Alternatives to NVIDIA OpenShell
Compare NVIDIA OpenShell alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to NVIDIA OpenShell in 2026. Compare features, ratings, user reviews, pricing, and more from NVIDIA OpenShell competitors and alternatives in order to make an informed decision for your business.
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1
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. -
2
Ivanti Policy Secure
Ivanti
Ivanti Policy Secure (IPS) delivers enterprise-grade network access control (NAC) built for IT and security teams who need continuous, policy-driven enforcement across every device type, managed, unmanaged, and IoT alike. By continuously validating user identity and device security posture prior to granting network access, IPS reduces the risk of credential-based compromise and non-compliant endpoint connectivity at the network layer. Centralized policy orchestration enables granular, least-privilege access enforcement across wired, Wi-Fi, and cloud environments without requiring architectural overhauls. Full estate visibility through active device detection and classification closes the blind spots that traditional network access control solutions leave around shadow IT and IoT assets. Automated remediation workflows handle non-compliant devices without manual intervention, while integrated guest access management maintains productivity for transient users. -
3
NVIDIA Open Agent Safety Platform is an open reference design for continuously monitoring and governing AI agent behavior, helping organizations keep agents isolated, observable, auditable, and within defined operational boundaries. It combines runtime governance, continuous threat detection, and hardware-isolated policy enforcement to secure enterprise AI agents from testing through deployment. NVIDIA OpenShell provides an open-source runtime that separates how agents execute from how they reach data, tools, and external systems, using sandboxed execution and deterministic, zero-trust policy enforcement to control what agents can see, do, and interact with. Policies are enforced outside the agent process, helping limit the impact of unexpected behavior. NVIDIA Sentry adds an independent security layer that observes agent requests and responses, establishes verifiable agent identities, continuously governs access to data, tools, APIs, and services, and can quarantine agents.
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4
nono
Always Further
nono is an open source, kernel-enforced sandbox for AI coding agents and LLM workloads. Unlike policy-based guardrails that intercept and filter operations, nono uses OS security primitives — Landlock on Linux and Seatbelt on macOS — to make unauthorised operations structurally impossible at the syscall level. Wrap any AI agent — Claude Code, OpenCode, OpenClaw, or any CLI process — with a single command. nono applies default-deny filesystem access, blocks destructive commands (rm, dd, chmod, sudo), isolates credentials and API keys, and cascades all restrictions to child processes. No escape mechanism exists once restrictions are applied. Built-in profiles get you running in seconds. Secrets inject securely from the system keystore and are zeroised on exit. Audit logging, atomic rollbacks, and Sigstore-attested policy signing are on the roadmap. Apache 2.0. From the creator of Sigstore. -
5
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 -
6
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 -
7
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 -
8
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 -
9
fx
Vercel
fx is a tiny, open, native coding agent harness and CLI written in Zig, optimized for research, performance, and embeddability as part of larger systems. Its design focuses on minimalism across the system prompt, tools, feature set, memory use, and a 6 MB binary, with an interface intended to feel closer to a Unix shell than a heavy terminal IDE. fx cold starts in microseconds and performs no unnecessary work or I/O before accepting input, making it suitable for programmatic use, resource-constrained environments, and agent sandboxes. Developers can start it inside a project and ask it to read files, search code, run commands, make changes, execute tests, and stream tool calls as they happen. The core is model- and provider-agnostic, supporting local models, gateways, direct provider access, and cloud inference. It is context-efficient by design, using a minimal system prompt and toolset to reduce token overhead and improve time to first token.Starting Price: Free -
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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. -
11
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). -
12
AGBCLOUD
AGBCLOUD
AGBCLOUD is an AI-native, cloud-based sandbox platform that provides developers and organizations with secure, isolated runtime environments for building and operating autonomous software agents. It equips agents with professional cloud development environments that support multilingual code generation, compilation, and debugging within browser-accessible sandboxes. It enables advanced capabilities such as browser use, computer use, and data analysis so AI systems can safely interact with files, applications, and the web in a controlled environment. AGBCLOUD integrates plug-and-play MCP tools and LLM-powered analytics to transform raw data into actionable insights and interactive applications. Its cross-platform sandbox architecture allows agents to move seamlessly between coding, browsing, and system-level operations while maintaining strong isolation and security.Starting Price: Free -
