Alternatives to Bevel
Compare Bevel alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Bevel in 2026. Compare features, ratings, user reviews, pricing, and more from Bevel 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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eve
Vercel
Eve is the framework for building agents, like Next.js for web apps, but for agents. It uses Markdown for instructions and skills, TypeScript for tools, and durable execution by default. An agent is a directory that defines instructions and skills in Markdown, tools in TypeScript, and then deploys. Eve compiles the directory, wires up durable workflows, and connects channels, giving developers a structured way to build production agents without gluing together point solutions. An instructions.md file can be a complete agent, while agent.ts lets teams choose a model or configure the runtime. Reusable skills are Markdown playbooks loaded when relevant, so the agent gets focused guidance without carrying everything in every prompt. Tools are added as TypeScript files, with the filename becoming the tool name, and no registration is required. Every agent includes an isolated sandbox and file tools, with support for custom sandbox setup. -
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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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Notenic
Notenic
Notenic is a runtime orchestration and governance platform designed to control and secure autonomous AI agents (“digital labor”) in real time, particularly in environments where failure carries regulatory, legal, or operational consequences. It operates as an infrastructure layer that sits directly in the execution path of AI systems, enforcing deterministic governance before any action reaches systems of record, rather than relying on post-output filters or prompt-level controls. It introduces a zero-trust runtime architecture built on core principles such as zero-persistence (no data retained after each session), execution-path control (policy enforcement at the moment of action), and independence from model context, ensuring that adversarial inputs cannot override governed behavior. Notenic provides a unified control plane that includes agent workforce management (treating AI agents as operational units with defined roles and supervision). -
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scribe
scribe
scribe is a self-hosted knowledge base written automatically by your tools. It reads Git history, Claude Code and Codex sessions, self-sent URLs, and drop files, then turns that work into a curated, cross-project wiki of plain Markdown stored in Git. Instead of making developers maintain a second brain or rebuild context whenever an agent session starts from zero, scribe captures decisions, fixes, evaluations, and the reasoning behind them so agents can query that memory before they act. Its pipeline runs on cron: it discovers projects, filters low-value noise with FTS5 before invoking an LLM, extracts grounded facts through bounded and two-pass workflows, and compiles them into entity-first pages with YAML frontmatter, wikilinks, backlinks, retrieval context, and typed relationships such as supersedes, contradicts, derived_from, specializes, and extends. -
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Vokal
Vokal
Vokal is a collaboration space for teammates and AI agents, built so founders and product teams can run agent work where the team can see it, review it, and reuse what matters. It gives human-agent work a shared place to start, move, stay visible, and become reusable context, instead of leaving agent runs, assumptions, and decisions trapped in private sessions across Claude Code, Codex, Cursor, ChatGPT, or other tools. Vokal connects channels, tasks, docs, files, apps, agents, memory, Knowledge Base, identity, access, runtime, and event logs around the work, helping teams keep output aligned, reviewed, controlled, and reusable. Agents can work in shared channels with named owners, roles, instructions, sources, statuses, permission scopes, app grants, memory scope, local project-file grants, and visible activity. Teams can use pre-built roles for engineering, product, growth, support, operations, research, and customer work, or bring their own local Codex, Claude Code, Hermes, etc.Starting Price: $20 per month -
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Tulsk
Tulsk
Tulsk is an agentic project management workspace for small startup teams, built to plan, run, and monitor autonomous AI work across projects, docs, tasks, comments, and agent workflows in one shared workspace. Teams use Tulsk to delegate real work to AI agents instead of managing separate chat windows, prompts, and half-finished outputs. Users can mention an agent in any task, and the agent reads the context, executes the work, and posts the result back in the thread with no copy-paste or babysitting. Tulsk combines projects, statuses, priorities, attachments, real-time comments, OpenClaw agent runtime, EMA AI project manager, Skills, MCP access, and agent scheduling in one workspace. OpenClaw gives agents their own dedicated cloud workspace with browser, shell, web search, editable persona files, attached skills, and tool access, so they can handle long-running jobs such as market research, competitor analysis, reports, content drafts, operational checks, and specialized workflows.Starting Price: $39 per month -
