Alternatives to Solid
Compare Solid alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Solid in 2026. Compare features, ratings, user reviews, pricing, and more from Solid competitors and alternatives in order to make an informed decision for your business.
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Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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BAND
BAND.ai
BAND builds enterprise-grade interaction infrastructure for distributed AI agents. Its platform enables real-time, multi-peer collaboration across agents and humans, while providing a runtime control plane that enforces policy, authority boundaries, and visibility across heterogeneous systems. BAND supports developers, engineering teams, and enterprise platform leaders operating multi-agent ecosystems across internal systems, SaaS platforms, and partner environments. -
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Archestra
Archestra
Archestra is an open source, self-hosted AI platform for deploying and governing agents across an organization. It provides agentic chat for non-developers, apps and skills, shared projects, a server-side agent runtime, MCP orchestration, permission-aware RAG, LLM and MCP proxies, security guardrails, and observability in one platform. Users sign in with SSO, and every tool call runs under that person’s own identity rather than a shared service account. Projects keep chats, files, scheduled tasks, and instructions together, while agents run in sandboxed containers and can start from schedules, emails, or webhooks. MCP servers run in the organization’s own Kubernetes environment and move through security-reviewed promotion flows with separate credentials and network policies. Knowledge bases can connect Confluence, Jira, drives, and internal documents while preserving source-system ACLs, so users only retrieve content they are already allowed to access.Starting Price: Free -
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Phinite
Phinite AI
Phinite provides shared infrastructure for building, deploying, and governing AI agents across orchestration, security, observability, lifecycle management, and environment promotion — so engineering teams don't rebuild these layers for every new agent use case. Core capabilities: Orchestration for multi-agent systems (agent-to-agent, nested calls) Deep session-level observability: execution timelines, decision variables, tool calls, latency/cost tracking Private Agent Registry for skill discoverability Eval suite for accuracy/safety benchmarking Dev-to-Production workflow with environment promotion Kubernetes-native deployment, VPC-internal deployability SOC 2 Type 2 complianceStarting Price: $20/month -
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Domino Enterprise AI Platform
Domino Data Lab
Domino is an enterprise AI platform designed to help organizations build, deploy, and scale AI systems that deliver real business outcomes. It provides end-to-end support for the AI lifecycle, from data science experimentation to production deployment and governance. The platform enables teams to access data, tools, and compute resources through a self-service environment with built-in IT controls. Domino supports the development of machine learning models, generative AI applications, and AI agents using preferred tools and frameworks. It also includes governance features such as model tracking, audit trails, and policy enforcement to ensure compliance and transparency. With hybrid and multi-cloud capabilities, organizations can run AI workloads across on-premises and cloud environments. Overall, Domino helps enterprises operationalize AI at scale while maintaining control, security, and efficiency. -
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OpenServ
OpenServ
OpenServ is an applied AI research lab building the infrastructure for autonomous agents. Our next-generation multi-agent orchestration platform combines proprietary AI frameworks and protocols with supreme user simplicity. Automate complex tasks across Web3, DeFAI, and Web2. We’re accelerating the agentic field through numerous academic partnerships, in-house research, and community-focused research initiatives. See the whitepaper detailing the architecture of OpenServ. Seamless developer experience and agent development with our SDK. Receive early access to our platform, white-glove support, and an opportunity to shape the future. -
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Agent Computer
Agent Computer
AgentComputer is a cloud-based infrastructure platform designed specifically for running AI agents in isolated, fully functional virtual environments. It provides “cloud computers” in the form of lightweight Ubuntu-based sandboxes that can be provisioned in under a second, allowing developers to quickly spin up, access, and manage environments through a command-line interface. These environments include persistent storage, meaning any installed tools, files, or configurations remain intact across restarts, enabling continuous and stateful workflows. It is built around an agent-first architecture, where AI agents can directly execute tasks within these environments via SSH, eliminating friction between instruction and execution. It includes an integrated AI harness that supports agents such as Claude, Codex, and other coding assistants, enabling collaborative, multi-agent workflows within the same system.Starting Price: $20 per month -
