Alternatives to Engram
Compare Engram alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Engram in 2026. Compare features, ratings, user reviews, pricing, and more from Engram competitors and alternatives in order to make an informed decision for your business.
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1
Pinecone
Pinecone
The AI Knowledge Platform. The Pinecone Database, Inference, and Assistant make building high-performance vector search apps easy. Developer-friendly, fully managed, and easily scalable without infrastructure hassles. Once you have vector embeddings, manage and search through them in Pinecone to power semantic search, recommenders, and other applications that rely on relevant information retrieval. Ultra-low query latency, even with billions of items. Give users a great experience. Live index updates when you add, edit, or delete data. Your data is ready right away. Combine vector search with metadata filters for more relevant and faster results. Launch, use, and scale your vector search service with our easy API, without worrying about infrastructure or algorithms. We'll keep it running smoothly and securely. -
2
Qdrant
Qdrant
Qdrant is a high-performance, composable vector search engine built in Rust for production-grade semantic, hybrid, and agentic workloads. Combine dense vectors, sparse vectors, metadata filters, multi-vector representations, and custom scoring as primitives at query time. Written in Rust for memory efficiency, SIMD optimization, and predictable performance without garbage collection pauses. No wrappers, no bolt-ons, no legacy compromises — just a custom HNSW implementation and storage engine built specifically for vector workloads. -
3
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 -
4
Hindsight
Vectorize
Hindsight is an agent memory system built to create smarter AI agents that learn over time instead of starting every conversation from zero. Most agent memory systems focus on recalling conversation history, but Hindsight is focused on making agents learn, not just remember. It gives AI agents persistent long-term memory using biomimetic data structures, helping them retain facts, recall relevant context, and reflect on experience as part of reasoning. Hindsight is designed for agents that need to understand who a user is, what has been discussed, what preferences have emerged, what decisions were made, and how behavior should adapt across sessions. It provides three core operations: retain, recall, and reflect. Retain stores new information, recall retrieves the right memories when needed, and reflect helps agents synthesize observations, form mental models, and learn from prior interactions.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
LangMem
LangChain
LangMem is a lightweight, flexible Python SDK from LangChain that equips AI agents with long-term memory capabilities, enabling them to extract, store, update, and retrieve meaningful information from past interactions to become smarter and more personalized over time. It supports three memory types and offers both hot-path tools for real-time memory management and background consolidation for efficient updates beyond active sessions. Through a storage-agnostic core API, LangMem integrates seamlessly with any backend and offers native compatibility with LangGraph’s long-term memory store, while also allowing type-safe memory consolidation using schemas defined in Pydantic. Developers can incorporate memory tools into agents using simple primitives to enable seamless memory creation, retrieval, and prompt optimization within conversational flows. -
7
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. -
8
OpenViking
OpenViking
OpenViking is an open source context database designed specifically for AI agents, built around a file-system paradigm that unifies the management of memories, resources, and skills. Instead of treating context as scattered chunks in a fragmented vector store, OpenViking organizes agent context into a virtual file system under the viking protocol, giving agents a structured way to store, navigate, retrieve, and observe the information they need. It is designed to help developers move beyond the hassle of manual context management by giving agents a minimalist interaction model for context, similar to reading and writing files. OpenViking supports hierarchical context loading, semantic retrieval, recursive retrieval, sessions, metrics, and observability, making it possible for AI agents to access the right level of information without stuffing everything into the prompt.Starting Price: Free -
9
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. -
10
MemClaw
Caura AI
MemClaw is a persistent-memory service for LLM-based agents and a governed shared memory layer for agent fleets. It is designed to help AI agents learn from each other by turning isolated agent context into a Company Brain with memory, governance, provenance, contradiction detection, and visibility scopes built in from day one. MemClaw separates an organization’s agent force, including tenants, fleets, nodes, and agents, from the governed memory plane through MCP Server, REST API, OpenClaw plugin, MemClaw Core, and persistent storage. Agents can write to and recall from the Company Brain through MCP-compatible tools, direct HTTPS calls, or OpenClaw integration, while MemClaw Core runs enrichment such as entity extraction, contradiction detection, PII scanning, and lifecycle transitions before anything is stored. Every memory can be stamped with a visibility scope, auto-classified into types such as fact, episode, decision, preference, rule, plan, commitment, action, and outcome.Starting Price: $49 per month -