13
MCPTotal
MCPTotal
MCPTotal is a secure, enterprise-grade platform designed to manage, host, and govern MCP (Model Context Protocol) servers and AI-tool integrations in a controlled, audit-ready environment rather than letting them run ad hoc on developers’ machines. It offers a “Hub”, a centralized, sandboxed runtime environment where MCP servers are containerized, hardened, and pre-vetted for security. A built-in “MCP Gateway” acts like an AI-native firewall: it inspects MCP traffic in real time, enforces policies, monitors all tool calls and data flows, and prevents common risks such as data exfiltration, prompt-injection attacks, or uncontrolled credential usage. All API keys, environment variables, and credentials are stored securely in an encrypted vault, avoiding the risk of credential-sprawl or storing secrets in plaintext files on local machines. MCPTotal supports discovery and governance; security teams can scan desktops and cloud instances to detect where MCP servers are in use.Starting Price: Free -
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Whim
Whim
Whim is a cloud dev workspace for running AI coding agents at the speed of thought. It lets developers run AI coding agents like Claude Code and Codex in isolated cloud containers instead of running them locally on a laptop. Each task gets its own sandboxed Ubuntu environment with full shell access, git branch isolation, and real-time terminal streaming, allowing developers and teams to use AI coding agents in daily workflows with parallelism, collaboration, and zero local setup. Users can connect a repo, write a prompt, and the AI agent starts working in a secure cloud container accessible from any device. Multiple tasks can run simultaneously, making it possible to try different approaches, work on separate features, or let an orchestrator coordinate a squad of agents without them stepping on each other’s toes. Whim supports Claude and GPT models through native CLI runtimes, with additional models planned through OpenRouter.Starting Price: $50 per month -
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Prime Intellect
Prime Intellect
Prime Intellect is the open superintelligence stack: an integrated compute, training, inference, and sandbox platform for teams that want to train, deploy, and continuously improve their own models. The stack is built around owning intelligence instead of waiting on frontier models to improve, giving users one loop for reinforcement learning environments, hosted evaluations, large-scale training, inference, and compute. In Lab, teams can post-train self-improving agents by turning tasks into RL environments, creating, developing, evaluating, and pushing them with the Prime CLI. The Environment Hub gives access to and contributions across 2,500+ open-source RL environments, while hosted evaluations let teams benchmark model performance across open-source models with no infrastructure or setup. Hosted Training supports large-scale models optimized for agentic workflows, managed training workflows with full visibility and control, and hands-on support from the applied research team. -
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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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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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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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epho
epho
Epho turns coding agents into an API, letting developers run Claude Code, Codex, or OpenCode in isolated cloud sandboxes through a single HTTP endpoint. Send a prompt, choose a harness and model, attach repositories and files, connect MCP servers, and pass environment variables or provider credentials; Epho boots the environment, clones the code, wires in the tools, and streams the agent’s work back as it happens. Runs can return live events, tool calls, edits, final answers, and artifacts, or execute asynchronously with polling and webhooks. Chats are durable, so follow-up turns can resume with the same filesystem, checkout, agent session, system prompt, model, and MCP configuration even if the original sandbox is gone. Private GitHub, GitLab, and Bitbucket repositories are supported, and agents can read code, make changes, run tests, and iterate on failures just as they would locally. Every event is persisted, allowing interrupted streams to reconnect without losing the run.Starting Price: $0.00013 per GiB per hour -
20
OpenFang
OpenFang
OpenFang is an open source Agent Operating System built in Rust that provides a unified runtime for building, deploying, and managing autonomous AI agents at production scale. It packages a batteries-included architecture into a single binary, enabling developers to run agents that operate continuously, build knowledge graphs, and report results to a centralized dashboard without constant user prompts. At the core of OpenFang are “Hands,” pre-built autonomous capability packages that execute on schedules and perform tasks such as lead generation, research, browser automation, and social management. It includes dozens of pre-built agents, native tools, and channel adapters that allow agents to function across platforms like Slack, WhatsApp, Discord, and Teams from a single environment. Security is built into the foundation through multiple defense layers such as WASM sandboxing, cryptographic signing, taint tracking, and tamper-evident audit trails.Starting Price: Free -
