13+ Best AI Agents in 2026
Autonomous AI agents that complete multi-step tasks for you.
Looking for the best ai agent platform in 2026? This page ranks the top 13 ai agents, including free options, freemium plans and premium tools — all independently reviewed by the ToolVerse editorial team. Use the comparison table below to quickly find the best fit for your workflow, budget and skill level.
Top 5 AI Agents compared
| # | Tool | Pricing | Rating |
|---|---|---|---|
| 1 | Lindy Prebuilt 'AI employees' for everyday business operations | $49.99/mo | 4.5(26,300) |
| 2 | AgentGPT Browser-based autonomous agents — free hosted demo or self-hosted | $40/mo | 3.9(21,600) |
| 3 | CrewAI Open-source multi-agent orchestration, free framework plus a managed cloud | Freemium | 4.4(19,200) |
| 4 | Manus General AI agent that completes real tasks end to end | $19/mo | 4.4(18,700) |
| 5 | Devin Autonomous AI software engineer — now 96% cheaper than its original $500/month | $20/mo | 4.1(16,400) |
All AI Agents
Lindy
Prebuilt 'AI employees' for everyday business operations
Lindy's pitch is the fastest path from zero to a working AI agent handling real business operations: prebuilt "AI employees" for common tasks — email triage, meeting scheduling, CRM updates, customer support — that you can stand up in minutes via a drag-and-drop builder, rather than assembling an agent from scratch. It includes 4,000+ integrations and voice-agent capabilities alongside its core workflow automation, positioning it as more turnkey than Relevance AI's build-your-own-workforce approach. Its credit-based pricing meters every action, with cost scaling by complexity: a simple step costs roughly 1 credit, while email parsing or multi-step workflows burn 5-10 or more credits per run — worth understanding before assuming a flat monthly rate covers unlimited usage. Independent comparisons consistently place Lindy as offering better value than Zapier per dollar of task automation, largely because its pricing tiers include a meaningfully larger effective task allowance per plan level. With a free tier (limited agents and tasks) and paid plans starting around $50/month, Lindy sits above Relevance AI's $19/month entry point but below CrewAI's technical, developer-oriented positioning. It's the strongest fit specifically for non-technical teams wanting fast, ready-made automation of everyday operational tasks — email, scheduling, CRM hygiene — without the setup overhead of a code-first framework or the build-your-own-agent-team complexity of Relevance AI.
AgentGPT
Browser-based autonomous agents — free hosted demo or self-hosted
AgentGPT was among the earliest browser-accessible autonomous agent tools, letting you set a goal in plain language and watch an AI agent break it down into sub-tasks and attempt to complete them with minimal ongoing supervision — no local installation required for the hosted demo version. It's built on the same autonomous-agent philosophy as tools like AutoGPT, but with a more accessible, browser-first entry point that made it a popular way for non-developers to first experience agentic AI. Its pricing structure is genuinely two-tiered in a way worth understanding clearly: the hosted demo offers limited free usage with no setup, while a separate self-hosted, open-source version follows a bring-your-own-infrastructure cost model — you pay only for VPS hosting (roughly $5-20/month) plus your own LLM API key usage, with no platform subscription fee at all for the self-hosted path. Managed/paid tiers on the hosted platform run around $40/month for higher usage limits and premium features. The honest limitation shared across early autonomous-agent tools like AgentGPT: they tend to consume more API tokens than more targeted platforms, since the autonomous, exploratory approach generates more LLM calls per completed task than a narrowly-scoped agent would. It remains a reasonable low-commitment way to experiment with autonomous agent behavior — set a goal, watch it work — before committing to a more structured, business-operations-focused platform like Lindy or a developer framework like CrewAI for production use.
CrewAI
Open-source multi-agent orchestration, free framework plus a managed cloud
CrewAI is both a free, MIT-licensed open-source Python framework for orchestrating multiple collaborating AI agents and a managed hosted platform (CrewAI AMP) for teams that don't want to run it themselves — a dual identity that's core to understanding its actual cost. The open-source framework, with over 50,000 GitHub stars and a reported 2 billion agent executions in the trailing 12 months as of 2026, lets developers build "crews" of specialized agents (a researcher, a writer, a reviewer) that divide and coordinate complex multi-step tasks, and it's used by a majority of Fortune 500 companies according to the company's own disclosures. CrewAI's public cloud pricing has genuinely changed multiple times and is worth getting straight: a $25/month Professional tier (100 executions/month) existed from its October 2025 AMP launch through spring 2026, then was removed entirely. As of mid-2026, the public cloud pricing is two tiers only — Basic, free with 50 workflow executions/month and full core platform access (not a crippled trial), and custom-quoted Enterprise for organizations needing compliance certifications and dedicated support (estimated $60,000-$120,000 annually in third-party analysis). If you're reading an older article citing a $99/month or $25/month self-serve mid-tier, that pricing has been discontinued. The cost that catches most teams off guard isn't the platform fee at all — it's LLM API usage. Because CrewAI counts one "execution" as a full crew run regardless of how many agents are involved or how many tokens they consume internally, a crew with 10 agents making extensive LLM calls costs the same one execution as a single-agent crew, but the underlying API bill can be dramatically higher. Production costs for token-hungry multi-agent workflows commonly run $1.50-12/hour depending on task complexity — budget for that separately from whatever CrewAI's own platform tier costs.
