Alternatives to Letta

Compare Letta alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Letta in 2026. Compare features, ratings, user reviews, pricing, and more from Letta competitors and alternatives in order to make an informed decision for your business.

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    Cognigy.AI

    Cognigy.AI

    NiCE Cognigy

    NiCE Cognigy delivers AI that works – fast, human, and built for real-world scale. As part of NiCE, a global leader in customer experience technology, we combine Generative and Conversational AI with orchestration, tools, and enterprise integrations to power Agentic AI. The result? Smarter automation, better service, and instant resolution across every channel. NiCE Cognigy’s AI Agents Supercharge Your Customer Service -Industry-specific pre-trained AI Agents -Multilingual call and chat support (100+ languages) -Seamless integration with existing enterprise systems -Leverages memory and context for hyper-personalized interactions -Absorbs enterprise knowledge to accurately answer any customer query -Real-time assistance and actionable service insights for human agents Business Impact for our Customers: -30% CSAT improvement -70% AHT reduction -99.5% Faster response time -99% Routing accuracy
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    Mem0

    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
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    Cognee

    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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    Agno

    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
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    VoltAgent

    VoltAgent

    VoltAgent

    VoltAgent is an open source TypeScript AI agent framework that enables developers to build, customize, and orchestrate AI agents with full control, speed, and a great developer experience. It provides a complete toolkit for enterprise-level AI agents, allowing the design of production-ready agents with unified APIs, tools, and memory. VoltAgent supports tool calling, enabling agents to invoke functions, interact with systems, and perform actions. It offers a unified API to seamlessly switch between different AI providers with a simple code update. It includes dynamic prompting to experiment, fine-tune, and iterate AI prompts in an integrated environment. Persistent memory allows agents to store and recall interactions, enhancing their intelligence and context. VoltAgent facilitates intelligent coordination through supervisor agent orchestration, building powerful multi-agent systems with a central supervisor agent that coordinates specialized agents.
    Starting Price: Free
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    AgentOps

    AgentOps

    AgentOps

    Industry-leading developer platform to test and debug AI agents. We built the tools so you don't have to. Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. Track, save, and monitor every token your agent sees. Manage and visualize agent spending with up-to-date price monitoring. Fine-tune specialized LLMs up to 25x cheaper on saved completions. Build your next agent with evals, observability, and replays. With just two lines of code, you can free yourself from the chains of the terminal and instead visualize your agents’ behavior in your AgentOps dashboard. After setting up AgentOps, each execution of your program is recorded as a session and the data is automatically recorded for you.
    Starting Price: $40 per month
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    Dynamiq

    Dynamiq

    Dynamiq

    Dynamiq is a platform built for engineers and data scientists to build, deploy, test, monitor and fine-tune Large Language Models for any use case the enterprise wants to tackle. Key features: 🛠️ Workflows: Build GenAI workflows in a low-code interface to automate tasks at scale 🧠 Knowledge & RAG: Create custom RAG knowledge bases and deploy vector DBs in minutes 🤖 Agents Ops: Create custom LLM agents to solve complex task and connect them to your internal APIs 📈 Observability: Log all interactions, use large-scale LLM quality evaluations 🦺 Guardrails: Precise and reliable LLM outputs with pre-built validators, detection of sensitive content, and data leak prevention 📻 Fine-tuning: Fine-tune proprietary LLM models to make them your own
    Starting Price: $125/month
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    Mastra AI

    Mastra AI

    Mastra AI

    Mastra is a powerful TypeScript framework for building intelligent AI agents that can execute tasks, access knowledge bases, and maintain memory persistently within workflows. This framework simplifies the process of creating and deploying AI-powered agents by leveraging TypeScript’s capabilities to streamline development. With features like customizable agent instructions, memory, and task orchestration, Mastra provides developers with the tools to build and scale AI agents for various applications, from personal assistants to specialized domain experts.
    Starting Price: Free
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    Origon