11
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. -
12
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 -
13
Memory AGI
Memory AGI
Memory AGI is a runtime memory layer for AI agents, built around the idea of giving agents real muscle memory. Hand over a slice of company data, and Memory AGI builds the organization’s knowledge and runtime memory layer, grounds agents in the business, and keeps that context current automatically. Your AI is only as good as the context you give it; without it, agents stay stuck at an intern-level, guessing at how the company runs. Memory AGI turns processes into knowledge agents that can actually execute, so they run reliably, show their work, and can be trusted with what they ship. It is built on three layers of muscle memory. Dynamic Ingestion captures and structures the company’s unique knowledge from voice notes, internal documents, or the tools where data already lives. The Runtime Memory Layer gives agents access to a live, de-duplicated context layer; a company knowledge base that humans, agents, and automations can all draw on to perform tasks like the best employees. -
14
MythOS
MythOS
MythOS is a shared memory system between you and every AI you use, built to help people stop re-explaining themselves across models, agents, and channels. It is designed for people who write to think, giving them a modular thinking system for structured notes, memos, contextual maps, and AI-powered workflows. Users can capture what they read, connect what they think, and publish what matters while keeping their library one click away from every AI. MythOS works as a personal knowledge operating system where memory, notes, ideas, resources, and context can be organized into structured documents that stay useful over time. Its approach treats knowledge as a process, not a one-time activity, so living documents can remain in progress, evolve, and connect with related people, projects, topics, and ideas. It supports contextual maps, public memos, private knowledge, AI-ready memory, exportable data, and workflows that help users build a durable layer of context.Starting Price: $10 per month -
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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 -
16
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 -
17
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. -
18
MemPalace
MemPalace
MemPalace is a local-first storage and retrieval system for AI workflows, built to give AI a memory while keeping the user’s words under their own control. It stores conversations verbatim instead of reducing them to summaries, then organizes that memory into a navigable “palace” structure inspired by the ancient memory palace technique. Conversations can be arranged into wings for people, projects, or topics, with rooms and drawers used to make information easier to locate, narrow, and retrieve later. It is designed for people who believe their words are theirs, with local-first storage, zero telemetry, and a privacy-focused approach that keeps memory on the user’s machine. MemPalace supports AI workflows through MCP tooling, including tools for palace reads and writes, knowledge-graph operations, cross-wing navigation, drawer management, and agent diaries.Starting Price: Free -
19
PlatformPilot
DynG AI
PlatformPilot is a company brain for AI-first teams. It captures how your company actually works, your decisions, playbooks, and tribal knowledge, and turns it into a living memory your team and your AI agents can use to answer questions and take action across all your tools. Unlike search tools that only retrieve, PlatformPilot reasons across your systems, shows the why behind every answer, and acts on your own playbooks, in your own cloud, getting sharper every time it is used. It connects to your stack through the Model Context Protocol (MCP), so it works as a shared memory layer inside the tools your team already uses, including Claude Code, Claude Desktop, and OpenAI-based agents. Memory evolves as you work. - Living memory that learns from outcomes, not just stores notes - Reasoning across all your tools. We support +200 tools. - Plain-language search over your team's decisions, playbooks, and history - Self-organizing knowledgeStarting Price: $100 -
20
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 -
21
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 -
22
CMEM Cloud
cmem.ai
CMEM Cloud is the cloud sync layer for claude-mem, built to link AI agent memory everywhere through one private MCP link. claude-mem is the open source engine that takes notes while an agent works, and CMEM Cloud mirrors that local memory so agents can recall it across every session, machine, editor, and MCP-compatible client. Instead of making users re-explain context, paste old notes, or restart from zero, the system captures decisions, bug fixes, dead ends, environment notes, architecture choices, and other structured observations as the agent works. Those observations are stored in a temporal database, searched by meaning through vector recall, and made available through a private MCP endpoint that any compatible agent can read and write through. It starts with installing the local engine, letting a second model write structured notes out of band, syncing the local database to CMEM Cloud, and then recalling that memory anywhere.Starting Price: Free -