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JetStream Security
JetStream
JetStream Security is a security-first AI governance platform designed to give enterprises full visibility, control, and accountability over their AI systems by turning them from opaque, fragmented tools into managed, traceable infrastructure. It acts as a centralized control plane that connects identity, runtime governance, observability, and financial oversight into a single system, allowing organizations to “see every AI action, tie actions to accountable owners, [and] keep workflows inside approved boundaries” while enforcing policy at runtime. It introduces agentic identity, binding human, agentic, and non-human identities to specific actions and access permissions, ensuring every invocation, tool call, or workflow can be traced and governed through least-privilege access principles. Through continuous runtime governance, JetStream compares live AI behavior against approved blueprints, using immutable logging and real-time observability to detect drift. -
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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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MiniMax Code
MiniMax
MiniMax Code brings the agent experience to Mac and Windows, where users can pick a workspace, describe what they need, and let the agent read, analyze, batch-process, and act on local files or remote tasks. Instead of manually managing every step, users define the goal and MiniMax Code builds the right agent team, soloing simple tasks and teaming up on complex work. The agent remembers habits, preferences, projects, and repeated workflows through persistent memory, generating skills over time so users do not have to explain the same context again. It is designed to work where people already chat, handling local files, remote work, schedules, teams, memories, and skills directly from the conversation. The product supports advanced coding and agentic workflows, including multi-file edits, test-validated repairs, long-horizon tool chains, planning, document summarization, creative writing, research, full-stack development, reports, presentations, web development, and everyday Q&A.Starting Price: $20 per month -
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Nimbalyst
Nimbalyst
Nimbalyst is a free, local, visual workspace for building with Claude Code and Codex. Nimbalyst provides a session and task manager and visual editors for markdown, mockups, diagrams, drawings, csv, mcp, data-models, code, sessions, and tasks. Nimbalyst enables builders (developers, product managers, designers, and others) working with agents to achieve: - Higher bandwidth: a visual workspace to collaborate with your agents on sessions, files, and tasks. - Richer context: live diffs, linked files, and integrated editors keep you and your agents on the same page - Faster workflows: your agent builds custom tools and visual interfaces for your use cases right inside the workspace where you workStarting Price: $0/user/month -
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Apigene
Apigene
Apigene MCP Gateway is the runtime layer that connects AI agents to APIs and MCP servers through the Model Context Protocol. It exposes agent tools, context, skills, and instructions as a single remote MCP endpoint that is fully managed and governed, making MCP native rather than experimental. Apigene provides the full agent foundation layer as one MCP Gateway, allowing agents to securely access APIs and MCP servers without custom glue code or framework-specific logic. Teams can build AI agents using chat, defining which APIs and MCP servers the agent can use, how it should reason, and how it should act without code. It supports intelligent tool selection, automatically matching the right API or MCP tool to each request, and multi-platform deployment across ChatGPT, Claude, Cursor, Gemini, VS Code, internal copilots, enterprise AI platforms, and custom apps.Starting Price: $200 per month -
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Reasonix
Reasonix
Reasonix is an open source coding agent designed for long autonomous sessions that remain readable, auditable, and reversible. One local engine powers four interfaces: terminal, desktop app, browser, and ACP-compatible editors, with sessions, permissions, skills, and MCP servers shared across them. Plan mode holds every write until the proposed steps are reviewed and approved, while reads, writes, and shell commands are separately gated and constrained by a workspace sandbox. Each turn creates a checkpoint outside Git, allowing users to rewind a long run without affecting commit history. MCP support over stdio, SSE, and streamable HTTP merges external tools into one registry, while Markdown skills and isolated subagents extend the agent without requiring a fork. Reasonix maps a codebase once and keeps that map throughout the session, letting users queue tasks, review diffs, and resume work without losing context.Starting Price: Free -