    Origon

    Origon

    Origon is a full-stack AI agent development and operations platform engineered as a unified “Agentic Operating System” that supports the entire lifecycle of autonomous AI systems from design to deployment and observability. It offers an intuitive Studio for visual, drag-and-drop agent creation and configuration, Sessions for real-time observation, behavior tracing, and debugging, and Insights dashboards for performance analytics, reliability tracking, and outcome measurement in one place. Origon runs natively on dedicated infrastructure optimized for low-latency performance and security, avoiding dependency on external cloud APIs, and includes a built-in knowledge engine that connects agents to contextual memory and domain data so responses stay grounded and consistent. It supports hundreds of connectors and APIs, including chat, voice, WhatsApp, SMS, email, and telephony, and lets agents execute code and interact with real systems with a single click.
    Starting Price: $200 per month
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    EverMemOS

    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
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    BotDojo

    BotDojo

    BotDojo

    BotDojo is an enterprise-grade AI enablement platform that empowers organizations to design, deploy, monitor, and scale intelligent agents across chat, voice, email, and web channels using a low-code visual workflow builder, while integrating deeply with enterprise data sources and systems. It provides over 100 ready-made templates to accelerate common use-cases (such as support automation, knowledge search, sales insights, and internal ops), supports branching logic, memory, tool orchestration (code, RPA, web browse), and connects to CRMs, ticketing systems, and databases. BotDojo also delivers human-feedback loops and continuous agent learning by enabling employees to coach agents via feedback queues, codifying corrections into memory and prompts, and evaluating performance through robust observability (audit trails, metrics such as deflection, first-contact resolution, and cost per interaction).
    Starting Price: $89 per month
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    LangMem

    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.
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    Cisco AI Canvas
    The Agentic Era marks a transformative shift from traditional application-centric computing to a new frontier defined by agentic AI, autonomous, context-aware systems capable of acting, learning, and collaborating within complex, dynamic environments. These intelligent agents don’t just respond to commands; they perform complete tasks, retain memory and context via large language models tailored for specific domains, and can scale across industries into the tens of millions. This evolution brings the need for a new operational mindset, AgenticOps, and a reimagined management interface built around three guiding principles, keeping humans thoughtfully in the loop to provide creativity and judgment, enabling agents to operate across siloed systems with cross-domain context, and deploying purpose-built models fine-tuned for their distinct tasks. Cisco brings this to life through AI Canvas, the industry’s first generative, shared workspace driven by a multi-data, multi-agent architecture.
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    Membase

    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.
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    AgentFlow

    AgentFlow

    Multimodal

    AgentFlow is an agentic AI platform that automates workflows for finance and insurance companies. The platform includes modular AI agents, such as Document AI, Decision AI, and Report AI, each specializing in different stages of regulated workflows: triage, diligence, decisioning, and reporting. AgentFlow orchestrates multiple AI agents with human supervisors and third-party systems, enabling deep transformation of how work gets done. The platform features self-learning capabilities that allow AI agents to improve over time based on subject matter experts' feedback and provides transparency through explainability features that help users understand the reasoning behind AI-driven decisions. Every action and output is fully auditable, ensuring compliance with the strict standards of regulated industries. Its main mission is to codify tacit internal knowledge in order to reliably augment high-leverage workflows and preserve the know-how across generations of talent.
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    ByteRover

    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
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    Teradata Enterprise AgentStack
    Teradata Enterprise AgentStack is an integrated platform for building, deploying, and governing enterprise-grade autonomous AI agents that connect to trusted data and analytics, helping organizations move from experimentation to production-ready agentic AI with enterprise-level control. It unifies capabilities to support the full agent lifecycle; AgentBuilder accelerates the creation of intelligent agents using no-code and pro-code tools that integrate with Teradata Vantage and open-source frameworks; the Enterprise MCP delivers secure, context-rich access to governed enterprise data and curated prompts for agent intelligence; AgentEngine provides scalable execution of agents with consistent memory and reliability across hybrid environments; and AgentOps centralizes monitoring, governance, compliance, auditability, and policy enforcement so agents operate within defined guardrails.
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    OpenAI Frontier
    OpenAI Frontier is a new enterprise AI agent platform that helps businesses build, deploy, manage, and orchestrate fleets of AI agents that can perform real work inside existing systems, workflows, and data environments. It provides a unified framework where organizations can integrate AI agents, whether created by OpenAI or third parties, connect them with internal tools like CRM, data warehouses, ticketing systems, and other enterprise applications, and give them shared context, permissions, memory, and oversight so they can act reliably on business-relevant tasks. Frontier’s goal is to move AI agents from isolated pilots into production by providing features like shared business context, governance controls, onboarding workflows, observability, and secure access boundaries while allowing companies to centralize and scale intelligent automation in a way similar to how HR systems manage human work.
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    Strands Agents