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CrewAI
CrewAI
CrewAI is a leading multi-agent platform that enables organizations to streamline workflows across various industries by building and deploying automated processes using any Large Language Model (LLM) and cloud platform. It offers a comprehensive suite of tools, including a framework and UI Studio, to facilitate the rapid development of multi-agent automations, catering to both coding professionals and those seeking no-code solutions. The platform supports flexible deployment options, allowing users to move their created 'crews'—teams of AI agents—to production with confidence, utilizing powerful tools for different deployment types and autogenerated user interfaces. CrewAI also provides robust monitoring capabilities, enabling users to track the performance and progress of their AI agents on both simple and complex tasks. Additionally, it offers testing and training tools to continually enhance the efficiency and quality of outcomes produced by these AI agents. -
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Flowise
Flowise AI
Flowise is an open-source platform that enables developers and teams to build AI agents and LLM-powered applications through a visual interface. The platform provides modular building blocks that allow users to create everything from simple chatbot workflows to complex multi-agent systems. With its drag-and-drop design environment, developers can rapidly prototype and deploy AI-powered applications without extensive coding. Flowise supports integrations with more than 100 large language models, embeddings, and vector databases. It also includes features such as human-in-the-loop workflows, observability tools, and execution tracing for monitoring agent behavior. Developers can extend applications through APIs, SDKs, and embedded chat interfaces using TypeScript or Python. By combining visual development tools with scalable infrastructure, Flowise simplifies the process of building and deploying production-ready AI agents.Starting Price: Free -
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Composio
Composio
Composio is a platform that enables AI agents to seamlessly interact with external tools and applications. It provides pre-built integrations with over 1,000 apps, allowing agents to execute tasks across services like Slack, Gmail, GitHub, and more. The platform handles complex processes such as authentication, tool execution, and sandboxed environments automatically. Composio supports dynamic tool selection, ensuring agents use the right tools based on user intent. It also enables secure, parallel execution of workflows in isolated environments. Developers can build agents that move beyond conversation to perform real-world actions. By simplifying integrations and execution, Composio helps turn AI agents into powerful, task-performing systems.Starting Price: $49 per month -
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Molted
Molted.net
Molted is a managed operating environment for autonomous AI agents. It lets teams deploy, host, monitor, recover, and scale OpenClaw-based agents without building their own cloud, DevOps, integration, and recovery stack. Molted provides agent-ready runtimes with persistent workspaces, browser automation, 1,000+ app integrations, dedicated email and voice per agent, monitoring, automatic recovery, and lifecycle management. Agents can use tools, access websites without APIs, communicate through email/voice/SMS, and keep working continuously. It is built for AI agencies, SaaS builders, OpenClaw consultants, and teams running agent fleets for customer-facing or internal workflows. Molted supports multi-agent management, versioned filesystems, restore points, REST API control, and cloud, on-premise, or sovereign deployments. Molted is not generic hosting; it is the run layer for production AI agents. -
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Subconscious
Subconscious
Subconscious is a developer-first platform designed to build, deploy, and scale production-ready AI agents by handling the hardest parts of agent architecture automatically. It provides a complete agent system that manages context, orchestrates tools, and enables long-horizon reasoning, allowing developers to focus on defining goals and capabilities rather than stitching together complex infrastructure. It introduces a unified inference engine composed of a co-designed model and runtime that decomposes complex tasks, generates workflows dynamically, and executes multi-step reasoning without manual context engineering or multi-agent orchestration. Unlike traditional approaches that rely on chaining APIs and frameworks, Subconscious enables agents to take in goals and tools, then autonomously plan, reason, and act with minimal human intervention, effectively creating systems that can “get the job done” on their own.Starting Price: $2 per 1M tokens -
