Key Takeaways
- NamoWork aggregates over 500 specialist AI agents covering roles from competitor analysis to content creation, running on top of mainstream agent frameworks including Claude Code and supporting multi-agent setups with cloud execution without requiring users to manage their own infrastructure.
- Relevance AI raised a $24 million Series B led by Bessemer Venture Partners in May 2025 and offers a no-code platform for building and deploying autonomous agents, with a Free tier (200 actions/month), Pro at $19/month, Team at $234/month, and Enterprise on request. Its customers include Roku, Autodesk, and SafetyCulture.
- AgentSky launched on Product Hunt in August 2026 and ranked number one on its launch day. It starts at $3/month per agent plus usage, with parked agents free. It supports Claude Code, Codex, Hermes, and OpenClaw harnesses and provides multi-channel access through WhatsApp, iMessage, Telegram, Slack, Discord, web, A2A protocol, and CLI.
- Relevance AI supports deployments of 35+ interconnected agents running simultaneously, with customers reporting outcomes including $7 million in pipeline generation and three times increases in meeting volume from sales agent deployments.
- AgentSky’s clone-to-cloud feature lets users migrate a locally running Claude Code or Codex agent to the cloud in one command, preserving all instructions and MCP server configurations while leaving secrets and API keys on the local machine.
- AgentSky’s pricing model is pay-as-you-run with no flat seat fee: agents cost nothing when parked and only accumulate charges when actively processing work. Users who hold a Claude Pro/Max or ChatGPT subscription can connect it and run eligible agents at zero additional model cost.
- Relevance AI’s September 2025 pricing update split charges into Actions (what an agent does) and Vendor Credits (model costs), with paid plans allowing users to bring their own API keys to bypass Vendor Credits entirely, making model cost predictable and controllable at scale.
Autonomous AI agents have moved from research concept to practical tool faster than almost any other AI category. The operational challenge in 2025 and 2026 is no longer whether agents work but which platform delivers them in a way that fits how a specific team operates. A non-technical sales operations team needs something different from a developer who wants cloud-hosted agents reachable on Slack. A business that wants to spin up 500 specialist agents for research workflows has different requirements than one that wants to clone a single coding agent from a laptop to the cloud.
NamoWork, Relevance AI, and AgentSky each answer a distinct version of the autonomous agent question. NamoWork is an agent aggregator: a marketplace of 500+ pre-built specialist agents that run on top of Claude Code and similar frameworks. Relevance AI is a no-code platform for business teams that want to build, deploy, and orchestrate their own agents without writing code. AgentSky is a managed infrastructure layer for developers and technical teams who want long-horizon, always-on agents accessible from any channel with no ops overhead. Understanding which category fits the job is the fastest path to the right choice.
Quick Comparison: NamoWork vs Relevance AI vs AgentSky
| Feature | NamoWork | Relevance AI | AgentSky |
|---|---|---|---|
| Primary user | Teams wanting pre-built specialist agents | Business teams (no-code) | Developers and technical teams |
| Agent source | Marketplace (500+ pre-built) | Build your own or use templates | Choose any harness and model |
| Starting price | Contact for pricing | Free (200 actions/mo) | $3/mo per agent + usage |
| Harness support | Claude Code, mainstream frameworks | Relevance AI native | Claude Code, Codex, Hermes, OpenClaw |
| Multi-agent support | Yes (multi-agent setups) | Yes (35+ interconnected) | Yes (fleet management) |
| Channel access | Cloud execution | Web, integrations | WhatsApp, Telegram, Slack, iMessage, web, CLI, A2A |
| Best for | Specialist task coverage at scale | No-code business automation | Long-horizon developer agents |
What Is NamoWork?
NamoWork is an autonomous AI agent platform that aggregates more than 500 specialist agents covering a wide range of business roles, from competitor analysis and market research to content creation and workflow automation. Rather than requiring teams to build agents from scratch, NamoWork provides a library of ready-to-run agents that execute on top of mainstream agent frameworks, including Claude Code. It supports multi-agent setups, allowing multiple specialist agents to collaborate on a task or pipeline in the cloud without the user managing the underlying infrastructure.
The platform is positioned for teams that need broad task coverage across many domains without the time investment of building and fine-tuning agents for each role. A team that wants an agent for competitor monitoring, a separate one for content brief generation, and another for outreach research can access all three from the NamoWork library rather than sourcing, configuring, and hosting them separately. This aggregator model differentiates NamoWork from Relevance AI, which requires teams to build their own agents, and AgentSky, which provides the cloud infrastructure for running agents but not the agents themselves.
What Is Relevance AI?
Relevance AI is a no-code platform for building and deploying autonomous AI agents for business workflows. Based in Sydney with a San Francisco office, it raised a $24 million Series B led by Bessemer Venture Partners in May 2025, with Insight Partners, King River Capital, and Peak XV also participating. Its core product is a visual agent builder that lets non-technical users create agents for sales, marketing, customer support, and operations without writing code. Teams can choose from pre-built agent templates or build custom agents through the visual interface, and can deploy complex setups with 35 or more interconnected agents working in parallel.