    Strands Agents

    Strands Agents

    Strands Agents is an open-source framework designed to help developers build controllable and flexible AI agents using Python and TypeScript. It enables users to create agents by defining tools as simple functions, eliminating the need for complex workflows or orchestration pipelines. The SDK works with any model and cloud provider, giving developers full freedom in how they deploy and scale their agents. It introduces a streamlined agent loop where the model handles reasoning while developers maintain control through code. Features like steering hooks allow developers to validate and guide agent behavior before and after actions are taken. The platform also includes built-in capabilities such as memory management, observability, and evaluation tools. Overall, Strands Agents SDK simplifies agent development while improving reliability, control, and performance.
    Starting Price: Free
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    Lux

    Lux

    OpenAGI Foundation

    Lux is a powerful computer-use AI platform that enables agents to operate software just like a human user—clicking, typing, navigating, and completing tasks across any interface. It offers three execution modes—Tasker, Actor, and Thinker—giving developers the ability to choose between step-by-step precision, near-instant task execution, or long-form reasoning for complex workflows. Lux can autonomously perform actions such as crawling Amazon data, running automated QA tests, or extracting insights from Nasdaq’s insider activity pages. The platform makes it possible to prototype and deploy real computer-use agents in as little as 20 minutes using developer-friendly SDKs and templates. Its agents are built to understand vague goals, execute long-running operations, and interact naturally with human-facing software instead of relying solely on APIs. Lux represents a new paradigm where AI goes beyond reasoning and content generation to directly operate computers at scale.
    Starting Price: Free
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    Langflow

    Langflow

    Langflow

    Langflow is a low-code AI builder designed to create agentic and retrieval-augmented generation applications. It offers a visual interface that allows developers to construct complex AI workflows through drag-and-drop components, facilitating rapid experimentation and prototyping. The platform is Python-based and agnostic to any model, API, or database, enabling seamless integration with various tools and stacks. Langflow supports the development of intelligent chatbots, document analysis systems, and multi-agent applications. It provides features such as dynamic input variables, fine-tuning capabilities, and the ability to create custom components. Additionally, Langflow integrates with numerous services, including Cohere, Bing, Anthropic, HuggingFace, OpenAI, and Pinecone, among others. Developers can utilize pre-built components or code their own, enhancing flexibility in AI application development. The platform also offers a free cloud service for quick deployment and test
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    Phidata

    Phidata

    Phidata

    Phidata is an open source platform for building, deploying, and monitoring AI agents. It enables users to create domain-specific agents with memory, knowledge, and external tools, enhancing AI capabilities for various tasks. The platform supports a range of large language models and integrates seamlessly with different databases, vector stores, and APIs. Phidata offers pre-configured templates to accelerate development and deployment, allowing users to quickly go from building agents to shipping them into production. It includes features like real-time monitoring, agent evaluations, and performance optimization tools, ensuring the reliability and scalability of AI solutions. Phidata also allows developers to bring their own cloud infrastructure, offering flexibility for custom setups. The platform provides robust support for enterprises, including security features, agent guardrails, and automated DevOps for smoother deployment processes.
    Starting Price: Free
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    Memories.ai

    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
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    MemMachine

    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
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    Claude Managed Agents
    Claude Managed Agents is a pre-built, configurable agent system from Anthropic designed to run long-running, asynchronous tasks on managed infrastructure without requiring developers to build their own agent loops. It acts as a complete “agent harness,” allowing developers to define goals while the system handles execution, orchestration, and state management behind the scenes. Unlike direct model prompting, which requires step-by-step interaction, Managed Agents are designed for tasks that unfold over time, such as research, automation, or multi-step workflows, where the agent can continue working independently after being started. It supports advanced capabilities such as multi-agent orchestration, where a primary agent can coordinate specialized sub-agents that operate in parallel with isolated contexts, improving both speed and output quality.
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    Gobii

