai
Memories.ai
Memories.ai builds the foundational visual memory layer for AI, transforming raw video into actionable insights through a suite of AI‑powered agents and APIs. Its Large Visual Memory Model supports unlimited video context, enabling natural‑language queries and automated workflows such as Clip Search to pinpoint relevant scenes, Video to Text for transcription, Video Chat for conversational exploration, and Video Creator and Video Marketer for automated editing and content generation. Tailored modules address security and safety with real‑time threat detection, human re‑identification, slip‑and‑fall alerts, and personnel tracking, while media, marketing, and sports teams benefit from intelligent search, fight‑scene counting, and descriptive analytics. With credit‑based access, no‑code playgrounds, and seamless API integration, Memories.ai outperforms traditional LLMs on video understanding tasks and scales from prototyping to enterprise deployment without context limitations.Starting Price: $20 per month -
21
myNeutron
Vanar Chain
Tired of repeating to your AI? myNeutron's AI Memory captures context from Chrome, emails, and Drive, organizes it, and syncs across your AI tools so you never re-explain. Join, capture, recall, and save time. Most AI tools forget everything the moment you close the window — wasting time, killing productivity, and forcing you to start over. MyNeutron fixes AI amnesia by giving your chatbots and AI assistants a shared memory across Chrome and all your AI platforms. Store prompts, recall conversations, keep context across sessions, and build an AI that actually knows you. One memory. Zero repetition. Maximum productivity.Starting Price: $6.99 -
22
mcp-use
mcp-use
mcp-use is an open source development platform offering SDKs, cloud infrastructure, and a developer-friendly control plane for building, managing, and deploying AI agents that leverage the Model Context Protocol (MCP). It enables connection to multiple MCP servers, each exposing specific tool capabilities like browsing, file operations, or specialized integrations, through a unified MCPClient. Developers can create custom agents (via MCPAgent) that dynamically select the most appropriate server for each task using configurable pipelines or a built-in server manager. It simplifies authentication, access control, audit logging, observability, sandboxed runtime environments, and deployment workflows, whether self-hosted or managed, making MCP development production-ready. With integrations for popular frameworks like LangChain (Python) and LangChain.js (TypeScript), mcp-use accelerates the creation of tool-enabled AI agents.Starting Price: Free -
23
Atla
Atla
Atla is the agent observability and evaluation platform that dives deeper to help you find and fix AI agent failures. It provides real‑time visibility into every thought, tool call, and interaction so you can trace each agent run, understand step‑level errors, and identify root causes of failures. Atla automatically surfaces recurring issues across thousands of traces, stops you from manually combing through logs, and delivers specific, actionable suggestions for improvement based on detected error patterns. You can experiment with models and prompts side by side to compare performance, implement recommended fixes, and measure how changes affect completion rates. Individual traces are summarized into clean, readable narratives for granular inspection, while aggregated patterns give you clarity on systemic problems rather than isolated bugs. Designed to integrate with tools you already use, OpenAI, LangChain, Autogen AI, Pydantic AI, and more. -
24
RemNote
RemNote
Build a life-long knowledge-base to organize your thinking and learning with powerful referencing and linking features. Create flashcards and practice with spaced repetition to deeply learn any body of knowledge. Link notes and ideas to supercharge your memory, organization, and thinking skills. Create flashcards directly within your notes to rapidly break down and remember any body of knowledge. Consolidate knowledge in your long-term memory with a personalized spaced-repetition learning schedule. Super-fast global search turns your notes into a lifelong knowledge base and library. Easily share documents (including flashcards) with teams, students, peers, or the world.Starting Price: $6 per month -
25
LangFast
Langfa.st
LangFast is a lightweight prompt testing platform designed for product teams, prompt engineers, and developers working with LLMs. It offers instant access to a customizable prompt playground—no signup required. Users can build, test, and share prompt templates using Jinja2 syntax with real-time raw outputs directly from the LLM, without any API abstractions. LangFast eliminates the friction of manual testing by letting teams validate prompts, iterate faster, and collaborate more effectively. Built by a team with experience scaling AI SaaS to 15M+ users, LangFast gives you full control over the prompt development process—while keeping costs predictable through a simple pay-as-you-go model.Starting Price: $60 one time -
26
BoxLang
BoxLang