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Superagent
Superagent
Superagent is an open source AI safety and agent development platform that helps developers and organizations build, deploy, and protect AI-driven applications and assistants by embedding safety guardrails, runtime security, and compliance controls into agent workflows. It provides purpose-trained models and APIs (such as Guard, Verify, and Redact) that block prompt injections, malicious tool calls, data leakage, and unsafe outputs in real time, while red-teaming tests probe production systems for vulnerabilities and deliver findings with remediation guidance. Superagent integrates with existing AI systems at inference and tool-call layers to filter inputs/outputs, remove sensitive data like PII/PHI, enforce policy constraints, and stop unauthorized actions before they occur, offering unified observability, live trace logs, policy controls, and audit trails for security and engineering teams.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 -
23
NVIDIA TensorRT
NVIDIA
NVIDIA TensorRT is an ecosystem of APIs for high-performance deep learning inference, encompassing an inference runtime and model optimizations that deliver low latency and high throughput for production applications. Built on the CUDA parallel programming model, TensorRT optimizes neural network models trained on all major frameworks, calibrating them for lower precision with high accuracy, and deploying them across hyperscale data centers, workstations, laptops, and edge devices. It employs techniques such as quantization, layer and tensor fusion, and kernel tuning on all types of NVIDIA GPUs, from edge devices to PCs to data centers. The ecosystem includes TensorRT-LLM, an open source library that accelerates and optimizes inference performance of recent large language models on the NVIDIA AI platform, enabling developers to experiment with new LLMs for high performance and quick customization through a simplified Python API.Starting Price: Free -
24
CodeTrain
InferHaven
CodeTrain is a training tool for engineers who ship with AI and can no longer explain everything they shipped. It takes a question, a repo, or an onboarding task and turns it into a short lesson of two to six steps against the real code. The learner types every line. The tutor plans the steps, runs the code, grades each attempt, and makes the step smaller when someone is stuck instead of handing over the answer outright. The free tier executes Python in the browser through Pyodide, so nothing leaves the machine and the tier costs almost nothing to run. Server-side sandboxes handle the shell and toolchain lessons. The control plane is FastAPI on Fly.io, the front end is static on Cloudflare Pages, auth is Clerk, billing is Stripe. Tutoring runs on Claude models by default, and bring-your-own-key is supported for Anthropic, Bedrock, Vertex, OpenAI-compatible endpoints, and Ollama, so a team can keep inference on infrastructure it already owns.Starting Price: $24/month -
25
OpenAI Agents API
OpenAI
The Agents API lets developers build and run cloud agents with the same harness and infrastructure that powers Codex, fully managed by OpenAI. A production-ready agent can be created with a single API call by specifying the task, model, tools, and environment, while OpenAI hosts and maintains the agent harness. Developers can choose where agents run: in an OpenAI-hosted sandbox, on their own infrastructure, or through supported sandbox partners. OpenAI-hosted sandboxes provide secure environments where agents can run code, work with files, use packages, skills, and plugins, and produce artifacts. The API is designed for long-running work, with automatic context compaction that preserves relevant information as sessions span multiple context windows. Tool search loads relevant tool definitions only when needed, while programmatic tool calling lets agents run calls in parallel, chain related operations, and filter or combine results in code. -
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SURF Security
SURF Security
Create a security air gap, reduce your attack surface and isolate your business from internal and external exploits, while streamlining SaaS apps and accessing your data. Grants access based on the identity of the users and their devices to any SaaS or on-prem apps. Isolated work environment from device and web threats locally on the endpoint, by encrypting, sandboxing and rendering content. Enforcing enterprise browser security policies like DLP, web filtering, phishing protection, extension management and more. SURF brings Zero-Trust principles to the user via the browser, protecting everyone and everything in the enterprise regardless of role. By configuring only a few policies, IT and security teams can significantly reduce the attack surface. Discover the benefits of utilizing SURF from an Information technology perspective. -
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Cisco Secure IPS
Cisco
As cyber attacks evolve, network security requires unparalleled visibility and intelligence covering all threats for comprehensive protection. And with differing organizational responsibilities and agendas, you need a consistent security enforcement mechanism. These increasing operational demands call for a renewed focus on dedicated Secure IPS to provide a deeper level of security and visibility for the enterprise. With Cisco Secure Firewall Management Center, you can see more contextual data from your network and fine-tune your security. View applications, signs of compromise, host profiles, file trajectory, sandboxing, vulnerability information, and device-level OS visibility. Use these data inputs to optimize security through policy recommendations or Snort customizations. Secure IPS receives new policy rules and signatures every two hours, so your security is always up to date. -
