Alternatives to PlatformPilot
Compare PlatformPilot alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to PlatformPilot in 2026. Compare features, ratings, user reviews, pricing, and more from PlatformPilot competitors and alternatives in order to make an informed decision for your business.
-
1
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. -
2
SIRP
SIRP
SIRP is an AI-native Autonomous SOC platform. Not a SOAR upgrade. A replacement for the architecture that made SOAR necessary in the first place. Where legacy SOAR executes static playbooks, SIRP deploys AI agents that analyze alerts, compute risk, and execute response decisions autonomously, within defined policy boundaries, with full audit coverage. No manual triage. No static playbook logic. No human in the loop for routine Tier-1 cases. The platform learns from every outcome. Detection gets sharper. Response gets faster. The SOC operates at machine speed without surrendering governance or control on decisions that warrant human judgment. Built for enterprise SOC teams and MSSPs that are done waiting for a copilot to tell them what to do. -
3
HQ
Indigo AI
HQ is the shared AI context layer for teams, giving the whole team and every AI tool one workspace to work from, with knowledge, skills, and workflows compounding in one place, and any agent running on top. It works as an operating system for AI workers over Claude Code, Cursor, Codex, ChatGPT, and Claude chat through MCP, so every teammate and every agent can start from the same shared context instead of separate chat histories, scattered files, and siloed workflows. HQ turns one person’s best work into team infrastructure: any prompt or workflow can become a reusable /command, then /hq-sync ships it to the whole team so anyone can run it in one step. Knowledge that usually lives across decisions, docs, playbooks, policies, projects, code, and ideas accumulates in HQ as the team works, creating one source of truth that every agent can search, reuse, and build on. Agents can be deployed into email and Slack, acting on top of the team’s skills and knowledge with full context. -
4
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 -
5
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 -
6
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. -
7
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 -
8
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. -
9
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 -
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
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 -
12
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 -
13
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 -
14
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 -
15
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 -
16
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 -
17
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 -
18
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. -
19
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 -
20
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. -
21
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. -
22
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 -
23
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. -
24
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 -
25
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 -
26
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 -
27
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 -
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
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. -
30
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. -
31
Vokal
Vokal
Vokal is a collaboration space for teammates and AI agents, built so founders and product teams can run agent work where the team can see it, review it, and reuse what matters. It gives human-agent work a shared place to start, move, stay visible, and become reusable context, instead of leaving agent runs, assumptions, and decisions trapped in private sessions across Claude Code, Codex, Cursor, ChatGPT, or other tools. Vokal connects channels, tasks, docs, files, apps, agents, memory, Knowledge Base, identity, access, runtime, and event logs around the work, helping teams keep output aligned, reviewed, controlled, and reusable. Agents can work in shared channels with named owners, roles, instructions, sources, statuses, permission scopes, app grants, memory scope, local project-file grants, and visible activity. Teams can use pre-built roles for engineering, product, growth, support, operations, research, and customer work, or bring their own local Codex, Claude Code, Hermes, etc.Starting Price: $20 per month -
32
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 -
33
HAQQ
HAQQ
HAQQ is a legal AI and practice management platform designed to help lawyers, law firms, legal teams, businesses, governments, and consumers complete legal work faster. The platform supports drafting, legal research, contract review, risk analysis, matter management, billing, CRM, document management, tasks, time tracking, client portals, and mobile access. HAQQ combines chat, eFirm, mobile apps, eBar, client portal, API, MCP, legal sources, firm knowledge, templates, precedents, clause libraries, playbooks, policies, and matter history in one operating system. Its agentic legal system uses model selection, tool routing, sub-agent orchestration, memory, guardrails, deep reasoning, lookahead, rollback, and human-in-the-loop workflows. The platform includes enterprise-grade security with cross-matter isolation, audit trails, role-based access control, anonymization, GDPR, ISO 42001, ISO 27001, and SOC 2 Type II compliance.Starting Price: $0 -
34
Coral
Coral