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Daytona
Daytona
Daytona is a cloud-native development runtime that enables developers and AI agents to instantly create, run, and manage isolated sandboxes for any codebase. Each sandbox runs inside a secure microVM with full Linux compatibility, networking, and persistent storage. Daytona provides SDKs in Python and TypeScript, allowing applications to programmatically execute code, run processes, upload files, or spin up environments dynamically. Teams use Daytona to replace complex local setups with reproducible cloud sandboxes that can be started in seconds and accessed through preview URLs, SSH, or APIs. It’s built for automation, observability, and scalability, powering everything from personal development environments to enterprise-grade agent runtimes. -
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Contextually
Contextually
Contextually is an enterprise AI platform designed to help organizations build and deploy production-ready AI agents that can reason over complex, domain-specific data using advanced context engineering. It provides a unified context layer that connects AI models to large volumes of enterprise knowledge, including documents, databases, and multimodal data, enabling agents to deliver accurate, grounded, and relevant outputs. It allows users to define and configure agents quickly through prebuilt templates, natural language prompts, or a visual drag-and-drop interface, supporting both dynamic agents and structured workflows tailored to specific use cases. It includes tools for ingesting and processing massive datasets from multiple sources, transforming unstructured and structured information into retrievable knowledge with intelligent parsing, metadata generation, and continuous updates. -
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HyperLake
CerebrixOS
HyperLake is built for organizations preparing for a world where AI agents become primary users of infrastructure. Today, most enterprise infrastructure was designed for humans, dashboards, applications, and scheduled pipelines. AI agents behave differently. They query data, call tools, trigger workflows, generate artifacts, operate across systems, and need continuous access to governed compute, data, policies, and services. HyperLake provides the command center to deploy, manage, run, secure, and govern that agentic infrastructure. The first product wedge is Agentic Data Cloud Infrastructure: open-stack data, analytics, semantic, workflow, and agent infrastructure deployed inside the customer’s own VPC, private cloud, or on-prem environment. -
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Preloop
Preloop
Preloop is the open source AI agent control plane for agents that take real actions. It combines an MCP firewall for tool access, an AI model gateway for cost, safety, and attribution, policy-as-code with human approvals, runtime session observability, and audit trails in a single self-hostable platform. AI agents can deploy code, change infrastructure, move money, touch production data, and burn model spend in seconds, so Preloop helps teams control what agents can do, how much they spend, and which actions require human approval. It works with OpenClaw, Hermes, Claude Code, Codex CLI, Cursor, Gemini CLI, Windsurf, Cline, OpenCode, and any MCP-compatible agent or managed runtime. Access rules can inspect arguments and context, not just tool names, with CEL expressions for fine-grained conditions. Teams can start with observability, then layer in approvals and deny rules without SDKs or invasive app changes.Starting Price: $290 per month -
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Mistral AI Studio
Mistral AI
Mistral AI Studio is a unified builder-platform that enables organizations and development teams to design, customize, deploy, and manage advanced AI agents, models, and workflows from proof-of-concept through to production. The platform offers reusable blocks, including agents, tools, connectors, guardrails, datasets, workflows, and evaluations, combined with observability and telemetry capabilities so you can track agent performance, trace root causes, and govern production AI operations with visibility. With modules like Agent Runtime to make multi-step AI behaviors repeatable and shareable, AI Registry to catalogue and manage model assets, and Data & Tool Connections for seamless integration with enterprise systems, Studio supports everything from fine-tuning open source models to embedding them in your infrastructure and rolling out enterprise-grade AI solutions.Starting Price: $14.99 per month -
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StateFabric
J Gregory Technology Ltd.