23
claude-mem
cmem.ai
claude-mem is an offline-first cloud memory for AI agents, built around an open source engine and a cloud sync layer that links agent memory everywhere through one private MCP link. It is designed so coding agents and AI assistants do not start from zero every session, every machine, or every editor. claude-mem takes notes while an agent works, capturing decisions, fixes, dead ends, environment notes, architecture choices, and other structured observations in a temporal database. CMEM Cloud then mirrors that local memory behind a private Model Context Protocol endpoint, allowing any compatible agent or IDE to read and write the same memory across tools such as Claude Code, Cursor, Windsurf, OpenCode, Codex CLI, Gemini CLI, and VS Code. It works locally first, with or without a network, while keeping memory synchronized when cloud access is available.Starting Price: Free -
24
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 -
25
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 -
26
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 -
27
Zep
Zep
Zep ensures your assistant remembers past conversations and resurfaces them when relevant. Identify your user's intent, build semantic routers, and trigger events, all in milliseconds. Emails, phone numbers, dates, names, and more, are extracted quickly and accurately. Your assistant will never forget a user. Classify intent, emotion, and more and turn dialog into structured data. Retrieve, analyze, and extract in milliseconds; your users never wait. We don't send your data to third-party LLM services. SDKs for your favorite languages and frameworks. Automagically populate prompts with a summary of relevant past conversations, no matter how distant. Zep summarizes, embeds, and executes retrieval pipelines over your Assistant's chat history. Instantly and accurately classify chat dialog. Understand user intent and emotion. Route chains based on semantic context, and trigger events. Quickly extract business data from chat conversations.Starting Price: Free -
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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 -
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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 -
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Memdex
Memdex
Memdex turns every AI conversation into reusable local memory by auto-saving chats and bringing the right context back when users need it across ChatGPT, Claude, Gemini, and more. It solves the problem of scattered AI conversations that are hard to find, stuck inside separate tools, and difficult to reuse when starting a new chat. Users can click the Memdex button to save a conversation or turn on auto-save so every AI conversation is captured automatically across supported tools. Memdex then detects relevant context as the user types in any AI tool, highlighting matching words from saved conversations, like spell-check, but for context. When a match appears, users can attach the full previous conversation with one click, allowing the AI to pick up where the earlier discussion left off without re-explaining background, preferences, or project details.Starting Price: $7 per month -
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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. -
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Subspace
Subspace
Subspace is an AI-native agent workspace designed to help developers and teams manage, coordinate, and collaborate with multiple coding agents in a single unified environment while preserving context across sessions. Instead of treating each AI interaction as isolated, the platform builds persistent memory in the background by compressing every conversation into structured observations such as decisions, blockers, and progress, which are continuously synthesized into a clear, evolving project state. This shared memory belongs to the workspace rather than any individual tool, allowing different agents like Claude Code, Codex, or others to seamlessly pick up where previous sessions left off without requiring repeated explanations or manual context transfer. Subspace integrates terminals, files, documentation, browser views, and git workflows into organized workspaces, enabling users to run multiple agents side by side and switch between projects almost instantly.Starting Price: $12 per month -
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Graphify
Graphify