Coral is an open-source query layer that allows AI agents and developers to access data across APIs, databases, and file systems using SQL. The platform turns connected sources such as GitHub, Slack, Linear, Datadog, Sentry, Stripe, and PagerDuty into readonly tables that can be explored and joined together. Instead of building custom integrations, ETL pipelines, or API wrappers, teams can use Coral to query multiple systems from one runtime. Coral supports CLI and MCP access, making it usable with tools such as Claude Code, Codex, and other agent frameworks. The platform handles authentication, pagination, rate limits, schema mapping, caching, and semantic hints to improve accuracy and reduce cost. Coral helps engineering teams give AI agents safer, faster, and more useful context for production workflows.Starting Price: $249/month -
35
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 -
36
Claude Fable 5
Anthropic
Claude Fable 5 is an advanced AI model from Anthropic designed to assist with software engineering, research, knowledge work, vision tasks, and complex reasoning. Built on the Mythos-class architecture, it delivers significantly improved performance across coding, analysis, and long-context workflows. The model can handle extended autonomous tasks while maintaining focus and consistency over large amounts of information. Claude Fable 5 integrates advanced reasoning, multimodal understanding, and memory capabilities to support professional and enterprise use cases. Anthropic has implemented specialized safeguards that automatically route certain high-risk cybersecurity, biology, chemistry, and model distillation requests to a different model. Claude Fable 5 helps organizations and professionals accelerate complex work while maintaining strong safety and governance controls.Starting Price: $10 per 1 million (input) -
37
Aident AI
Aident AI
No coding. No drag-and-drop frustration. APE(Aident Playbook Editor) lets you write in plain English, test instantly, and get your first automation working in minutes. APE (Aident Playbook Editor) is your AI-powered workflow editor for small teams. Instead of wiring drag-and-drop nodes or hiring technical help, describe your process in plain English. APE’s Editor Agent converts your text into a working Playbook—a reliable workflow that executes across your favorite tools. You can test, debug, and run it anytime. Connect with 250+ tools like Google Sheets, Notion, Slack, and Twitter. Built for non-technical founders, APE makes automation accessible and empowering. 1. Start with a Goal — Describe what you want automated; 2. AI Drafts It — APE generates a ready-to-run workflow; 3. Test & Approve — Preview and refine results in minutes; 4. Run & Scale — Let APE keep your workflows alive and reliable.Starting Price: $12/month -
38
Kiite
Kiite
Move aside, huge documents and buried content. Give your team the best knowledge, at the right moments, without all the digging. Kiite’s AI-enriched Playbooks™ let you remix your favorite resources and hacks with your best company content in a personalized hub that moves as fast as your team does. Toss the fluff and get right to the in-the-moment micro-content your team needs the most. Now you don't have to remember where that PDF or presentation is stored. Search globally across popular repositories, like Google Drive, Salesforce, Microsoft OneDrive, or Dropbox, to quickly find what you need. Create your own workspace and start unlocking your team's best knowledge. Take your selling game up a level with Playbooks™ from the experts ClozeLoop's Playbooks™ for Account Executives is quintessential. Advance your sales career with Playbooks™ from the tech sales career experts Uvaro's Career Advancement Playbook™. -
39
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 -
40
ClearMash
ClearMash
Knowledge items, call scripts, products catalog, tasks and any other information needed by the agent is the heart of any contact center. Agents need to be informed with up-to-date, relevant, and effective information to answer any question or issue by the customer. Optimize your customer interaction with ClearMash’s knowledge administration and get the best out of your agents. Give your agents the best search engine for contact centers. ClearMash’s search can find anything, in ClearMash’s knowledge administration and outside (like file servers, websites, emails and etc.) and do it fast. Allowing your agents to give better answers and improve your customer satisfaction. In real-time agents don’t have time to consult knowledge administration every call. To reduce the knowledge administration you train your agents, but with training, you count on the memory of the agents and this is also not optimal. No need to count on memory and no need to leave the operational systems to search. -
41
Goldfish
Goldfish
Goldfish is a little AI memory that lives on your Mac, giving users one click to answer every message in their tone, with full context, anywhere they type. It works like a tiny companion that remembers what happens across apps, including threads, docs, tabs, and the context of everyday work, so users stop re-explaining the same things every time they need AI help. Press anywhere there is a text field, and Goldfish reads the context already in front of you to help reply, write, summarize, or continue. Users can also chat with full context from the aquarium in the notch, connect it to Claude through local MCP, and use it to identify repetitive workflows over time. Unlike a generic writing assistant, Goldfish already knows what the user is working on, so it does not just write in their tone; it writes with the context they would otherwise have to explain manually. Its memory captures work context as it happens and turns it into searchable local memory.Starting Price: Free -
42
Cuey
Cuey
Cuey helps serious AI users de-risk AI answers without leaving ChatGPT, Claude, Gemini, and other AI tools. It lets users compare answers across multiple models in a single workflow, keep context, and stay inside the AI tools they already use instead of switching tabs. Cuey is designed for people who want to cross-check advice, research, and judgment-heavy tasks before they act, reducing hallucination risk by aggregating multiple AI answers and making model comparison easier. It supports a broad set of AI models across different capability tiers, from lightweight GPT, Claude, Gemini, and Grok variants for everyday prompts and quick drafting to advanced and ultra models for deeper reasoning, long-form quality, complex analysis, and critical writing tasks. Cuey also helps keep memory and prompt workflows portable across AI services, making it easier to reuse context and maintain continuity between tools.Starting Price: $9.99 per month -