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Memory AGI
Memory AGI
Memory AGI is a runtime memory layer for AI agents, built around the idea of giving agents real muscle memory. Hand over a slice of company data, and Memory AGI builds the organization’s knowledge and runtime memory layer, grounds agents in the business, and keeps that context current automatically. Your AI is only as good as the context you give it; without it, agents stay stuck at an intern-level, guessing at how the company runs. Memory AGI turns processes into knowledge agents that can actually execute, so they run reliably, show their work, and can be trusted with what they ship. It is built on three layers of muscle memory. Dynamic Ingestion captures and structures the company’s unique knowledge from voice notes, internal documents, or the tools where data already lives. The Runtime Memory Layer gives agents access to a live, de-duplicated context layer; a company knowledge base that humans, agents, and automations can all draw on to perform tasks like the best employees. -
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Keycard
Keycard
Keycard is an identity-and-access infrastructure platform built for the agent-native era, enabling developers and enterprises to securely connect AI agents, users, services, and APIs with real-time, policy-driven identity controls. It issues dynamic, ephemeral access tokens in place of static secrets and supports federated identity models to unify users, agents, and workloads under a distributed authorization framework. The platform provides drop-in SDKs for popular frameworks so developers can build agent-aware applications without becoming IAM experts. Keycard’s data model includes identity-attested agents, tasks, tools, and resources, allowing logical zones with context-aware permissions and auditability. On the policy side, security teams can define deterministic, task-based rules that enforce who (user/agent) can do what (task) on which resource under which conditions, all with full transparency. -
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Phoenix.vu
iBoson Innovations Private Limited
Phoenix.vu is an AI coding agent built natively for Xcode — not a generic tool adapted to fit. Describe a change in plain English, and Phoenix.vu reads your actual project structure, writes the Swift code, runs the real Xcode build, and iterates through compiler errors until it compiles clean. It's especially strong at build-error and failing-test fixes, bounded refactors across multiple files, and generating tests for existing code. Every change comes back as a reviewable diff inside Xcode — nothing applies without approval, and there's no copy-pasting between a chat window and your editor. It remembers project context across sessions, so you're not re-explaining your codebase each time. Privacy-first: source code and project history stay local on your Mac; only the minimal context a task needs is sent for inference, and nothing is retained afterward. Pricing is pay-as-you-go credits from $10, no subscription required.Starting Price: $10 -
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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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Tragentics
Tragentics
Tragentics is the AI agent security platform that authenticates every agent, injects keys from an encrypted Credential Vault so agents never hold them, routes every call through a content-blind relay, and records a metadata-only audit trail — across platforms and protocols. Tragentics runs no inference and executes no agent logic. It never reads or stores what your agents say. Every agent gets a permanent ID and an Ed25519 identity, keys are encrypted at rest with AES-256-GCM, and every call is authenticated, rate-limited, and recorded as metadata only — never payloads. Protocol-agnostic: it routes MCP, A2A, ACP, OpenAI, ANP, and DID traffic for the agents you already own.Starting Price: $39/month -
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OpenViking
OpenViking
OpenViking is an open source context database designed specifically for AI agents, built around a file-system paradigm that unifies the management of memories, resources, and skills. Instead of treating context as scattered chunks in a fragmented vector store, OpenViking organizes agent context into a virtual file system under the viking protocol, giving agents a structured way to store, navigate, retrieve, and observe the information they need. It is designed to help developers move beyond the hassle of manual context management by giving agents a minimalist interaction model for context, similar to reading and writing files. OpenViking supports hierarchical context loading, semantic retrieval, recursive retrieval, sessions, metrics, and observability, making it possible for AI agents to access the right level of information without stuffing everything into the prompt.Starting Price: Free -
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Idira
Idira by Palo Alto Networks