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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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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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Apache Mesos
Apache Software Foundation
Mesos is built using the same principles as the Linux kernel, only at a different level of abstraction. The Mesos kernel runs on every machine and provides applications (e.g., Hadoop, Spark, Kafka, Elasticsearch) with API’s for resource management and scheduling across entire datacenter and cloud environments. Native support for launching containers with Docker and AppC images.Support for running cloud native and legacy applications in the same cluster with pluggable scheduling policies. HTTP APIs for developing new distributed applications, for operating the cluster, and for monitoring. Built-in Web UI for viewing cluster state and navigating container sandboxes. -
31
Jozu
Jozu
Jozu is an AI supply chain security platform that verifies artifacts before execution, governs agent activity at runtime, and preserves proof of what happened afterward. Jozu Hub provides a self-hosted registry for models, agents, MCP servers, and skills, centralizing each artifact with cryptographic signatures, attestations, scanning, policy controls, and audit records. Its AI-specific security analysis covers threats such as executable code hidden in model packages, backdoored weights, data poisoning, prompt injection, compromised tools, and license violations. Policies can be authored once, distributed as signed OCI artifacts, and enforced when artifacts are pulled, promoted, admitted, or executed. Jozu Agent Guard runs alongside workloads on servers, desktops, edge devices, and air-gapped systems, applying local prompt and input-output filtering, tool-access controls, approval requirements, and runtime policy enforcement. -
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Tuning Engines
CerebrixOS
Tuning Engines is a unified AI control and governance layer for teams building production intelligence across models, agents, tools, and fine-tuned systems. It brings together the full AI lifecycle in one governed platform: inference, model routing, fallback policies, fine-tuning jobs, datasets, evaluations, model imports and exports, custom models, agents, MCP servers, reusable skills, guardrails, AGT YAML policies, data capture, runtime traces, usage analytics, API keys, billing, team roles, and integrations. Developers get OpenAI-compatible APIs, Anthropic-compatible routes, CLI workflows, MCP access, coding-agent integrations, and resource catalogs for models, agents, tools, and skills. Teams can connect Claude Code, OpenCode, Aider, Cline, Roo, Continue.dev, Cursor, VS Code, Windsurf, and other AI workflows through a single governed platform. -
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Opal Zero
Opal Security
Opal Zero is a just-in-time access governance platform for AI agents that inventories every agent, maps it to an accountable owner, decides each access request, and enforces the decision in the MCP gateway already in place. It gives organizations one inventory across identity providers and AI platforms such as Okta, Entra, Anthropic, OpenAI, Bedrock AgentCore, and Cursor, showing what every agent can access and who owns it. Risk Center surfaces access that is off-purpose, unowned, or standing and routes issues to the appropriate owner with an inline fix. Paladin evaluates requests using policy and context, identifies the least-privileged path, respects owner boundaries, and shows the reasoning behind each decision. Policy Insights uses real agent behavior to identify unused access and opportunities to improve access policy instead of relying on one-off remediation. Gateway Enforcement writes approved decisions as scoped, time-bound policy into existing gateways. -
34
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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Snowflake CoCo
Snowflake
Snowflake CoCo is a data-native AI coding agent that turns complex data engineering, analytics, machine learning, and AI workflows into simple conversations. It understands enterprise context, including catalog, lineage, RBAC policies, compute, and pipeline dependencies, helping generated code reference real objects with the correct permissions. Teams can use CoCo to identify data, build pipelines across dbt, Apache Airflow, Postgres, Spark, and AWS Glue, generate executable ML pipelines for Snowflake Notebooks, and create apps and AI agents grounded in enterprise data. Its agent harness includes Snowflake-specialized tools such as semantic catalog search, data diffing, and sandboxed runtimes rather than relying on generic code wrappers. For complex, multi-step tasks, orchestration can coordinate sub-agents and route between models automatically. CoCo is available as a desktop development environment with access to local files, terminals, and Snowflake.Starting Price: $2 per credit -
36
Dymium
Dymium