Relevance AI’s enterprise customers include Roku, Autodesk, and SafetyCulture, with reported outcomes including $7 million in pipeline generation and three times increases in meeting volume from sales-focused agent deployments. The platform updated its pricing model in September 2025 to separate Actions (what agents do) from Vendor Credits (model costs), with paid plans allowing customers to bring their own API keys and eliminate the Vendor Credits cost entirely. The Free tier includes 200 Actions per month. Pro is $19 per month billed annually. Team is $234 per month billed annually. Enterprise is priced on request. Relevance AI’s strength is making enterprise-grade agent automation accessible to subject-matter experts rather than requiring dedicated AI engineers.
What Is AgentSky?
AgentSky is a managed agent-as-a-service platform built for developers and technical teams who want to run long-horizon, always-on AI agents in the cloud without managing the underlying infrastructure. It launched in 2026 and reached number one on Product Hunt on August 3, 2026, with more than 10,000 agent sessions supported in production across its launch applications. The platform supports four agent harnesses: Claude Code, Codex, Hermes, and OpenClaw. Users pick a harness, pick a model, and launch an agent in one click. The agent runs in a managed sandbox with full conversation history, state snapshots, backup, and restore, and can be reached from WhatsApp, iMessage, Telegram, Slack, Discord, web chat, A2A protocol, and CLI without the context resetting between channels.
AgentSky starts at $3 per month per agent plus usage, with parked agents costing nothing. Users who hold a Claude Pro/Max or ChatGPT subscription can connect it and run eligible agents at zero additional model cost. The clone-to-cloud feature migrates a locally running Claude Code or Codex agent to the cloud in one command, copying instructions and MCP server configurations while leaving API keys and secrets on the local machine. AgentSky is designed for developers who run coding agents, research agents, or virtual teammates and want them always available without keeping a local machine running or rebuilding the agent context on each session restart.
NamoWork vs Relevance AI vs AgentSky: Feature-by-Feature Breakdown
Agent Source and Customization
NamoWork’s 500+ specialist agent library is its defining advantage for teams that want immediate coverage across many business domains without building from scratch. The tradeoff is that pre-built agents may not perfectly match specific workflows and may offer less customization depth than a custom-built agent. Relevance AI sits at the opposite end on this axis: every agent is built by the user through its visual interface, which means maximum customization but requires more setup time. AgentSky does not provide pre-built agents; it is a hosting and management layer for agents the user selects or builds. The user chooses a harness and model and is responsible for configuring the agent’s instructions and capabilities. Teams that need agents up and running immediately without configuration time will find NamoWork the fastest path; teams that need agents precisely tailored to their workflow will find Relevance AI or AgentSky more appropriate.
No-Code vs Developer Access
Relevance AI is the only platform of the three that is genuinely no-code and designed for non-technical business users. A sales operations manager can build and deploy a lead research agent in Relevance AI without writing any code or understanding how LLM APIs work. NamoWork’s pre-built library also reduces the technical barrier, though configuring multi-agent setups and connecting to specific data sources may require technical support. AgentSky is explicitly developer-first: everything it does through the UI is also available as a CLI command and REST API, and the platform is designed around the assumption that the user is comfortable with terminal commands and agent frameworks. For business teams without engineering support, Relevance AI is the most accessible entry point by a clear margin.
Multi-Channel Access
AgentSky’s multi-channel architecture is its strongest differentiator. The same agent session is accessible from WhatsApp, iMessage, Telegram, Slack, Discord, web, A2A protocol, and CLI, with full history maintained across all channels. A developer who sends a message to their coding agent from Slack in the morning can continue the same session from a terminal in the afternoon without rebuilding context. Relevance AI provides web-based access and integrations through its platform but does not offer the same native multi-channel messaging coverage. NamoWork focuses on cloud execution and workflow automation rather than conversational channel access. For teams that want agents reachable through whatever communication tool they happen to be using at the moment, AgentSky’s channel coverage is not matched by either competitor.
Pricing and Cost Structure
Relevance AI offers the lowest barrier to entry with a free tier that includes 200 Actions per month. The Pro plan at $19 per month covers solo users and small teams, and the Team plan at $234 per month covers multi-seat deployments. The September 2025 pricing update that separated Actions from Vendor Credits, combined with the option to bring your own API keys, makes Relevance AI’s cost structure transparent and controllable at scale. AgentSky at $3 per month per agent plus usage is extremely low-cost for individual or small-fleet deployments, particularly for users who already have a Claude Pro/Max subscription and can run eligible agents at zero additional model cost. Parked agents cost nothing, making it practical to maintain many agents without paying for them until they are needed. NamoWork does not publish public pricing.
Long-Horizon and Persistent Agent Support
AgentSky is specifically engineered for long-horizon agents that run continuously over days, weeks, or months. Its managed recovery system uses snapshots and backups to restore agent state after faults or restarts without losing conversation history or task context. The infinitely long continuous history means agents remember prior instructions, decisions, and outputs across extended work. Relevance AI agents can run autonomously on scheduled triggers and multi-step workflows, but the platform is more oriented toward task-based automation than continuous long-horizon sessions. NamoWork supports cloud execution and multi-agent collaboration but focuses on specialist task completion rather than persistent always-on agent sessions. For developers building agents that need to operate continuously across weeks of work without human restart intervention, AgentSky’s durability architecture is purpose-built for that use case.