Idira is Palo Alto Networks’ next-generation identity security platform built for the AI enterprise, designed to secure every human, machine, and agentic identity through one unified control plane. It modernizes privileged access management by extending privilege controls beyond administrators to every identity that can access sensitive systems, data, applications, cloud services, workloads, endpoints, secrets, certificates, SSH keys, and AI agents. It discovers identity risk, applies privilege dynamically, and governs the full lifecycle from first access to final session. Idira replaces static, always-on access with dynamic privilege, just-in-time access, zero standing privilege, continuous verification, policy-driven controls, and real-time enforcement based on identity, device, and context. For human identities, it unifies privileged access, workforce access, endpoint privilege management, and identity governance, helping organizations reduce privilege sprawl. -
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Gentoro
Gentoro
Gentoro is a platform built to empower enterprises to adopt agentic automation by bridging AI agents with real-world systems securely and at scale. It uses the Model Context Protocol (MCP) as its foundation, allowing developers to automatically convert OpenAPI specs or backend endpoints into production-ready MCP Tools, without writing custom integration code. Gentoro takes care of runtime concerns like logging, retries, monitoring, and cost optimization, while enforcing secure access, auditability, and governance policies (e.g., OAuth support, policy enforcement) whether deployed in a private cloud or on-premises. It is model- and framework-agnostic, meaning it supports integration with various LLMs and agent architectures. Gentoro helps avoid vendor lock-in and simplifies tool orchestration in enterprise environments by managing tool generation, runtime, security, and maintenance in one stack. -
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Permiso
Permiso Security
Permiso is an identity security platform that secures human, non-human, and AI identities across cloud, SaaS, and on-premises environments. The platform is built around its Universal Identity Graph, which connects identities to credentials, machines, agents, permissions, and runtime activity to provide continuous visibility across authentication boundaries. Permiso helps organizations discover identities, evaluate identity risk, detect threats, and defend against account compromise, insider threats, and attacks targeting AI agents and non-human identities. The platform combines identity discovery, posture management, runtime monitoring, threat detection, and response capabilities into a single identity security solution. It continuously analyzes identity behavior, permissions, tool calls, API activity, and machine interactions to identify suspicious activity before it becomes an incident. -
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Kuku
Kuku
Kuku is a native macOS note-taking and knowledge management app that combines a lightweight Markdown editor with modern AI-driven tools while keeping your files as plain .md on your disk so they remain accessible by editors like vim, versionable with git, and free from cloud vendor lock-in. It supports bidirectional links with autocompletion and backlinks panels that help you interconnect ideas, plus a graph view for visualizing relationships between notes. It includes an AI agent powered by Gemini with a tool that can search your local vault, read files, generate summaries, and create or edit documents with cursor-style edit previews that show suggested changes as diffs before you accept or reject them. Kuku also offers local Whisper speech-to-text for offline audio transcription, fast full-text search using SQLite FTS5 with BM25 ranking, and a native performance footprint built on Tauri that results in a small installation and low memory usage without Electron overhead.Starting Price: $12 per month -
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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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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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Raft
Raft
Raft is a real-time collaboration platform where humans and AI agents work together as teammates in channels, direct messages, threads, and tasks. Chat is the workspace, so people and agents share the same conversations, context, and project history without moving work between separate tools. Each agent is a persistent, long-running process with its own identity, memory, expertise, and workspace, allowing it to retain codebase knowledge, preferences, and past discussions across days and tasks. Agents can claim work, run in parallel, hand tasks to one another, review each other’s output, mention teammates, and keep progress visible in shared threads while humans set direction, steer the work, and make final decisions. Raft supports multiple agent runtimes, including Claude, Codex, Hermes, and others, so teams can use different models and computers for different roles within the same project. Existing external agents can also join channels like regular team members.Starting Price: $8.80 per month -
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MemClaw
Caura AI