StateFabric a small infrastructure layer for AI agents that need more context than chat history. Once an agent starts using tools, running for longer sessions between restarts, ‘keep the messages in memory’ doesn’t really cut it. You need to know: - what happened? - what state changed? - which tools were called? - what context should go into the next model turn? StateFabric stores an append-only event log for agent runs, then derives working context from it. Today it supports: - Durable sessions and event storage - User/model/tool event timelines - Reconstructed session state from stored events - Compacted model-facing context - A dashboard for inspecting sessions, raw payloads, compaction artefacts, and usage - Google ADK integration via @statefabric/adk - Direct Node/REST usage via @statefabric/client (for custom runtimes)Starting Price: £10/month -
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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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Pushary
Pushary
Pushary sends a push to your phone when your AI agents need you. Claude Code, Codex, Cursor, and other agents pause for approval on risky actions like shell commands, file writes, and deploys. Pushary turns each pause into a notification you approve or deny from your lock screen, so your agents keep working while you are away from your desk. Set permission policies per tool: auto-approve safe actions, require approval for risky ones, and keep a full audit log of every question and answer. Run a whole fleet of agents and track them in one place. Pushary also powers push notifications for e-commerce and SaaS: subscriber capture, campaigns, automation flows, templates, and analytics. Connect any agent through a simple CLI or MCP. Native iOS and Android apps included.Starting Price: $9.99/month -
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Emergence Orchestrator
Emergence
Emergence Orchestrator is an autonomous meta-agent designed to coordinate and manage interactions between AI agents across enterprise systems. It enables multiple autonomous agents to work together seamlessly, handling sophisticated workflows that span modern and legacy software platforms. The Orchestrator empowers enterprises to manage and coordinate multiple autonomous agents at runtime across various domains, facilitating use cases such as supply chain management, quality assurance testing, research analysis, and travel planning. It handles tasks like workflow planning, compliance, data security, and system integrations, freeing teams to focus on strategic priorities. Key features include dynamic workflow planning, optimal task delegation, agent-to-agent communication, an agent registry cataloging various agents, a skills library for task-specific capabilities, and customizable compliance policies. -
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Peta
Peta
Peta is an enterprise-grade control plane for the Model Context Protocol (MCP) that centralizes, secures, governs, and monitors how AI clients and agents access external tools, data, and APIs. It combines a zero-trust MCP gateway, secure vault, managed runtime, policy engine, human-in-the-loop approvals, and full audit logging into a single platform so organizations can enforce fine-grained access control, hide raw credentials, and track every tool call made by AI systems. Peta Core acts as a secure vault and gateway that encrypts credentials, issues short-lived service tokens, validates identity and policies on each request, orchestrates MCP server lifecycle with lazy loading and auto-recovery, and injects credentials at runtime without exposing them to agents. The Peta Console lets teams define who or which agents can access specific MCP tools in specific environments, set approval requirements, manage tokens, and analyze usage and costs.Starting Price: Free -
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Fluq
Fluq
Fluq is an AI agent observability and orchestration platform designed to give teams full visibility and control over how their AI agents operate in real time. It acts as a centralized “single pane of glass” where every agent action, LLM calls, tool usage, file operations, token consumption, and associated costs are tracked and visualized through detailed waterfall traces. By routing all agent requests through a lightweight proxy, Fluq requires minimal setup and works with any LLM provider or agent framework, allowing organizations to integrate it into existing systems without modifying code. It enables teams to inspect each decision an agent makes, drill into execution steps, and understand exactly how outcomes are generated, improving transparency and debuggability. It also includes governance features such as policy enforcement, spend limits, approval gates, and access controls, helping prevent issues like runaway costs, misuse of tools, or inaccurate outputs.Starting Price: $29 per month -
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TinyFish
TinyFish