Who Should Use Which?
NamoWork is the right choice for businesses that want immediate access to a wide range of specialist agents without allocating engineering time to build them. Companies that need competitive intelligence, content workflows, research pipelines, and outreach agents running quickly will find the 500+ agent library reduces the time from decision to operational agent dramatically. It is particularly well-suited for marketing and operations teams that need many different types of agents rather than one deeply customized one.
Relevance AI is the right choice for business teams that need custom agents built and iterated by non-technical staff. Sales, customer support, and operations teams that have specific workflows and business logic that off-the-shelf agents do not cover will benefit from Relevance AI’s no-code builder. Its enterprise-grade multi-agent orchestration (35+ agents running in parallel) makes it viable for large-scale deployment, and the $24M Series B and enterprise customer base indicate institutional investment in the platform’s reliability. The free tier is also the only zero-cost entry point among the three for teams that want to test agent automation before committing.
AgentSky is the right choice for developers and technical teams who already run Claude Code, Codex, or similar agent frameworks and want them in the cloud without managing infrastructure. The clone-to-cloud feature, multi-channel access, and pay-per-use pricing with free parked agents make it the lowest-friction upgrade path for developers who currently run agents locally. For teams building virtual teammates that should be reachable on WhatsApp and Slack without separate integrations or server maintenance, AgentSky removes the infrastructure burden entirely.
Our Verdict
The right platform depends entirely on who is deploying agents and for what purpose. For non-technical business teams, Relevance AI’s no-code builder, transparent pricing, free tier, and enterprise customer validation make it the most accessible and proven choice in this group. For developers wanting the fastest path from local agent to cloud agent with multi-channel presence, AgentSky’s infrastructure design is purpose-built for that workflow at a price that makes it trivial to try. NamoWork’s differentiation is scope: 500+ pre-built specialist agents covering the widest range of business domains of the three, making it the strongest fit for teams that need many types of agents quickly rather than one deeply customized platform. These tools are less in direct competition than they appear; they serve meaningfully different points in the autonomous agent adoption journey.
Frequently Asked Questions
What is the difference between NamoWork, Relevance AI, and AgentSky?
NamoWork is an agent marketplace that aggregates 500+ pre-built specialist agents running on frameworks like Claude Code. Relevance AI is a no-code platform for building and deploying custom autonomous agents for business workflows without writing code. AgentSky is a managed cloud infrastructure layer for developers who want to run long-horizon agents with multi-channel access and no ops overhead. Each serves a different type of user and agent use case.
Is Relevance AI free?
Yes. Relevance AI offers a free tier that includes 200 Actions per month, which is sufficient for individual testing and small-scale agent experiments. The Pro plan costs $19 per month billed annually and covers more actions and features. The Team plan at $234 per month billed annually covers multi-seat teams and higher action volumes. Enterprise pricing is available on request for large deployments.
What agent frameworks does AgentSky support?
AgentSky currently supports four agent harnesses: Claude Code, Codex, Hermes, and OpenClaw. Within each harness, users can choose from a range of underlying models. The platform allows users to switch harnesses or models mid-task without losing conversation history, and a clone-to-cloud feature migrates locally configured Claude Code or Codex agents to the cloud in one command.
Can Relevance AI handle multi-agent workflows?
Yes. Relevance AI supports deployments of 35 or more interconnected agents working simultaneously. This multi-agent orchestration capability allows teams to build complex workflows where specialist agents hand off tasks to each other, with the platform managing coordination and data flow between agents. Verified enterprise customers have used this capability for large-scale sales automation and customer support pipelines.
How does AgentSky pricing work?
AgentSky charges $3 per month per agent plus usage-based charges for when agents are actively working. Parked agents cost nothing, so you can maintain a fleet of agents without paying for idle capacity. Users who hold a Claude Pro/Max or ChatGPT subscription can connect it to AgentSky and run eligible agents at zero additional model usage cost. A $3 credit is granted on signup with no credit card required.
Who uses Relevance AI?
Relevance AI’s enterprise customers include Roku, Autodesk, and SafetyCulture. The platform serves mid-market to enterprise companies, with verified outcomes including $7 million in pipeline generation and three times increases in meeting volume from sales agent deployments. The platform is used primarily by sales, marketing, customer support, and operations teams who want to automate repeatable workflows through AI agents without requiring engineering resources to build and maintain them.
What makes AgentSky different from running a Claude Code agent locally?
A locally running Claude Code agent depends on your machine being on, requires you to manage updates and restarts, forgets context if the process crashes, and is only accessible while you are at your computer. AgentSky runs the same agent in a managed cloud sandbox with full history persistence, automatic crash recovery via snapshots and backups, and multi-channel access through WhatsApp, iMessage, Telegram, Slack, Discord, and CLI. Parked agents stay ready without consuming compute resources, and the same agent can be reached from any device or channel without losing context.