    Gobii

    Gobii

    Gobii is a cloud-hosted platform that enables you to spin up fully managed browser-automation agents via API, allowing tasks like web-based research, form-filling, data extraction, and multi-step workflows to be automated at scale. These agents operate like “always-on employees” that can browse websites, even those without APIs, navigate dynamic content, handle JavaScript, and even rotate proxies automatically. Users can create agents, assign them prompts or tasks, and retrieve structured JSON outputs or live previews of the agent’s browser actions. Gobii supports synchronous and asynchronous task execution, secret handling for things like login credentials, schema-enforced output validation, and integrates with popular programming languages (Python, Node.js) for seamless implementation. The platform emphasises scalability (hundreds of tasks in parallel), enterprise-grade security (audit logs, proxies, task management), and a simple developer experience.
    Starting Price: $30 per month
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    Mindset AI

    Mindset AI

    Mindset AI

    Mindset Al's agent talks to users, determine exactly what they're looking for, and serves up easy-to-digest slices of content. Mindset Al's agent instantly delivers accurate, personalized, specific answers directly from your content library. When users ask a question, the Al agent will engage in conversation to determine exactly what they're looking for, so they'll always get the best-fit answer. Capabilities allow our AI to interact like a human coach, offering different responses based on user's needs and preferences. Mindset automatically updates to keep your knowledge in sync. Choose which parts of your knowledge base Mindset can access. Fine-tune your agent to fit exactly what you need and give it access to any LLM. Mindset connects to all your workplace applications. See how employees are engaging with your content. Track agent bias, monitor performance, and run tests at scale before giving your team access.
    Starting Price: $652.40 per month
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    Second Me

    Second Me

    Second Me

    ​Second Me is the first open-source AI identity system that delivers 100% private, deeply personalized AI agents built specifically to represent your authentic self. It doesn't just learn your preferences, it comprehends your unique thinking patterns, represents you across different contexts, forms collaborative networks with other Second Mes, and creates new value in the emerging agent economy. Second Me features Hierarchical Memory Modeling (HMM), a three-layer structure that enables your AI self to rapidly recognize patterns, adapt, and evolve alongside you. Its Personalized Alignment Architecture (Me-alignment) transforms your scattered data into deep personalized understanding, outperforming leading retrieval-augmented generation models by 37% in user understanding. Operating with 100% privacy, Second Me can run locally, ensuring you retain complete control over your personal data, sharing it only with your explicit permission.
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    Amazon Bedrock AgentCore
    Amazon Bedrock AgentCore enables you to deploy and operate highly capable AI agents securely at scale, offering infrastructure purpose‑built for dynamic agent workloads, powerful tools to enhance agents, and essential controls for real‑world deployment. It works with any framework and any foundation model in or outside of Amazon Bedrock, eliminating the undifferentiated heavy lifting of specialized infrastructure. AgentCore provides complete session isolation and industry‑leading support for long‑running workloads up to eight hours, with native integration to existing identity providers for seamless authentication and permission delegation. A gateway transforms APIs into agent‑ready tools with minimal code, and built‑in memory maintains context across interactions. Agents gain a secure browser runtime for complex web‑based workflows and a sandboxed code interpreter for tasks like generating visualizations.
    Starting Price: $0.0895 per vCPU-hour
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    Hyperspell

    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.
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    Vivgrid