BoxLang is a modern, dynamically and loosely typed scripting language for the Java Virtual Machine (JVM) that supports Object-Oriented (OO) and Functional Programming (FP) constructs. It can be deployed on multiple platforms and all operating systems, web servers, Java application servers, AWS Lambda, WebAssembly, and more. BoxLang combines many features from different programming languages to provide developers with a modern, fluent, and expressive syntax. BoxLang has been designed to be a highly modular and dynamic language that takes advantage of all the modern features of the JVM. It is dynamically typed, which means there's no need to declare types. It can perform type inference, auto-casting, and promotions between different types. The language adjusts to its deployed runtime and can add, remove, or modify methods and properties at runtime. -
27
iLangL Cloud
iLangL
iLangL Cloud is a middleware that is aimed to safely transfer content between content management systems and translation tools. iLangL serves as a bridge between a CMS and the following translation tools - Memsource, memoQ, and MultiTrans - helping users to easily transfer content between CMS and a translation tool. By using iLangL Cloud, you can be sure that all the content will go through safely to a translation tool and back, without damage to any sensitive data.Starting Price: $125 per month -
28
Mem0
Mem0
Mem0 is a self-improving memory layer designed for Large Language Model (LLM) applications, enabling personalized AI experiences that save costs and delight users. It remembers user preferences, adapts to individual needs, and continuously improves over time. Key features include enhancing future conversations by building smarter AI that learns from every interaction, reducing LLM costs by up to 80% through intelligent data filtering, delivering more accurate and personalized AI outputs by leveraging historical context, and offering easy integration compatible with platforms like OpenAI and Claude. Mem0 is perfect for projects such as customer support, where chatbots remember past interactions to reduce repetition and speed up resolution times; personal AI companions that recall preferences and past conversations for more meaningful interactions; AI agents that learn from each interaction to become more personalized and effective over time.Starting Price: $249 per month -
29
LangSmith
LangChain
Unexpected results happen all the time. With full visibility into the entire chain sequence of calls, you can spot the source of errors and surprises in real time with surgical precision. Software engineering relies on unit testing to build performant, production-ready applications. LangSmith provides that same functionality for LLM applications. Spin up test datasets, run your applications over them, and inspect results without having to leave LangSmith. LangSmith enables mission-critical observability with only a few lines of code. LangSmith is designed to help developers harness the power–and wrangle the complexity–of LLMs. We’re not only building tools. We’re establishing best practices you can rely on. Build and deploy LLM applications with confidence. Application-level usage stats. Feedback collection. Filter traces, cost and performance measurement. Dataset curation, compare chain performance, AI-assisted evaluation, and embrace best practices. -
30
DemoGPT
Melih Ünsal
DemoGPT is an open source platform that simplifies the creation of LLM (Large Language Model) agents by providing an all-in-one toolkit. It offers tools, frameworks, prompts, and models for rapid agent development. The platform automatically generates LangChain code, which can be used for creating interactive applications with Streamlit. DemoGPT translates user instructions into functional applications through a multi-step process: planning, task creation, and code generation. It supports a streamlined approach to building AI-powered agents, offering an accessible environment for developing sophisticated, production-ready solutions with GPT-3.5-turbo. Additionally, it integrates API usage and external API interaction in future updates.Starting Price: Free -
31
Lang.ai
Lang.ai
Lang auto-tags every support interaction with your own unique data categories, cutting average time to resolution by 60%+. Activate your customer support data to unlock a faster, smarter CX team. With better-categorized support interactions, you can automate manual agent tasks like routing, triage, and prioritization cutting average time to ticket resolution. Every company is sitting on a trove of customer interaction data. Lang helps you define your own unique CX categories to capture and structure more data than previously possible. Easily generate insights from your data that drive customer retention and surface revenue opportunities. With your own data language, Lang will help you auto-tag and categorize customer interactions to find new patterns in your data. Easily configure automation based on these insights with integrations into key CX systems. Auto-tag and categorize incoming support tickets in real-time. -
32
ZeroClaw
ZeroClaw
ZeroClaw is a Rust-native autonomous AI agent framework engineered for teams that require fast, secure, and highly modular agent infrastructure. It is designed as a compact, production-ready runtime that launches quickly, runs efficiently, and scales through interchangeable providers, channels, memory systems, and tools. Built around a trait-based architecture, ZeroClaw allows developers to swap model backends, communication layers, and storage implementations through configuration changes without rewriting core code, reducing vendor lock-in and improving long-term maintainability. It emphasizes a minimal footprint, shipping as a single binary of about 3.4 MB with startup times under 10 milliseconds and very low memory usage, making it suitable for servers, edge devices, and low-power hardware. Security is a first-class design goal, with sandbox controls, filesystem scoping, allowlists, and encrypted secret handling enabled by default.Starting Price: Free -