TinyFish is an enterprise AI platform that builds and operates “enterprise web agents” designed to execute complex workflows directly across the web at massive scale. Instead of relying on APIs or manual processes, these agents interact with websites the way humans do, navigating interfaces, extracting data, and completing multi-step tasks across thousands of platforms simultaneously. It is built to handle the growing complexity of the modern web, where valuable data is often fragmented, hidden behind logins, or constantly changing, making traditional automation unreliable. TinyFish agents are powered by infrastructure that can learn, adapt, and scale, enabling them to maintain accuracy and reliability even as web environments evolve. It is designed around outcome-driven workflows rather than isolated tasks, meaning agents can execute entire processes such as pricing intelligence, inventory tracking, or market monitoring from start to finish.Starting Price: $1.50 per month -
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Sprites
Fly.io
Sprites by Fly.io is a stateful sandbox platform for running arbitrary code in hardware-isolated Linux environments. A Sprite acts like a persistent Linux computer where developers can execute AI agents, user-uploaded binaries, scripts, applications, and other workloads. The platform supports checkpoint and restore, allowing environments to persist and resume instead of starting from scratch each time. Sprites use fast directly attached NVMe storage that continuously syncs to durable external object storage. Developers can create, manage, execute commands, and connect to Sprite consoles through the CLI, REST API, JavaScript, Go, Elixir, and Python tooling. Built for developers and AI infrastructure teams, Sprites gives applications a simple place to safely run code with persistence, sandboxing, usage-based pricing, and scalable execution.Starting Price: $30 per month -
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asqav
asqav
asqav is an AI governance and security platform designed to make AI agents audit-ready by providing real-time monitoring, enforcement, and verifiable proof of every action taken by an agent. It introduces a lightweight SDK that allows developers to integrate governance directly into their agents in just a few lines of code, enabling continuous oversight across the full lifecycle of AI operations. It includes behavioral monitoring to detect issues such as drift, rate limits, and scope violations, along with advanced threat detection that identifies prompt injections, exposure of sensitive data, toxic outputs, and other risks. It enforces policy through configurable “policy gates,” which apply per-agent rules, preflight checks, and dynamic approvals before actions are executed, ensuring that agents operate within defined boundaries. asqav also provides automated incident response capabilities, including the ability to suspend, quarantine, or escalate risky agents.Starting Price: $39 per month -
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InstaVM
InstaVM
InstaVM is a production sandbox and cloud built for AI agents, giving agents instant computers with runtime, storage, networking, secrets, and policy. It goes beyond basic sandboxes by running untrusted code inside hardware-isolated real VMs rather than containers, helping teams give AI agents secure execution environments with full Linux filesystems, networking, package management, RESTful API access, and persistent state. InstaVM supports snapshots, allowing users to fork any sandbox and rewind any run, while persistent volumes keep state beyond each execution. Egress control lets teams allowlist what calls home, secrets injection and Vault help protect sensitive credentials from prompt injections, and public URL deploys can expose any port to the public web. It is built for agent patterns such as code interpreters, deploy agents, deep research agents, AI evaluations, reinforcement learning, computer use, and vibe coding apps.Starting Price: $100 per month -
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Barndoor.ai
Barndoor.ai
Barndoor is a data and access management layer designed to secure how artificial intelligence systems interact with enterprise data and infrastructure. It acts as a centralized control plane that governs AI agents and applications, allowing organizations to define policies, enforce access rules automatically, and maintain full visibility over how AI tools operate across business systems. Instead of relying only on traditional identity-based permissions, Barndoor introduces context-aware governance, enabling administrators to control what actions an AI agent can perform based on factors such as the user operating the agent, the system being accessed, the type of data involved, and the specific task being attempted. It evaluates every AI request in real time and enforces policies before an action is executed, preventing unsafe or unauthorized operations from reaching internal systems or modifying sensitive information.Starting Price: $500 per month -
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Microsoft Scout
Microsoft
Microsoft Scout is an always-on AI agent designed to autonomously manage and coordinate work across Microsoft 365 environments. As Microsoft's first Autopilot agent, it operates with its own identity and permissions, allowing it to take actions on behalf of users while adhering to organizational policies and security controls. The platform integrates with Microsoft Teams, Outlook, OneDrive, SharePoint, calendars, emails, contacts, and other workplace resources to stay connected to daily workflows. Microsoft Scout can proactively schedule meetings, identify potential risks, prepare materials, coordinate tasks, and help users stay on top of upcoming deliverables. Powered by Work IQ, the agent continuously develops contextual understanding of user priorities and work patterns to provide increasingly relevant assistance. Built with enterprise-grade governance, identity management, and compliance protections, Microsoft Scout helps organizations automate coordination. -