MemClaw is a persistent-memory service for LLM-based agents and a governed shared memory layer for agent fleets. It is designed to help AI agents learn from each other by turning isolated agent context into a Company Brain with memory, governance, provenance, contradiction detection, and visibility scopes built in from day one. MemClaw separates an organization’s agent force, including tenants, fleets, nodes, and agents, from the governed memory plane through MCP Server, REST API, OpenClaw plugin, MemClaw Core, and persistent storage. Agents can write to and recall from the Company Brain through MCP-compatible tools, direct HTTPS calls, or OpenClaw integration, while MemClaw Core runs enrichment such as entity extraction, contradiction detection, PII scanning, and lifecycle transitions before anything is stored. Every memory can be stamped with a visibility scope, auto-classified into types such as fact, episode, decision, preference, rule, plan, commitment, action, and outcome.Starting Price: $49 per month -
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Timbal
Timbal
Timbal is the end-to-end AI ecosystem for enterprises; a production AI platform that enterprise teams use to build, deploy, and govern agents, workflows, interfaces, and knowledge bases on the models they choose. Teams can define behavior in code or in Studio, run on the model and provider of their choice, and ship to chat, email, voice, and product UI from a single runtime. Timbal brings together the full production stack: a typed Python framework, a Studio for building visually, a runtime that orchestrates agents and workflows, governance and evals for enterprise rollout, and integrations with the systems teams already use. Agents provide autonomous AI for real work with reasoning, tools, and memory, while workflows create deterministic AI pipelines that chain steps, branch on logic, retry failed steps, stream outputs, and guarantee outcomes. Interfaces let teams ship custom AI experiences from chat to dashboards to voice, and knowledge bases connect company context.Starting Price: €25 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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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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Maetra
Maetra
Maetra is an AI governance and compliance control plane for teams operating tool-using AI agents. Discover inventories agents and capabilities; Comply maps systems to applicable frameworks and keeps reusable evidence current; Govern evaluates consequential actions against versioned policies and routes human approval when required. Secure scans prompts, messages, model outputs, and tool calls for prompt injection, data exposure, unsafe actions, and policy violations. Task Guard detects task drift, scope changes, and mismatched effects. Interaction Guard protects supported browser-AI prompts and files, while Audit preserves linked decision, approval, runtime, and change evidence. Teams can adopt modules separately or together through the web app, REST APIs, SDKs, and MCP. A 14-day no-card trial is available, with paid plans from $20/month.Starting Price: $20/month -
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IronClaw
Near AI
IronClaw is a secure, open source runtime designed to run autonomous AI agents with strong built-in protections for credentials and system access. It positions itself as a security-focused alternative to OpenClaw, operating inside encrypted enclaves on the NEAR AI Cloud or locally to protect sensitive data throughout execution. It enables users to deploy AI agents quickly through one-click setup while keeping API keys, tokens, and passwords stored in an encrypted vault that the AI itself cannot directly access. IronClaw isolates every tool inside its own WebAssembly sandbox with capability-based permissions and strict resource limits, preventing compromised skills from affecting other parts of the system. It is built in Rust to enforce memory safety at compile time and eliminate common exploit classes such as buffer overflows and use-after-free errors.Starting Price: $20 per month -
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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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NullClaw
NullClaw
NullClaw is an ultra-lightweight autonomous AI assistant infrastructure built in Zig and distributed as a single static binary designed to run efficiently on virtually any hardware. It emphasizes extreme performance and minimal resource usage, shipping as a roughly 678 KB executable that typically consumes about 1 MB of RAM and boots in under two milliseconds. It eliminates traditional runtime overhead by avoiding virtual machines, interpreters, and complex dependency chains, allowing developers to deploy agents simply by running the compiled binary. Despite its small footprint, the framework provides a full autonomous agent stack with support for more than 22 model providers, 18 communication channels, hybrid vector and FTS5 memory, streaming, voice, and multi-layer sandboxing. Security is built in through workspace scoping, explicit command allowlists, encrypted secrets, and strict sandbox isolation using tools such as Landlock, Firejail, or Docker.Starting Price: Free -