33
Langdock
Langdock
Native support for ChatGPT and LangChain. Bing, HuggingFace and more coming soon. Add your API documentation manually or import an existing OpenAPI specification. Access the request prompt, parameters, headers, body and more. Inspect detailed live metrics about how your plugin is performing, including latencies, errors, and more. Configure your own dashboards, track funnels and aggregated metrics.Starting Price: Free -
34
FastAgency
FastAgency
FastAgency is an open source framework designed to accelerate the deployment of multi-agent AI workflows from prototype to production. It provides a unified programming interface compatible with various agentic AI frameworks, enabling developers to deploy agentic workflows in both development and production settings. With features like multi-runtime support, seamless external API integration, and a command-line interface for orchestration, FastAgency simplifies the creation of scalable, production-ready architectures for serving AI workflows. Currently, it supports the AutoGen framework, with plans to extend support to CrewAI, Swarm, and LangGraph in the future. Developers can easily switch between frameworks, choosing the best one for their project's specific needs. FastAgency also features a common programming interface that enables the development of core workflows once and reuse them across various user interfaces without rewriting code.Starting Price: Free -
35
Mimecast Cloud Archive
Mimecast
Mimecast Cloud Archive has long set the industry standard for enterprise information archiving, helping to keep corporate knowledge available, protecting and preserving it, all while simplifying management and administration. By aggregating data across multiple platforms, organizations gain long-term business insights and create a secure, digital corporate memory while reducing costs and risks for legal and compliance teams. IT teams can reduce administrative overhead with streamlined management and By aggregating data across multiple platforms, organizations gain long-term business insights and create a secure, digital corporate memory while reducing costs and risks for legal and compliance teams. IT teams can reduce administrative overhead with streamlined management and simplified data recovery. Anytime, anywhere access to archive data improves employee productivity and workflow efficiency. -
36
Naptha
Naptha
Naptha is a modular AI platform for autonomous agents that empowers developers and researchers to build, deploy, and scale cooperative multi‑agent systems on the agentic web. Its core innovations include Agent Diversity, which continuously upgrades performance by orchestrating diverse models, tools, and architectures; Horizontal Scaling, which supports collaborative networks of millions of AI agents; Self‑Evolved AI, where agents learn and optimize themselves beyond human‑designed capabilities; and AI Agent Economies, which enable autonomous agents to generate useful goods and services. Naptha integrates seamlessly with popular frameworks and infrastructure, LangChain, AgentOps, CrewAI, IPFS, NVIDIA stacks, and more, via a Python SDK that upgrades existing agent frameworks with next‑generation enhancements. Developers can extend or publish reusable components on the Naptha Hub, run full agent stacks anywhere a container can execute on Naptha Nodes. -
37
Pylar
Pylar
Pylar is a secure data-access layer that sits between AI agents and your databases, enabling agents to safely interact with structured data without giving them direct database access. It connects to one or more data sources (like BigQuery, Snowflake, PostgreSQL, business apps such as HubSpot or Google Sheets). Pylar can create governed SQL views using its built-in SQL IDE; those views define exactly which tables, columns, and rows agents are allowed to access. It lets you build “MCP tools” (either by writing natural-language prompts or manual configuration) that wrap SQL queries into standardized, safe operations. Agents can access data through a single MCP endpoint, compatible with multiple agent builders like custom AI assistants, no-code automation tools, or integrations (e.g. Zapier, n8n, LangGraph, VS Code, etc.).Starting Price: $20 per month -
38
Truelang
Truelang
TrueLang is an AI-powered WordPress translation plugin designed to make website localization simple, fast, and cost-effective. It allows users to translate unlimited pages into unlimited languages using leading AI models like GPT, Claude, Gemini, and DeepSeek. The plugin operates on a one-time payment model, eliminating recurring subscription fees common in competing tools. Users can leverage their own API keys, ensuring full control over data and translation costs. TrueLang also supports multilingual SEO features such as translated URLs, meta tags, and hreflang integration. It integrates seamlessly with WordPress tools like WooCommerce, Elementor, and Yoast SEO. Overall, TrueLang provides a flexible and affordable solution for businesses looking to scale globally without ongoing costs.Starting Price: $99 one-time -