Graphify is an open source knowledge graph engine that turns any input, including code, docs, papers, meetings, images, browser tabs, and commits, into one traversable graph with complete recall. It is built as persistent memory for AI coding assistants, giving tools like Claude Code, Codex, OpenCode, Cursor, Gemini CLI, GitHub Copilot CLI, Aider, Factory Droid, Kimi Code, Kiro, Pi, and Google Antigravity a queryable understanding of a project instead of making them repeatedly grep through files. Users can point Graphify at any directory, and it builds an initial corpus through AST extraction, semantic analysis, and Leiden clustering, transforming an entire codebase or document corpus into a graph in one pass. Unlike RAG pipelines that re-embed everything on every change, Graphify maintains a living graph that updates only affected nodes and edges when files change, allowing the rest of the corpus to stay intact even at enterprise scale.Starting Price: Free -
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Mira
Mira
Mira is a truly personal AI agent that acts inside Telegram across personal and group chats with zero setup. Built to live in the messenger where users already work, Mira remembers, understands, adapts, and grows with every chat, turning Telegram into an AI execution layer for planning, creating, searching, summarizing, and acting. Its structured memory layer learns from real conversations across personal and group contexts, building shared memory with AI search, insights, and context retrieval so users do not have to repeat preferences, project details, recurring workflows, or communication style every session. Mira can manage tasks, set reminders, draft and send messages, search the web, summarize documents, generate content, and automate multi-step workflows while staying available inside the same chat interface. The AI Content Studio helps users create high-quality content instantly inside Telegram, while the Content Creator Agent can create, edit, and schedule content end to end. -
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Superlinked
Superlinked
Combine semantic relevance and user feedback to reliably retrieve the optimal document chunks in your retrieval augmented generation system. Combine semantic relevance and document freshness in your search system, because more recent results tend to be more accurate. Build a real-time personalized ecommerce product feed with user vectors constructed from SKU embeddings the user interacted with. Discover behavioral clusters of your customers using a vector index in your data warehouse. Describe and load your data, use spaces to construct your indices and run queries - all in-memory within a Python notebook. -
36
TwinMind
TwinMind
TwinMind is a personal AI sidebar that understands meetings and websites to provide real-time answers and assist with writing based on context. It offers features such as unified search across the web, open browser tabs, and past conversations, delivering personalized responses. The AI is context-aware, eliminating the need for lengthy search queries by comprehending the context of user interactions. It enhances user intelligence during conversations with proactive insights and suggestions, and maintains a perfect memory, allowing users to create a diary of their life and retrieve information from their memories. TwinMind processes audio on-device, ensuring that conversation data is stored only on the user's phone, with encrypted and anonymized data for any web queries. The platform offers flexible pricing plans, including a free version with 20 hours per week of transcription.Starting Price: $12 per month -
37
Acontext
MemoDB
Acontext is a context platform for AI agents. It stores multi-modal messages/artifacts, monitors agents' task status, and runs a Store → Observe → Learn → Act loop that identifies successful execution patterns, so autonomous agents can act smarter and succeed more over time. Developer Benefits: Less Tedious Work: Store multi-modal context and artifacts in one place by integrating all context data without configuring Postgres, S3, or Redis, and it only requires a few lines of code. Acontext handles repetitive, time-consuming configuration tasks, so developers don’t have to. Self-Evolving Agents: Similar to Claude Skills, which require predefined rules, Acontext allows agents to automatically learn from past interactions, reducing the need for constant manual updates and tuning. Easy Deployment: Open-source, one-command setup, One-line install. Ultimate Value: Improve agent success rates and reduce running steps, then save costs.Starting Price: Free -
38
Memorae
Memorae
Memorae is an AI-powered memory and productivity service that turns brain overload into a reliable system by unifying reminders, lists, briefings, context, files, and communication channels in one memory layer above the apps people already use. Instead of depending on scattered chats, emails, notes, screenshots, and calendars, users can capture information from WhatsApp, Telegram, email, the app, Chrome, and other channels, then retrieve it later from the same connected memory system. Memorae helps users create reminders, manage lists, organize files, sync multiple calendars, and interact across communication channels using simple text or voice messages. Its Memory Everywhere feature connects everyday inputs, so important details do not disappear inside silos, while long-term memory helps the system remember schedules, preferences, VIPs, rules, and recurring ways of deciding.Starting Price: $5.16 per month -
39
MiMo Code
Xiaomi Technology