43
Claude Sonnet 4.5
Anthropic
Claude Sonnet 4.5 is Anthropic’s latest frontier model, designed to excel in long-horizon coding, agentic workflows, and intensive computer use while maintaining safety and alignment. It achieves state-of-the-art performance on the SWE-bench Verified benchmark (for software engineering) and leads on OSWorld (a computer use benchmark), with the ability to sustain focus over 30 hours on complex, multi-step tasks. The model introduces improvements in tool handling, memory management, and context processing, enabling more sophisticated reasoning, better domain understanding (from finance and law to STEM), and deeper code comprehension. It supports context editing and memory tools to sustain long conversations or multi-agent tasks, and allows code execution and file creation within Claude apps. Sonnet 4.5 is deployed at AI Safety Level 3 (ASL-3), with classifiers protecting against inputs or outputs tied to risky domains, and includes mitigations against prompt injection. -
44
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 -
45
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 -
46
Praction
Praction
Praction is an automated Chief Revenue Officer (CRO) platform designed to optimize revenue growth for B2B companies. By combining data-driven assessments with proven growth playbooks, Praction provides detailed diagnostics and actionable plans to accelerate revenue. The platform offers tailored playbooks for every team and growth stage, continuously monitors risks, and identifies solutions to fix revenue leaks. Praction's 90-day pilot program focuses on optimizing revenue strategy, refining sales processes, enhancing customer retention, and aligning go-to-market operations. This pilot includes access to Praction's automated CRO platform and custom consulting services. Key programs offered by Praction encompass empowering sales through specialized training and systems, reducing churn by engaging customers to increase satisfaction and loyalty, increasing customer lifetime value with tailored pricing and GTM strategies, and creating accountability by training teams on clear metrics.Starting Price: $7,950 per month -
47
ALLMO.ai
ALLMO.ai
ALLMO.ai is an AI Visibility Management platform that helps companies monitor, analyze, and improve how their brand appears in AI generated answers across tools like ChatGPT, Perplexity, Claude, Gemini, and other large language models. The platform tracks relevant prompts, measures share of voice against competitors, analyzes brand mentions and cited sources, and highlights concrete opportunities to improve visibility in AI search. Instead of only showing data, ALLMO.ai turns insights into actionable recommendations and practical GEO playbooks that teams can apply directly. The software is built to be easy to use, so marketing, SEO, content, and growth teams can understand where they stand, what to improve, and which actions to take next without needing a SEO degree.Starting Price: 30€ -
48
Ejentum
Ejentum
Ejentum is a reasoning harness for agentic AI, built as a structured reasoning layer that makes LLM agents more reliable, auditable, and disciplined during long or complex tasks. It works as a tool that an agent can call mid-task, returning the exact cognitive operation matched to the problem in front of it, so the agent can correct reasoning at inference time instead of relying only on static prompts. Ejentum is designed to stop AI agents from drifting, flattering, fabricating, locking into false hypotheses, stopping at shallow answers, or losing important context after several steps. It provides 679 abilities across four cognitive harnesses: reasoning, code, anti-deception, and memory. The reasoning harness channels analytical power across causality, time, space, simulation, abstraction, and metacognition, helping agents avoid surface-level pattern matching.Starting Price: €25 per month -
49
HybridClaw
HybridAI
HybridClaw is an enterprise-grade AI agent platform designed to function as a persistent digital coworker that unifies workflows across communication channels, tools, and execution environments into a single intelligent system. It provides a “shared assistant brain” that operates consistently across Discord, Teams, iMessage, WhatsApp, email, web interfaces, and terminal environments, ensuring that all users interact with the same memory, behavior, and execution logic. It combines persistent workspace memory, semantic recall, and knowledge-graph relationships to maintain context across long-running conversations and tasks, allowing it to remember projects, decisions, and interactions over time. HybridClaw enables end-to-end task execution by securely running tools, commands, and workflows within sandboxed environments, applying guardrails, permission controls, and audit logs to ensure safe and controlled automation.Starting Price: Free -
50
AllyMatter
AllyMatter
AllyMatter is a centralized enterprise knowledge management platform designed to help organizations turn scattered documentation and tribal knowledge into a searchable, governed, and scalable system that supports workflows, compliance, and collaboration across departments. It provides a central knowledge hub where teams can store policies, procedures, SOPs, training materials, playbooks, and other critical documents with advanced search so information is always findable; workflow automation including custom approval flows and notifications so changes move through review and sign-off efficiently; audit trails, version control, and acknowledgment tracking that capture who changed what and when and help with compliance; and role-based access controls and SSO integration so sensitive data stays protected and accessible to the right people only.