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VideoDB
VideoDB
VideoDB is a modern backend for AI agents, giving them the ability to see, understand, and act on video and audio in real time. It sits between raw media streams and agent reasoning systems, turning continuous streams into structured, searchable context with playable evidence. Our unified See->Understand->Act workflow replaces a fragmented stack of FFmpeg, vector DBs, and transcription tools with a single, programmable media layer. Featuring "Indexes-as-code," we allow developers to extract meaning from spoken words and visual scenes with near-zero latency. VideoDB supports Python and Node.js SDKs and integrates seamlessly with Claude, Cursor, and Codex via the Model Context Protocol (MCP). Built on a streaming-first architecture, it ensures your agents observe the world continuously rather than just reading static files. Whether you are building an AI meeting copilot, camera intelligence, or automated media editing, VideoDB provides the perception layer you need.Starting Price: $20/month -
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LangChain
LangChain
LangChain is a powerful, composable framework designed for building, running, and managing applications powered by large language models (LLMs). It offers an array of tools for creating context-aware, reasoning applications, allowing businesses to leverage their own data and APIs to enhance functionality. LangChain’s suite includes LangGraph for orchestrating agent-driven workflows, and LangSmith for agent observability and performance management. Whether you're building prototypes or scaling full applications, LangChain offers the flexibility and tools needed to optimize the LLM lifecycle, with seamless integrations and fault-tolerant scalability. -
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Graft
Graft AI
Graft AI is a platform that makes legacy software usable by AI agents without requiring companies to replace existing systems. The platform turns real user interfaces into stable, governed tools that agents can call reliably. Graft observes workflows across ERPs, mainframes, desktop apps, web portals, virtual desktops, internal tools, files, and exports. It maps screens, inputs, transitions, rules, side effects, and application states to create typed tool contracts with policies, approvals, recovery logic, and conformance tests. Every action is auditable, permission-aware, and verified against the source system so agents can execute work safely and consistently. Built for enterprises with hard-to-replace systems, Graft AI helps organizations connect agent workflows to existing software while keeping data controlled, governed, and traceable. -
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HelpNow Agentic AI Platform
Bespin Global
Bespin Global’s HelpNow Agentic AI Platform is an enterprise-grade AI agent automation and orchestration platform that lets organizations rapidly create, deploy, and manage autonomous AI agents tailored to real business workflows without deep coding, using a visual builder (Agentic Studio) and centralized portal to design single or multi-agent workflows, integrate with existing systems via APIs and connectors, and monitor performance in real time with an Agent Control Tower for governance, policy enforcement, and quality oversight; it supports LLM orchestration, multimodal inputs (text, voice, STT/TTS), and flexible deployment across cloud environments (AWS, GCP, Azure, on-premises) with connectivity to internal data, documents, and business processes so agents can act on context-rich enterprise information. It combines tools for agent lifecycle management, real-time observability, integration with voice and document processing, and enterprise governance. -
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Teradata Enterprise AgentStack
Teradata
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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nebulaONE
Cloudforce
nebulaONE is a secure, private generative AI gateway built on Microsoft Azure that lets organizations harness leading AI models and build custom AI agents without code, all within their own cloud environment. It aggregates top AI models from providers like OpenAI, Anthropic, Meta, and others into a unified interface so users can safely ingest sensitive data, generate organization-aligned content, and automate routine tasks while keeping data fully under institutional control. Designed to replace insecure public AI tools, nebulaONE emphasizes enterprise-grade security, compliance with regulatory standards such as HIPAA, FERPA, and GDPR, and seamless integration with existing systems. It supports custom AI chatbot creation, no-code development of personalized assistants, and rapid prototyping of new generative use cases, helping educational, healthcare, and enterprise teams accelerate innovation, streamline operations, and enhance productivity. -