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JetBrains Air
JetBrains
Air is an agentic development environment created by JetBrains that allows developers to delegate coding tasks to multiple AI agents and manage them within a single, unified workspace. Instead of functioning as a simple chat-based assistant, it is designed as a full development environment where tools are built around AI agents, enabling users to guide, supervise, and refine their output more effectively. Developers can run several agents concurrently, each working on different tasks in isolated environments, which helps prevent conflicts and improves productivity when handling complex projects. It supports integration with multiple AI systems such as Claude, Gemini, Codex, and other coding agents, allowing flexible, model-agnostic workflows within the same interface. Users can define tasks with rich context by referencing specific files, commits, classes, or code elements, ensuring that the agents generate more accurate and relevant results based on the actual codebase.Starting Price: Free -
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Gemini Managed Agents
Google
Gemini Managed Agents provides a visual way to prototype and learn how to build managed agents without having to create and write API calls. Managed agents on the Gemini API give developers a configurable agent harness where a single API call provisions a secure Linux sandbox for the agent to reason, execute code, manage files, and browse the web autonomously. In AI Studio Playground, users can switch to the Agents tab and start from pre-built templates that configure the base Antigravity Agent with tools, environment settings, instructions, and skills. The Antigravity Agent is a general-purpose managed agent powered by Gemini 3.5 Flash, able to run code, manage files, search the web, and be extended with custom instructions, skills, and data. Agent behavior, persona, and capabilities are defined through files in the environment, including AGENTS.md for system instructions and persona, and SKILL.md files for specific capabilities and workflows.Starting Price: $1.50 per 1M tokens -
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Agent 37
Agent 37
Agent 37 is a no-code AI agent platform designed to let users build, deploy, and monetize autonomous AI “skills” or assistants without handling infrastructure or complex engineering. It provides a hosted runtime where creators can upload their expertise, workflows, or tools and turn them into fully functional AI agents that can execute real actions such as API calls, web browsing, code execution, file processing, and automation tasks, rather than just generating text responses. It supports multiple leading AI models, including Claude, GPT, and Gemini, and offers more than 1,000 integrations, enabling agents to connect with external tools and services seamlessly. Agent 37 includes built-in features for hosting, authentication, analytics, and monetization, allowing creators to distribute their agents through shareable links, embed them on websites, and charge users through integrated payment systems.Starting Price: $3.99 per month -
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Oqoqo
Oqoqo
Oqoqo is a platform for building evals and custom benchmarks for real-world agentic tasks, letting teams run experiments at scale in realistic environments on fully managed cloud infrastructure. Users can define private task sets and rubrics, test whether agents can use products such as skills, MCP servers, CLIs, SDKs, APIs, documentation, and files, and compare agents, models, treatments, and effort levels under the same conditions. Each task runs independently in its own isolated environment with the project state, context, files, tools, and credentials it needs. Oqoqo captures the full trajectory of every run, including commands, tool calls, errors, files, and where an agent stopped, then reports pass or fail results, pass rates, lift, token usage, and friction. Teams can use these insights to identify product interface issues, token inefficiencies, and performance differences, fix what failed, and rerun the experiment.Starting Price: $20 per month -
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Defakto
Defakto
Defakto secures every automated interaction by issuing short-lived, verifiable identities to non-human actors such as services, pipelines, AI agents, and machines, eliminating static credentials, API keys, and standing privileges. Their unified non-human identity and access management solution enables discovery of unmanaged identities across cloud, on-premises, and hybrid environments, issuance of dynamic identities at runtime tied to policy, enforcement of least-privilege access, and full audit-ready logging. The product consists of modules; Ledger for continuous discovery and governance of non-human identities; Mint for automated issuance of purpose-bound, ephemeral identities; Ship for secretless CI/CD workflows where hard-coded credentials are removed; Trim for automatic right-sizing of access and removal of over-privileged service accounts; and Mind for securing AI agents and large-language models with the same identity model used for workloads. -