    Vivgrid

    Vivgrid

    Vivgrid is a development platform for AI agents that emphasizes observability, debugging, safety, and global deployment infrastructure. It gives you full visibility into agent behavior, logging prompts, memory fetches, tool usage, and reasoning chains, letting developers trace where things break or deviate. You can test, evaluate, and enforce safety policies (like refusal rules or filters), and incorporate human-in-the-loop checks before going live. Vivgrid supports the orchestration of multi-agent systems with stateful memory, routing tasks dynamically across agent workflows. On the deployment side, it operates a globally distributed inference network to ensure low-latency (sub-50 ms) execution and exposes metrics like latency, cost, and usage in real time. It aims to simplify shipping resilient AI systems by combining debugging, evaluation, safety, and deployment into one stack, so you're not stitching together observability, infrastructure, and orchestration.
    Starting Price: $25 per month
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    OpenAI Agents SDK
    ​The OpenAI Agents SDK enables you to build agentic AI apps in a lightweight, easy-to-use package with very few abstractions. It's a production-ready upgrade of our previous experimentation for agents, Swarm. The Agents SDK has a very small set of primitives, agents, which are LLMs equipped with instructions and tools; handoffs, which allow agents to delegate to other agents for specific tasks; and guardrails, which enable the inputs to agents to be validated. In combination with Python, these primitives are powerful enough to express complex relationships between tools and agents, and allow you to build real-world applications without a steep learning curve. In addition, the SDK comes with built-in tracing that lets you visualize and debug your agentic flows, evaluate them, and even fine-tune models for your application.
    Starting Price: Free
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    Claude Sonnet 4.5
    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.
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    Koog

    Koog

    JetBrains

    Koog is a Kotlin‑based framework for building and running AI agents entirely in idiomatic Kotlin, supporting both single‑run agents that process individual inputs and complex workflow agents with custom strategies and configurations. It features pure Kotlin implementation, seamless Model Control Protocol (MCP) integration for enhanced model management, vector embeddings for semantic search, and a flexible system for creating and extending tools that access external systems and APIs. Ready‑to‑use components address common AI engineering challenges, while intelligent history compression optimizes token usage and preserves context. A powerful streaming API enables real‑time response processing and parallel tool calls. Persistent memory allows agents to retain knowledge across sessions and between agents, and comprehensive tracing facilities provide detailed debugging and monitoring.
    Starting Price: Free
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    Microsoft Foundry Agent Service
    Microsoft Foundry Agent Service is a secure, enterprise-ready platform for designing, deploying, and orchestrating AI agents at scale. It gives teams a streamlined interface and toolset to automate complex workflows using multi-agent systems. Developers can build with hosted agents, custom code, or agent frameworks while taking advantage of Azure’s reliability, scalability, and integrated observability. Built-in tools, enterprise connectors, and Model Context Protocol support make it easy for agents to interact with business systems and organizational data. Security, access governance, and compliance are embedded throughout, allowing companies to maintain full control while deploying intelligent automation across critical processes. With one-click deployment to Microsoft 365 experiences, Foundry Agent Service accelerates how organizations operationalize AI in everyday work.
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    Papr

    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
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    HappyRobot

    HappyRobot

    HappyRobot

    HappyRobot is an AI-native operating system designed to power autonomous operations by orchestrating customizable “AI workers” that understand your business, make intelligent decisions, and act in real time. Built to streamline enterprise workflows, especially in logistics, supply chain, retail, and services, it lets you create AI agents that can speak, type, reason, negotiate, schedule, process documents, browse systems, and escalate when needed. These workers execute tasks across voice calls, emails, messages, and other channels, with advanced reasoning powered by large language models connected to your tools and workflows via APIs, webhooks, or browser agents. You manage this AI workforce from a centralized “control tower,” where you can deploy, monitor, and iterate workflows in natural language or through integrated UIs, gaining visibility into each task and decision.
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    Agent Builder
    Agent Builder is part of OpenAI’s tooling for constructing agentic applications, systems that use large language models to perform multi-step tasks autonomously, with governance, tool integration, memory, orchestration, and observability baked in. The platform offers a composable set of primitives—models, tools, memory/state, guardrails, and workflow orchestration- that developers assemble into agents capable of deciding when to call a tool, when to act, and when to halt and hand off control. OpenAI provides a new Responses API that combines chat capabilities with built-in tool use, along with an Agents SDK (Python, JS/TS) that abstracts the control loop, supports guardrail enforcement (validations on inputs/outputs), handoffs between agents, session management, and tracing of agent executions. Agents can be augmented with built-in tools like web search, file search, or computer use, or custom function-calling tools.
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    Backboard