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Agent Control
Agent Control
Agent Control is the open source control plane for AI agents, built to establish a new standard for governing agent behavior at scale. It solves the problem of scattered, hardcoded checks by giving teams a centralized governance layer with step-level enforcement that can be managed from a single control plane and updated in real time without touching agent code. Developers can make any function governable by adding the control() decorator, turning meaningful decision points inside an agent into independently governed control points with their own policies. When a decorated function executes, Agent Control evaluates the input or output against the active policy and returns a decision: deny, steer, warn, log, or allow. If the decision is denied, the SDK raises a ControlViolationError before the unsafe action can proceed. Policies are decoupled from code, so developers decide where to place control hooks while policy teams decide what those hooks enforce.Starting Price: Free -
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Amazon Bedrock AgentCore
Amazon
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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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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GraphBit
GraphBit
GraphBit is an enterprise-grade agentic AI framework built to run critical AI systems with security, governance, and predictable production performance. It combines a Rust execution core with a Python wrapper to give developers high-performance orchestration with the accessibility of Python, helping teams build reliable multi-agent workflows with minimal CPU and memory usage. GraphBit is designed around the layers that reduce risk, including interfaces, configuration, models, tools, actions, memory, orchestration, and observability. It integrates into existing apps, powers custom AI interfaces, and lets users interact through familiar workflows with controlled actions. Teams can define policies, rules, and guardrails centrally, while GraphBit enforces behavior without changing application code. It supports LLMs and multimodal models from multiple providers, allowing teams to swap models freely without breaking workflows or governance. -
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Nora
Nora
Nora is described as a “deep reasoning agent” built for software development with a special focus on Web3 stacks. The platform supports major smart-contract languages like Solidity, Move, Cairo, and Rust and adapts to their execution models and semantics. It is compiler- and VM-aware by design: it understands bytecode generation, control flow, instruction-level transformations, and custom runtime environments (EVM, WASM, etc.). Its debugging and validation capabilities are context-aware, enabling it to identify subtle bugs, unintended state behaviors, and architectural bottlenecks across complex codebases. Nora also aims to accelerate the path from idea to product by assisting teams with core module development, interface wiring, integration testing, deployment logic, and maintaining architectural integrity, helping reduce context-switching and speed up Web3 productization.Starting Price: $29 per month -
41
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 -
42
Nagent AI
Nagent AI
Nagent AI is an enterprise AI agent platform that helps teams stop building AI tools and deploy agentic applications that execute real business workflows autonomously. Nagent lets anyone, from product managers to customer success teams, create, deploy, and orchestrate AI agents that learn, remember, and act. Its no-code Agent Builder Studio brings models, tools, logic, knowledge, memory, multimodal capabilities, and enterprise-grade safety into one workspace, making it possible to build agents from scratch, customize templates, or ask the AI assistant to help finish parts of the workflow. It includes a proprietary multi-agentic workflow system that orchestrates many agents into one flow, connecting content, research, reporting, and other enterprise processes. Nagent supports 40+ AI models in one platform, allowing users to use one or multiple models without managing separate keys, accounts, or billing.Starting Price: $49 per month -
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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 -
44
VoltusWave
VoltusWave
VoltusWave is an enterprise AI agent workforce platform designed to move beyond isolated automation tools by combining intelligent agents with a full execution layer where they can operate end-to-end business processes. It provides a unified system where AI agents can read documents, make decisions, execute workflows, and escalate exceptions, all with full auditability and human override built in. It is powered by six interconnected engines, including process orchestration, rules enforcement, document generation, integration infrastructure, no-code application building, and a governed AI agent workforce, enabling organizations to run complex operations such as procure-to-pay or enterprise-to-cash cycles with minimal manual intervention. AI agents operate across these layers to handle documents, approvals, reconciliations, compliance checks, and customer interactions, while a rules engine ensures that every action follows predefined logic with version control and traceability. -