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Pillar Security
Pillar Security
Pillar Security is a unified AI security platform for securing the agentic workforce across the entire AI lifecycle, from development to deployment and runtime protection. It connects business context across discovery, testing, and protection so security intelligence compounds across AI applications, agents, models, prompts, frameworks, tools, MCP servers, skills, coding agents, SaaS, cloud, code, and endpoints. Pillar helps organizations discover and manage AI assets everywhere, including shadow AI and unapproved systems, assess supply chain and posture risks, map agentic attack surfaces, and validate the vulnerabilities that actually matter. Its AI Security Posture Management capabilities analyze connected agents, tools, permissions, data sources, prompts, models, and supply chain components to expose risky paths, policy violations, misconfigurations, coding agent risks, and blast radius when a single component is compromised. -
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Contextual AI
Contextual AI
The Contextual AI Platform is an enterprise-grade solution designed to help teams build AI agents that reduce hours of technical work to just minutes. It brings together state-of-the-art context engineering tools, enterprise data management, and production-ready security in one unified platform. With Agent Composer, users can define and configure specialized AI agents using natural language prompts, visual editors, or pre-built templates. The platform supports continuous ingestion and extraction from massive knowledge bases, transforming unstructured enterprise data into actionable intelligence. Contextual AI enables traceable reasoning, fine-grained attribution, and grounded outputs that users can trust. Its robust runtime ensures agents perform reliably at scale across complex document volumes. The platform is built to move organizations from experimentation to production quickly and confidently. -
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Better Claw
Better Claw
BetterClaw is a no-code AI agent builder for teams that need agents working, not infrastructure. Users can describe a job in chat, connect tools and an LLM provider, and deploy autonomous agents without Docker, YAML, config files, or VPS hosting. Agents can run on schedules across Telegram, Slack, Discord, Gmail, and custom webhooks, while tracked task states show work as backlog, ready, running, success, or failure and let failed runs be re-queued. The platform runs any OpenClaw-compatible skill and includes curated skills that pass a four-layer security audit. Teams can turn successful conversations into reusable skills, connect more than 30 LLM providers, and have agents return real deliverables including PDF, DOCX, XLSX/CSV, images, audio, video, and Markdown rather than chat text that must be copied manually. Built-in security includes AES-256 encrypted credentials, isolated containers per agent, five-minute secrets auto-purge, per-agent credential grants, access audit logs, etc.Starting Price: $49 per month -
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Obot MCP Gateway
Obot
Obot is an open-source AI infrastructure platform and Model Context Protocol (MCP) gateway that gives organizations a centralized control plane for discovering, onboarding, managing, securing, and scaling MCP servers, services that connect large language models and AI agents to enterprise systems, tools, and data. It bundles an MCP gateway, catalog, admin console, and optional built-in chat interface into a modern interface that integrates with identity providers (e.g., Okta, Google, GitHub) to enforce access control, authentication, and governance policies across MCP endpoints, ensuring secure, compliant AI interactions. Obot lets IT teams host local or remote MCP servers, proxy access through a secure gateway, define fine-grained user permissions, log and audit usage, and generate connection URLs for LLM clients such as Claude Desktop, Cursor, VS Code, or custom agents.Starting Price: Free -
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HOL Guard
HOL
HOL Guard is a local-first runtime security layer for AI agents that watches what an AI assistant is about to do and stops risky actions before they happen. It sits between the agent and the computer, evaluating supported tool calls and local artifacts for threats such as secret and credential exposure, destructive commands, prompt-injection-driven actions, malicious or changed packages, risky MCP configuration, and unsafe plugins, skills, hooks, and settings. Known threats can be blocked automatically, while ambiguous actions are paused for user approval so people remain in control. Guard runs entirely on the developer’s machine, works offline, and does not upload files, prompts, or passwords. Local checks typically complete in under 50 milliseconds and require no changes to existing code or routines. It supports coding agents including Claude Code, Cursor, Codex, Gemini CLI, OpenCode, Hermes, and OpenClaw, with tailored integrations that inspect actions before execution.Starting Price: $4.99 per month -
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ZGI