MiMo Code is a terminal-native AI coding assistant designed to live inside the developer’s computer, understand the project more deeply over time, and improve as it works. It can read and write code, run commands, manage Git, and keep a persistent project context across sessions through a built-in memory system. Instead of relying on the model to remember on its own, MiMo Code uses project memory, conversation checkpoints, scratch notes, task progress, and SQLite FTS5 full-text search to preserve rules, architecture decisions, session state, and ongoing work. When context nears the limit, it reconstructs the working state from the latest checkpoint, memory, task progress, and recent messages so the agent can continue rather than start from scratch. Multiple agents support different workflows, build for full-permission development, plan for read-only analysis, and compose for specs-driven development. -
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Osaurus
Osaurus
Osaurus is a native AI harness for macOS that lets users run open models entirely on their Mac, connect cloud models when greater capability is needed, and carry shared memory across them. Built in Swift for Apple Silicon, it works fully offline with local models through Ollama, MLX, or LM Studio, keeping conversations, code, files, settings, agents, skills, and provider keys on the device unless the user explicitly chooses a cloud provider. A system-wide chat overlay provides quick access from any app, while separate agents can be created for coding, research, file organization, and other jobs, each with its own prompt, history, and memory. Osaurus distills past conversations into relevant facts, loads packaged skills when tasks require them, and gives agents scoped access to working folders, file search, Git, and other tools. Agents can run code in an isolated sandbox, delegate work to subagents, operate on schedules, respond to folder changes, use voice input, and generate images. -
41
Akka
Akka
Akka is a production-grade runtime and agentic AI platform built to make complex distributed systems reliable, resilient, and governable. The platform supports operational data processing, streaming, real-time analytics, long-running workflows, durable memory, edge coordination, digital twins, model inference, and agent execution. Akka combines actor-based concurrency, clustering, durable in-memory state, event sourcing, streaming, backpressure, and active-active high availability to support mission-critical workloads. Its Agentic AI Platform helps teams specify, generate, test, run, govern, and verify AI systems with agents, tools, orchestrations, integrations, memory, APIs, streaming, guardrails, evaluations, HITL workflows, and audit logging. Akka is designed to provide uniform governance, predictable pricing, cloud freedom, and reliability SLAs for enterprise AI and distributed applications. -
42
Momo
Momo
Momo is an AI-augmented workplace memory platform that automatically builds a centralized, searchable company memory by connecting to a team’s existing productivity and communication apps such as Gmail, GitHub, Notion, and Linear, capturing work context, decisions, ownership, and ongoing work without manual note taking or daily status updates. It continually listens to activity and events across integrated apps to extract structured context and relationships between projects, customers, tasks, and decisions, keeping this live memory up to date so teams can search and visualize progress, dependencies, and historical context in one place. By eliminating the need to repeatedly ask what teammates did or to hunt through threads for decisions buried in conversations, Momo helps remote teams, cross-department collaborators, and distributed workforces reduce friction, accelerate onboarding, and maintain coherent context across workstreams. -
43
Deeplake
Activeloop
Deeplake is a GPU-native database for AI agents that helps teams store, retrieve, and process data where their models already run. Built by Activeloop, it is designed as a memory and data layer for production-grade AI agents, agentic loops, physical AI, and generative media workflows. The platform combines a familiar Postgres-style interface, analytical query performance, multimodal data lake capabilities, and GPU acceleration into one AI-focused data system. Deeplake supports use cases involving text, images, video, sensors, 3D scans, model weights, embeddings, and other complex data types. It helps agents retrieve context faster, reduce data movement, and run large volumes of queries more efficiently than traditional CPU-based database architectures. With SOC 2 Type II certification, VPC deployment, open-source traction, and support for modern AI stacks, Deeplake gives AI teams a scalable foundation for agent memory, retrieval, and multimodal data management.Starting Price: $0 -
44
Bidhive
Bidhive
Create a memory layer to dive deep into your data. Draft new responses faster with Generative AI custom-trained on your company’s approved content library assets and knowledge assets. Analyse and review documents to understand key criteria and support bid/no bid decisions. Create outlines, summaries, and derive new insights. All the elements you need to establish a unified, successful bidding organization, from tender search through to contract award. Get complete oversight of your opportunity pipeline to prepare, prioritize, and manage resources. Improve bid outcomes with an unmatched level of coordination, control, consistency, and compliance. Get a full overview of bid status at any phase or stage to proactively manage risks. Bidhive now talks to over 60 different platforms so you can share data no matter where you need it. Our expert team of integration specialists can assist with getting everything set up and working properly using our custom API. -