39
RA.Aid
RA.Aid
RA.Aid is an open source AI assistant that autonomously handles research, planning, and implementation to expedite software development processes. Built on LangGraph's agent-based task execution framework, RA.Aid operates through a three-stage architecture. RA.Aid supports multiple AI providers, including Anthropic's Claude, OpenAI, OpenRouter, and Gemini, allowing users to select models that best fit their requirements. It also features web research capabilities, enabling the agent to pull real-time information from the internet to enhance its understanding and execution of tasks. It offers an interactive chat mode, allowing users to guide the agent directly, ask questions, or redirect tasks as needed. Additionally, RA.Aid integrates with 'aider' via the '--use-aider' flag to leverage specialized code editing capabilities. It is designed with a human-in-the-loop interaction mode, enabling the agent to seek user input during task execution to ensure higher accuracy.Starting Price: Free -
40
Multilith
Multilith
Multilith gives AI coding tools a persistent memory so they understand your entire codebase, architecture decisions, and team conventions from the very first prompt. With a single configuration line, Multilith injects organizational context into every AI interaction using the Model Context Protocol. This eliminates repetitive explanations and ensures AI suggestions align with your actual stack, patterns, and constraints. Architectural decisions, historical refactors, and documented tradeoffs become permanent guardrails rather than forgotten notes. Multilith helps teams onboard faster, reduce mistakes, and maintain consistent code quality across contributors. It works seamlessly with popular AI coding tools while keeping your data secure and fully under your control. -
41
Literal AI
Literal AI
Literal AI is a collaborative platform designed to assist engineering and product teams in developing production-grade Large Language Model (LLM) applications. It offers a suite of tools for observability, evaluation, and analytics, enabling efficient tracking, optimization, and integration of prompt versions. Key features include multimodal logging, encompassing vision, audio, and video, prompt management with versioning and AB testing capabilities, and a prompt playground for testing multiple LLM providers and configurations. Literal AI integrates seamlessly with various LLM providers and AI frameworks, such as OpenAI, LangChain, and LlamaIndex, and provides SDKs in Python and TypeScript for easy instrumentation of code. The platform also supports the creation of experiments against datasets, facilitating continuous improvement and preventing regressions in LLM applications. -
42
NVIDIA NeMo Guardrails
NVIDIA
NVIDIA NeMo Guardrails is an open-source toolkit designed to enhance the safety, security, and compliance of large language model-based conversational applications. It enables developers to define, orchestrate, and enforce multiple AI guardrails, ensuring that generative AI interactions remain accurate, appropriate, and on-topic. The toolkit leverages Colang, a specialized language for designing flexible dialogue flows, and integrates seamlessly with popular AI development frameworks like LangChain and LlamaIndex. NeMo Guardrails offers features such as content safety, topic control, personal identifiable information detection, retrieval-augmented generation enforcement, and jailbreak prevention. Additionally, the recently introduced NeMo Guardrails microservice simplifies rail orchestration with API-based interaction and tools for enhanced guardrail management and maintenance. -
43
Graph Engine
Microsoft
Graph Engine (GE) is a distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine. The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set. The capability of fast data exploration and distributed parallel computing makes GE a natural large graph processing platform. GE supports both low-latency online query processing and high-throughput offline analytics on billion-node large graphs. Schema does matter when we need to process data efficiently. Strongly-typed data modeling is crucial for compact data storage, fast data access, and clear data semantics. GE is good at managing billions of run-time objects of varied sizes. One byte counts as the number of objects goes large. GE provides fast memory allocation and reallocation with high memory ratios. -
44
Lunary
Lunary
Lunary is an AI developer platform designed to help AI teams manage, improve, and protect Large Language Model (LLM) chatbots. It offers features such as conversation and feedback tracking, analytics on costs and performance, debugging tools, and a prompt directory for versioning and team collaboration. Lunary supports integration with various LLMs and frameworks, including OpenAI and LangChain, and provides SDKs for Python and JavaScript. Guardrails to deflect malicious prompts and sensitive data leaks. Deploy in your VPC with Kubernetes or Docker. Allow your team to judge responses from your LLMs. Understand what languages your users are speaking. Experiment with prompts and LLM models. Search and filter anything in milliseconds. Receive notifications when agents are not performing as expected. Lunary's core platform is 100% open-source. Self-host or in the cloud, get started in minutes.Starting Price: $20 per month -