    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
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    ServiceNow AI Agents
    ServiceNow's AI Agents are autonomous systems embedded within the Now Platform, designed to perform repetitive tasks traditionally handled by humans. These agents interact with their environment to collect data, make decisions, and execute tasks, enhancing efficiency over time. Leveraging domain-specific large language models and a robust reasoning engine, they possess a deep understanding of business contexts, enabling continuous improvement in outcomes. Operating natively across workflows and data systems, AI Agents facilitate end-to-end automation, boosting team productivity by orchestrating workflows, integrations, and actions throughout the enterprise. Organizations can deploy prebuilt AI agents or develop custom agents tailored to specific needs, all functioning seamlessly on the Now Platform. This integration allows employees to focus on more strategic initiatives by automating routine tasks.
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    SuperAGI SuperCoder
    SuperAGI SuperCoder is an open-source autonomous system that combines AI-native dev platform & AI agents to enable fully autonomous software development starting with python language & frameworks SuperCoder 2.0 leverages LLMs & Large Action Model (LAM) fine-tuned for python code generation leading to one shot or few shot python functional coding with significantly higher accuracy across SWE-bench & Codebench As an autonomous system, SuperCoder 2.0 combines software guardrails specific to development framework starting with Flask & Django with SuperAGI’s Generally Intelligent Developer Agents to deliver complex real world software systems SuperCoder 2.0 deeply integrates with existing developer stack such as Jira, Github or Gitlab, Jenkins, CSPs and QA solutions such as BrowserStack /Selenium Clouds to ensure a seamless software development experience
    Starting Price: Free
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    Adobe Experience Platform Agent Orchestrator
    ​Adobe Experience Platform Agent Orchestrator powers AI agents to accelerate customer experience orchestration. These purpose-built Experience Platform Agents, on their own, or in conjunction with third-party agents—amplify your teams' capacity to deliver personalization at scale. They can also be customized, letting your developers extend customer experience capabilities to meet the needs of your organization. Empower customer experience teams, including marketers, data analysts, and IT, with intelligent agents that boost productivity, provide insights for improved decision-making, and help deliver on key business objectives. Help web teams optimize speed, site engagement, traffic, and security at scale with the Site Optimization Agent. Power on-brand content creation across the organization with the Content Production Agent.
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    Complete

    Complete

    Complete

    Complete is a collaborative AI workspace that enables teams and AI agents to work side by side in a unified environment designed to execute real workflows from planning to delivery. It centralizes conversations, files, and outputs into a single source of truth so teams can maintain shared context while agents perform tasks such as debugging, documenting, testing code, or generating business deliverables. It introduces structured execution threads that allow agents to run outcome-driven tasks while teams monitor progress and iterate on real outputs. Complete supports running multiple AI models in parallel, enabling specialized agents for coding, testing, and reasoning to operate within the same workflow. It integrates with project management and development tools and can bring AI directly into the IDE to accelerate coding and collaboration.
    Starting Price: $25 per month
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    Calljmp

    Calljmp

    Calljmp

    Calljmp is a developer-first AI agent runtime designed to build, run, and scale long-running stateful workflows written in TypeScript. While many modern tools like Mastra AI provide rich frameworks to define agents and workflows, Calljmp focuses on actually running them reliably in production. Calljmp combines agent logic, durable execution, human-in-the-loop pause/resume, retries with idempotency, and built-in observability into a unified execution environment. Developers implement agents as code, and the runtime guarantees reliable execution, state persistence, and operational visibility without gluing together custom queues, databases, and monitoring stacks. Calljmp is ideal for engineering teams, product developers, and backend architects who want to embed intelligent agents into product systems while offloading execution complexity to a purpose-built runtime.
    Starting Price: Free
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    LlamaIndex