Dymium is the real-time data governance layer that ensures AI agents, applications, and analytics only access the precise information they’re permitted to see. Powered by its Ghost Layer architecture, Dymium evaluates every request as it happens, enforcing identity-, role-, and context-aware policies instantly. Sensitive data never needs to be copied, staged, or broadly exposed—access is governed directly at the source through GhostDB, GhostAPI, and GhostMCP. This enables teams to work at inference speed without creating compliance or security risk. Every interaction is logged and auditable in real time, supporting GDPR, HIPAA, and AI Act requirements by default. With Dymium, organizations unlock more data safely while eliminating over-permissioning, data duplication, and operational bottlenecks. -
37
Wafer
Wafer
Wafer delivers the fastest open source LLMs for enterprise through serverless and dedicated inference built for production AI workloads. Its serverless inference gives teams access to top open models with no infrastructure, no deployment overhead, and fast APIs, including GLM-5.2-Fast for low-latency inference with EAGLE speculative decoding and a per-stream throughput SLA, GLM-5.2 as a flagship model with stronger coding and reasoning capabilities, and more. Wafer’s technology uses agents that optimize inference across the stack, identifying and enhancing bottlenecks in orchestration, algorithms, serving engines, GPU kernels, and diverse hardware. It profiles the stack to see whether latency or throughput comes from scheduling, decoding, kernels, memory pressure, or hardware fit, then tries many paths and ships the measured winner. Instead of relying on a single switch or heuristic, Wafer searches model, engine, kernel, and hardware combinations.Starting Price: Free -
38
Kastra
Kastra
Kastra is the authorization layer for AI systems, deciding what agents, models, and AI tools are allowed to do before they do it. It sits in the execution path of every prompt, tool call, shell command, database operation, and API request, evaluates each action against deterministic, attribute-based policy, and returns an allow, deny, redact, or escalate decision in under a millisecond. Unlike monitoring products that observe AI after it acts, Kastra blocks unauthorized behavior before it reaches a tool, API, database, or production system. Its unified control plane combines a policy engine, edge decision points, integrations, and a tamper-evident evidence vault that signs every decision for audit and replay. Kastra Edge brings local enforcement to developer machines, protecting Claude Code, Cursor, Codex CLI, and other coding agents from destructive commands, secret exfiltration, unsafe file writes, and unauthorized tool use.Starting Price: $19.99 per month -
39
Tetragon
Tetragon
Tetragon is a flexible Kubernetes-aware security observability and runtime enforcement tool that applies policy and filtering directly with eBPF, allowing for reduced observation overhead, tracking of any process, and real-time enforcement of policies. eBPF enables deep observability with low-performance overhead, mitigating risks without the latency introduced by user-space processing. Tetragon extends Cilium's design by recognizing workload identities like namespace and pod metadata, surpassing traditional observability. It offers pre-defined policy libraries for rapid deployment and operational insight, reducing setup time and complexity at scale. Tetragon blocks malicious activities at the kernel level, closing the window for exploitation without succumbing to TOCTOU attack vectors. Synchronous monitoring, filtering, and enforcement are performed entirely within the kernel using eBPF.Starting Price: Free -
40
AstrBot
AstrBot AI
AstrBot is an open source, cross-platform Agentic AI assistant and chatbot platform built for chats, automation, and smart collaboration. It runs directly in messaging apps and provides an agent runtime with Sub-Agents, complex workflows, tool calls, context management, scheduled tasks, runtime controls, and isolated agent sandboxes for real actions. Native MCP and Skills support expands AI capabilities, while a plugin-driven architecture provides access to more than 1,000 community extensions for productivity, group operations, content workflows, and external integrations. AstrBot supports OpenAI, Google, Anthropic, and OpenAI-compatible providers with flexible model switching, as well as text generation, vision, speech-to-text, text-to-speech, and embeddings. Its built-in knowledge base supports PDF, DOCX, and Markdown parsing, hybrid dense and BM25 retrieval, and references to multiple knowledge bases in a single conversation. -
41
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 -
42
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 -
43
kgateway
Cloud Native Computing Foundation
kgateway is a Kubernetes-native gateway platform designed to manage microservices and AI agent traffic at scale. It acts as a unified control plane for API gateways, AI gateways, inference routing, and agent-to-agent communication. Built on Envoy and open standards, kgateway implements the Kubernetes Gateway API for modern cloud-native environments. The platform enables centralized authentication, authorization, rate limiting, and traffic management. Kgateway also secures LLM consumption by controlling access to models, tools, and agents. It supports intelligent routing for AI inference workloads running in Kubernetes. Trusted by enterprises worldwide, kgateway delivers scalable, secure, and flexible connectivity across any cloud. -
44
WebAssembly
WebAssembly