45
HeapHero
Tier1app
Due to inefficient programming, modern applications waste 30% to 70% of memory. HeapHero is the industry's first tool to detect the amount of wasted memory. It reports what lines of source code originating the memory wastage and solutions to fix them. A Memory leak is a type of resource drain that occurs when an application allocates memory and does not release after finish using it. This allocated memory can not be used for any other purpose and it remains wasted. As a consequence, Java applications will exhibit one or more of these non-desirable behaviors: poor response time, long JVM pauses, application hang, or even crash. Android mobile applications can also suffer from memory leaks, which can be attributed to poor programming practices. Memory leaks in mobile apps bare direct consumer impact and dissatisfaction. Memory leak slows down the application's responsiveness, makes it hang or crashes the application entirely. It will leave an unpleasant and negative user experience. -
46
KeyMate.AI
KeyMate.AI
Elevate your research, project, and daily use with the search, browse, and long-term memory features of Keymate. A personal information store learning from your conversations and PDFs to make AI understand you. Store data to your personalized storage while using Keymate. Whenever needed ChatGPT stores more data it and it can query your preferences and past interactions to this personalized storage. You can transfer information context between different conversations in ChatGPT this way. -
47
Chainlit
Chainlit
Chainlit is an open-source Python package designed to expedite the development of production-ready conversational AI applications. With Chainlit, developers can build and deploy chat-based interfaces in minutes, not weeks. The platform offers seamless integration with popular AI tools and frameworks, including OpenAI, LangChain, and LlamaIndex, allowing for versatile application development. Key features of Chainlit include multimodal capabilities, enabling the processing of images, PDFs, and other media types to enhance productivity. It also provides robust authentication options, supporting integration with providers like Okta, Azure AD, and Google. The Prompt Playground feature allows developers to iterate on prompts in context, adjusting templates, variables, and LLM settings for optimal results. For observability, Chainlit offers real-time visualization of prompts, completions, and usage metrics, ensuring efficient and trustworthy LLM operations. -
48
LangProtect
LangProtect
LangProtect is an AI-native security and governance platform that protects LLM and Generative AI applications from prompt injection, jailbreaks, sensitive data leakage, and unsafe or non-compliant outputs. Built for production GenAI, it enforces real-time runtime controls at the AI execution layer by inspecting prompts, model responses, and tool/function calls as they happen. This allows teams to block high-risk behavior before it reaches end users, triggers downstream actions, or exposes confidential data. LangProtect integrates into existing LLM stacks via an API-first approach with minimal latency and supports cloud, hybrid, and on-prem deployments for enterprise security and data residency needs. It also secures modern architectures such as RAG pipelines and agentic workflows with policy-driven enforcement, continuous visibility, and audit-ready governance. -
49
EarlyCore
EarlyCore
EarlyCore is a security platform built for AI agents. It automates pre-production attack testing, real-time monitoring, and compliance reporting across the full agent lifecycle. Scans agents against thousands of attack scenarios covering prompt injection, jailbreaking, data exfiltration, tool misuse, and supply chain threats. In production, tracks every agent action, establishes behavioral baselines, and flags anomalies in real time. Alerts push to Slack, email, or webhooks. Compliance docs generate automatically, mapped to ISO 42001, NIST AI RMF, EU AI Act, SOC 2, and GDPR. Always audit-ready. Deploys in 15 minutes with zero code changes. Integrates with AWS Bedrock, Vertex AI, LangChain, and more. Multi-tenant support for agencies and MSSPs. Built for security teams, agencies, and MSSPs securing AI agents at scale.Starting Price: $100/month -
50
Agent Builder
OpenAI
Agent Builder is part of OpenAI’s tooling for constructing agentic applications, systems that use large language models to perform multi-step tasks autonomously, with governance, tool integration, memory, orchestration, and observability baked in. The platform offers a composable set of primitives—models, tools, memory/state, guardrails, and workflow orchestration- that developers assemble into agents capable of deciding when to call a tool, when to act, and when to halt and hand off control. OpenAI provides a new Responses API that combines chat capabilities with built-in tool use, along with an Agents SDK (Python, JS/TS) that abstracts the control loop, supports guardrail enforcement (validations on inputs/outputs), handoffs between agents, session management, and tracing of agent executions. Agents can be augmented with built-in tools like web search, file search, or computer use, or custom function-calling tools.