    LlamaIndex

    LlamaIndex

    LlamaIndex is a “data framework” to help you build LLM apps. Connect semi-structured data from API's like Slack, Salesforce, Notion, etc. LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models. LlamaIndex provides the key tools to augment your LLM applications with data. Connect your existing data sources and data formats (API's, PDF's, documents, SQL, etc.) to use with a large language model application. Store and index your data for different use cases. Integrate with downstream vector store and database providers. LlamaIndex provides a query interface that accepts any input prompt over your data and returns a knowledge-augmented response. Connect unstructured sources such as documents, raw text files, PDF's, videos, images, etc. Easily integrate structured data sources from Excel, SQL, etc. Provides ways to structure your data (indices, graphs) so that this data can be easily used with LLMs.
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    NVIDIA Agent Toolkit
    NVIDIA Agent Toolkit is a solution stack designed to build, deploy, and scale autonomous AI agents that can reason, plan, and execute complex tasks across enterprise systems. Unlike traditional generative AI, which responds to single prompts, agentic AI uses sophisticated reasoning and iterative planning to solve multi-step problems independently, enabling systems to analyze data, develop strategies, and complete workflows without continuous human input. It integrates multiple components of the NVIDIA AI ecosystem, including pretrained models, microservices, and development frameworks, allowing organizations to create context-aware AI agents that operate using their own data. These agents can ingest large volumes of structured and unstructured data from enterprise systems, interpret context, and coordinate actions across applications to automate processes such as customer service, software development, analytics, and operational workflows.
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    Amazon Bedrock
    Amazon Bedrock is a fully managed service that simplifies building and scaling generative AI applications by providing access to a variety of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon itself. Through a single API, developers can experiment with these models, customize them using techniques like fine-tuning and Retrieval Augmented Generation (RAG), and create agents that interact with enterprise systems and data sources. As a serverless platform, Amazon Bedrock eliminates the need for infrastructure management, allowing seamless integration of generative AI capabilities into applications with a focus on security, privacy, and responsible AI practices.
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    Accenture AI Refinery
    Accenture's AI Refinery is a comprehensive platform designed to help organizations rapidly build and deploy AI agents to enhance their workforce and address industry-specific challenges. The platform offers a collection of industry agent solutions, each codified with business workflows and industry expertise, enabling companies to customize these agents with their own data. This approach reduces the time to build and derive value from AI agents from months or weeks to days. AI Refinery integrates digital twins, robotics, and domain-specific models to optimize manufacturing, logistics, and quality through advanced AI, simulations, and collaboration in Omniverse, enabling autonomy, efficiency, and cost reduction across operations and engineering processes. The platform is built with NVIDIA AI Enterprise software, including NVIDIA NeMo, NVIDIA NIM microservices, and NVIDIA AI Blueprints, such as video search, summarization, and digital human.
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    Mistral Agents API
    Mistral AI has introduced its Agents API, a significant advancement aimed at enhancing the capabilities of AI by addressing the limitations of traditional language models in performing actions and maintaining context. This new API integrates Mistral's powerful language models with several key features, built-in connectors for code execution, web search, image generation, and Model Context Protocol (MCP) tools; persistent memory across conversations; and agentic orchestration capabilities. The Agents API complements Mistral's Chat Completion API by providing a dedicated framework that simplifies the implementation of agentic use cases, serving as the backbone of enterprise-grade agentic platforms. It enables developers to build AI agents capable of handling complex tasks, maintaining context, and coordinating multiple actions, thereby making AI more practical and impactful for enterprises.
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    LangGraph

    LangGraph

    LangChain

    Gain precision and control with LangGraph to build agents that reliably handle complex tasks. Build and scale agentic applications with LangGraph Platform. LangGraph's flexible framework supports diverse control flows – single agent, multi-agent, hierarchical, sequential – and robustly handles realistic, complex scenarios. Ensure reliability with easy-to-add moderation and quality loops that prevent agents from veering off course. Use LangGraph Platform to templatize your cognitive architecture so that tools, prompts, and models are easily configurable with LangGraph Platform Assistants. With built-in statefulness, LangGraph agents seamlessly collaborate with humans by writing drafts for review and awaiting approval before acting. Easily inspect the agent’s actions and "time-travel" to roll back and take a different action to correct course.
    Starting Price: Free