ZGI
ZGI is an open source enterprise AI platform for building business-ready agents with company data, tools, workflows, models, and skills. Its Agent Runtime lets agents load Skills, use company knowledge and live data, call tools, and return useful work fast. The Model Gateway connects global and domestic providers such as OpenAI, Anthropic, Google, DeepSeek, and Qwen, allowing teams to choose the right model for each agent by quality, availability, cost, or region while centrally controlling access, quotas, routing policies, and fallback. The product workspace covers the full agent lifecycle: Agent Studio combines Skills, knowledge, tools, and models; Workflows orchestrate multi-step work and let users inspect every execution; Database supports natural-language queries over live business data with governed access; Model Management handles provider connections and enterprise routing; and Knowledge Assets turn company files into searchable, source-aware knowledge.Starting Price: Free -
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Skydive
Skydive
Skydive is a platform for building AI agents that complete real work inside the tools teams already use. Instead of giving users a chatbot or asking them to construct workflows, it lets them describe the outcome they need in plain English and builds an agent around it, with no code, workflow canvas, or prompt engineering required. Every agent has its own cloud computer with a browser, terminal, and file system, allowing it to log into web-based tools, navigate interfaces, pull data, update systems, create files, and complete tasks from start to finish. Agents can work across Slack, email, iMessage, the web, desktop, and CLI while maintaining the same identity and continuous memory. Context, preferences, corrections, and decisions persist across sessions so agents improve as teams work with them. Multiple agents can collaborate automatically, with one agent’s output becoming another’s input without manually mapping handoffs.Starting Price: $20 per month -
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LM Studio Bionic
LM Studio
LM Studio Bionic is an AI agent built for getting real work done with open models across coding, research, documents, files, and general knowledge work. It gives users flexible control over where models run: locally on their device, through LM Link, or with frontier open-source models in LM Studio Secure Cloud for heavier tasks. Local models are powered by the LM Studio runtime and can be downloaded directly inside the app, while cloud requests use Zero Data Retention and are processed without being stored after completion. For coding, users can connect a local folder as a Code project and ask Bionic to inspect a codebase, explain unfamiliar logic, search for relevant files, trace behavior, edit code, or debug issues. Inline diffs make changes easy to review as the agent works. Work projects support documents, PDFs, presentations, spreadsheets, and local directories, allowing Bionic to generate new files, organize materials, summarize content, edit existing work, and more.Starting Price: Free -
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Microsoft Agent 365
Microsoft
Microsoft Agent 365 introduces a unified control plane that allows organizations to deploy, manage, and secure AI agents with the same confidence they apply to user management. It gives enterprises full visibility into all agents, including Entra-verified agents, self-registered agents, and shadow agents running across the environment. Built on Microsoft’s trusted ecosystem, Agent 365 extends familiar tools like Entra, Defender, Purview, Power Apps, and Microsoft 365 to support identity, security, governance, and productivity for agents. With Work IQ, organizations can connect agents directly to their unique company data and workflows, enabling smarter, more context-aware automation. IT admins can access Agent 365 early via Frontier, Microsoft’s early access program, and activate it at the tenant or user level. Designed to scale with modern AI adoption, Agent 365 ensures that enterprise agentic systems remain secure, compliant, and manageable from day one. -
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Traversal
Traversal
Traversal is an ambient AI Site Reliability Engineering (SRE) agent that operates 24/7 to autonomously troubleshoot, fix, and even prevent production incidents. It parses logs, metrics, traces, and your codebase to narrow down root causes of errors or latency, surfacing the blast radius, key bottleneck services, and candidate root causes with supporting evidence within minutes. Powered by advances in causal machine learning, large language model reasoning, and AI agents, Traversal catches issues before alerts fire and resolves them automatically. Designed for critical infrastructure and complex organizations, it supports heterogeneous data, bring-your-own models, and optional on-premises deployment. Traversal connects easily to existing systems with read-only access, no agents or sidecars, and no writes to production, ensuring privacy and control over data. By integrating seamlessly into your observability stack, Traversal reduces time to resolution, minimizes downtime, and more.