45
JinaChat
Jina AI
Experience JinaChat, a pioneering LLM service tailored for pro users. JinaChat ushers in a new era of multimodal chat capabilities, extending beyond text to incorporate images and more. Delight in our offer of free short interactions under 100 tokens. Our API empowers developers to leverage long conversation histories and eliminate redundant prompts to build complex applications. Dive headfirst into the future of LLM services with JinaChat, where conversations are multimodal, long-memory, and affordable. Modern LLM applications often hinge on lengthy prompts or extensive memory, leading to high costs when similar prompts are repeatedly sent to the server with only minor changes. JinaChat's API solves this problem by letting you carry forward previous conversations without resending the entire prompt. This saves you both time and money, making it the perfect tool for developing complex applications like AutoGPT.Starting Price: $9.99 per month -
46
Amelia
SoundHound AI
As the market-leading Digital Employee and Conversational AI solution, Amelia delivers the best elements of human interaction – conversation, expression, emotion and understanding – to user experiences every day, driving deeper connections and greater business value. Powered by Amelia, the Digital Employee Builder enables companies to design custom-made, no-code Conversational AI at scale for a variety of use cases, accelerating deployment speed and time-to-value. Amelia's brain uses episodic memory, process memory, intent recognition and emotional intelligence to respond to complex queries, process transactions and deliver personalized customer service. It's why she's the industry's Most Human AI™. Amelia stores facts, concepts, and the associations between them in her semantic memory. From standard operating procedures (SOPs) to policy documents, she can be trained to apply them to conversations. -
47
Command Code
Command Code
Command Code is a frontier coding agent that lives in the terminal, builds full-stack projects, ships features, fixes bugs, writes tests, and refactors code while continuously learning how each developer works. Powered by the meta neuro-symbolic taste-1 model and continuous reinforcement learning, it treats every accepted suggestion, rejection, and edit as a signal, turning recurring choices, structures, patterns, and tooling preferences into project-level skills and persistent memory. Instead of relying only on generic best practices, it learns code-review habits, style preferences, architectural decisions, package managers, libraries, and small conventions developers rarely document, then applies the relevant taste context in future sessions. Command Code supports interactive CLI work, headless prompts, automated execution, plan mode, background sandboxes, custom agents, checkpoints, and memory across sessions.Starting Price: $1 per month -
48
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 -
49
Dex
ThirdLayer
Joindex’s product Dex turns your browser into a single AI-powered workspace and “second brain” that understands your tasks, context, and workflows across all your tabs and connected apps so you can handle work faster without switching between tools. It connects with popular apps and services, remembers preferences and context, and surfaces relevant suggestions, notes, links, and actions right when you need them, helping with tasks like scheduling meetings, summarizing content, scraping and exporting data, managing emails, and automating repetitive steps directly in your browser. Dex organizes AI-generated notes and todos into retrievable memory, predicts what’s next based on your activity, and works across multiple applications and tabs so you don’t lose context or waste time digging for information, while privacy controls let you manage permissions and data access.Starting Price: Free -
50
Macro
Macro
Macro is an open-source collaborative workspace that brings email, messaging, documents, tasks, calls, AI agents, and CRM together in a single application. The platform creates a shared AI memory that continuously connects information across the workspace, giving users and AI agents complete context for collaboration and decision-making. Macro features a keyboard-first email client with AI-assisted productivity, unified inbox management, and fast search designed to streamline communication. It also includes collaborative documents, integrated team chat, task management, and CRM capabilities that are tightly connected instead of existing as separate tools. Built-in AI agents can summarize conversations, manage tasks, generate content, and provide company-wide knowledge based on shared workspace memory. Macro helps teams replace multiple disconnected workplace applications with a unified, AI-powered collaboration platform.Starting Price: $40/user/month