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Junction
Junction
Junction Panel is a lightweight control surface for managing AI coding agents from anywhere, designed to keep developers connected to their workflows without being tied to a desktop environment. It enables users to monitor, interact with, and control multiple local AI agents in real time, receiving alerts when an agent needs input and responding instantly from any device, including a phone. Through a unified interface, users can review diffs, tail logs, merge pull requests, and approve execution steps with one-tap actions, allowing development processes to continue seamlessly even when away from a workstation. It includes built-in features such as per-turn cost tracking for token usage, workspace browsing, custom commands, and agent checkpoints that allow rollback to previous states if something goes wrong. It also introduces a structured permission system with five levels of risk classification, ensuring that every agent action is categorized and reviewed appropriately.Starting Price: $10 per month -
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Agent Zero
Agent Zero
Agent Zero is an open source AI agent framework designed to run autonomous AI assistants that can perform complex tasks by interacting directly with a computer system. It provides an environment where AI agents operate with real system access, allowing them to execute commands, write and run code, browse the web, analyze data, and manage workflows as part of real-world automation processes. Instead of functioning as a simple chat interface, Agent Zero runs in its own virtual environment where it can interact with the operating system, install tools, execute scripts, and coordinate tasks across multiple components. It emphasizes transparency and control, allowing developers to view, modify, and customize how the agent behaves, what tools it can access, and how it processes information. Agent Zero uses a modular architecture that allows the agent to dynamically create and use tools while maintaining persistent memory.Starting Price: $2.65 per month -
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Mistral Agents API
Mistral AI
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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Bevel
Bevel
Bevel is a vendor-agnostic, Git-backed control plane for enterprise AI agents, where an organization’s agents, context, skills, tools, permissions, and identities are defined as files the company owns in its own infrastructure and served to any agent runtime over MCP. Context is stored as typed knowledge nodes with provenance for every fact, including where it came from, who last changed it, and when it was verified, then compiled into a graph that can be traversed, updated, and used for dashboards. Skills are written as plain Markdown procedures that process owners can read, review in diffs, and port across runtimes. Tool manifests define available capabilities, while secrets stay in a vault and access rules determine which agents may read specific files or call endpoints. Each agent has its own identity, credentials, and scope so actions remain attributable. -
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Akka
Akka
Akka is a production-grade runtime and agentic AI platform built to make complex distributed systems reliable, resilient, and governable. The platform supports operational data processing, streaming, real-time analytics, long-running workflows, durable memory, edge coordination, digital twins, model inference, and agent execution. Akka combines actor-based concurrency, clustering, durable in-memory state, event sourcing, streaming, backpressure, and active-active high availability to support mission-critical workloads. Its Agentic AI Platform helps teams specify, generate, test, run, govern, and verify AI systems with agents, tools, orchestrations, integrations, memory, APIs, streaming, guardrails, evaluations, HITL workflows, and audit logging. Akka is designed to provide uniform governance, predictable pricing, cloud freedom, and reliability SLAs for enterprise AI and distributed applications. -
50
Turgon
Turgon
Turgon is an AI-native data modernization platform built to complete enterprise transformation projects in weeks by combining specialized AI agents with human experts. Its agentic architecture accelerates migration from end-of-life systems by mapping, cleaning, and restructuring data in flight while continuously building and evolving a data ontology. It transforms fragmented structured and unstructured information into decision-grade assets, with agents enforcing data integrity, master data management, lineage, auditability, and compliance policies. AI agents can scan schemas, documents, logs, transcripts, data flows, and existing systems to construct a complete map of an enterprise environment, identify gaps, and generate production-ready specifications without lengthy discovery workshops. Specialized agents handle orchestration, Snowflake pipelines, production-grade integration code, semantic modeling, legacy modernization, QA, and monitoring.