WebAssembly (abbreviated Wasm) is a binary instruction format for a stack-based virtual machine. Wasm is designed as a portable compilation target for programming languages, enabling deployment on the web for client and server applications. The Wasm stack machine is designed to be encoded in a size- and load-time-efficient binary format. WebAssembly aims to execute at native speed by taking advantage of common hardware capabilities available on a wide range of platforms. WebAssembly describes a memory-safe, sandboxed execution environment that may even be implemented inside existing JavaScript virtual machines. When embedded in the web, WebAssembly will enforce the same-origin and permissions security policies of the browser. WebAssembly is designed to be pretty-printed in a textual format for debugging, testing, experimenting, optimizing, learning, teaching, and writing programs by hand. The textual format will be used when viewing the source of Wasm modules on the web.Starting Price: Free -
45
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. -
46
Data Sandbox
Data Republic
No matter how impressive your internal systems are, there are numerous benefits to be realized when utilizing outside expertise. The Data Sandbox allows outside data experts to work on your data without compromising security. With the world's best talent performing data analytics or building AI algorithms, you can crowdsource innovation and leverage cognitive diversity. Accelerate your collaboration with innovators including startups, scaleups and big tech. With the Data Sandbox, you can securely evaluate the potential value of these technology vendors’ apps, AI and ML algorithms using real data. Test and evaluate multiple vendors simultaneously before deploying into production environments. University researchers can offer immense value when working on real data. Forge research partnerships with prestigious institutions fueled by your data. The Data Sandbox eliminates concerns surrounding data security, so research and development can be carried out quickly and seamlessly. -
47
E2B
E2B
E2B is an open source runtime designed to securely execute AI-generated code within isolated cloud sandboxes. It enables developers to integrate code interpretation capabilities into their AI applications and agents, facilitating the execution of dynamic code snippets in a controlled environment. The platform supports multiple programming languages, including Python and JavaScript, and offers SDKs for seamless integration. E2B utilizes Firecracker microVMs to ensure robust security and isolation for code execution. Developers can deploy E2B within their own infrastructure or utilize the provided cloud service. The platform is designed to be LLM-agnostic, allowing compatibility with various large language models such as OpenAI, Llama, Anthropic, and Mistral. E2B's features include rapid sandbox initialization, customizable execution environments, and support for long-running sessions up to 24 hours.Starting Price: Free -
48
Quali
Quali
Quali’s CloudShell platform is a cloud automation and infrastructure orchestration product that lets organizations deliver fully functional sandboxes and complex IT environments across on-premises, hybrid, and public cloud infrastructure by eliminating manual provisioning and resource conflicts and boosting productivity with self-service access and reusable components. CloudShell enables users to model infrastructure and application environments using a drag-and-drop blueprint editor to define resources from inventory, set up network connectivity, and automate deployment and teardown workflows, greatly reducing configuration time and standardizing environment delivery. It offers a web-based self-service portal and catalog with inventory management, reservation and scheduling, conflict resolution, role-based access control with directory and SSO integration, and distributed execution engines for high-performance parallel sandbox deployment.Starting Price: Free -
49
Solid
Codapt lnc
Solid is the operating system for always-on AI agents. This AI agent infrastructure runs agent software, allocates resources, connects agents to external systems, and applies shared controls. It provides a persistent runtime, memory, approved computers, identities, accounts, credentials, phone numbers, system access, and controlled spending so work can continue after a chat closes. Agents can use APIs, MCP, code, browsers, desktops, phones, and software interfaces, subject to customer permissions and system policies. Solid can build and test a missing integration, app, API, dashboard, or report needed to finish the job. Customer-set budgets and approvals govern provisioning and purchases. Solid provides agent orchestration plus visibility into available activity, code, resource state, costs, logs, and exceptions, with policies routing sensitive, unclear, or out-of-policy decisions to people. Builders can embed a Solid-powered agent through its API.Starting Price: $40/month/user -
50
Tines 3B
Tines
Tines 3B is an AI-native intelligent workflow platform that provides one environment to deliver AI agents, apps, and automation faster, safely, and at scale. Teams can start with a natural-language prompt, describe a process in their own words, brainstorm with a connected LLM, or build workflows directly in code with Git integration and native branching. It proposes tests as users build, generates dummy data when needed, and asks before using live data or applications. Dedicated Spaces combine the right connectors, skills, and permissions, while LLM Skills help standardize how builds happen across teams. Every workflow step executes in an isolated sandbox, and credentials are injected at runtime through a transparent proxy so secrets are never exposed to builders, AI, or stored code. Workflows can run self-hosted, on-premises, or in hybrid environments.Starting Price: Free