Manus
TrendingGeneral AI agent that completes real tasks end to end
Manus is a general-purpose autonomous AI agent that goes beyond chat: give it an objective and it plans, browses the web, writes and runs code, manipulates files and delivers a finished artifact — a research report, a spreadsheet, a slide deck or a deployed web page. Each task runs inside its own cloud sandbox with a live view of what the agent is doing, so you can watch the browser tabs, terminal commands and files it creates in real time and step in when needed. Tasks continue running even after you close the tab, and Manus notifies you when the deliverable is ready. The platform is credit-based: simple tasks cost a few credits, long autonomous research runs cost more. Teams use Manus for competitive research, lead list building, data cleanup, market analysis and prototype generation — work that used to take an analyst a full day.
Devin
Autonomous AI software engineer — now 96% cheaper than its original $500/month
Devin, built by Cognition AI, was introduced in March 2024 as "the world's first AI software engineer" — an agent that works more like a remote contractor than an in-editor assistant: hand it a well-scoped engineering ticket, and it plans the approach, works inside its own sandboxed cloud environment with shell, browser and editor access, writes and tests code, and opens a pull request for human review, all with minimal step-by-step supervision. That's the core distinction from tools like Cursor or Claude Code, which sit inside your editor and wait for you to drive each interactive step. The headline change worth knowing before evaluating Devin in 2026: Cognition slashed pricing by 96% in late 2025. The original $500/month plan — which became genuinely famous as a talking point in every competitor's marketing — still exists as the Team tier (250 Agent Compute Units included, additional ACUs at $2.00 each), but a new self-serve Core tier now starts at just $20/month plus pay-as-you-go ACUs at $2.25 each. One ACU represents roughly 15 minutes of active autonomous work, so an hour of Devin running on Core costs around $9 — meaningfully more accessible than the original enterprise-only positioning suggested. Cognition's own July 2026 benchmarks (vendor-reported, not independently verified) put Devin's current SWE-1.7 model at 77.8% on SWE-bench Multilingual and 81.5% on Terminal-Bench 2.1, and the company raised $1 billion at a $25 billion valuation in May 2026 with annualized revenue near $492 million — rapid growth that followed the price restructure. Devin fits well-scoped, repetitive engineering work best: large migrations, framework upgrades, CI failure triage, documentation for legacy code — tasks with enough time and ticket clarity to justify autonomous, unsupervised execution. For interactive, moment-to-moment coding, reviewers consistently note Cursor or Claude Code remain faster and cheaper.
Relevance AI
Build a coordinated 'AI workforce' of role-based agents
Relevance AI's core concept is an "AI workforce": rather than one general-purpose assistant handling every request, you build narrowly-scoped agents with distinct roles — a research agent, an SDR agent, an ops agent — that work together as a coordinated team, each using only the tools and information assigned to its specific job. That multi-agent orchestration approach makes it particularly strong for go-to-market teams building sales and revenue-operations workflows where several specialized tasks need to hand off to each other. A significant pricing restructure took effect in September 2025 and remains the current model: costs split into Actions (what an agent actually does — API calls, tool use) and Vendor Credits (the underlying LLM model costs), with no markup on Vendor Credits and the option on paid plans to bring your own API keys to bypass them entirely. The free tier includes 200 Actions/month plus $2 in bonus vendor credits — useful for initial testing, but genuinely difficult to forecast real monthly spend from, since usage compounds quickly once agents run continuously or handle complex, multi-step tasks. Paid plans run from roughly $19/month for individuals up to about $199/month for teams, positioning it as more affordable at the entry level than Lindy (~$50/month) but with real usage-based cost uncertainty that Lindy's flatter-feeling tiers avoid. It's best suited to teams that want a genuine multi-agent "workforce" model for sales or ops specifically, and are comfortable actively monitoring Actions and Vendor Credit consumption rather than a fully predictable flat bill.
Genspark
All-in-one AI agent for search, docs, sheets and calls
Genspark is an agentic AI workspace built around Super Agent — a planner that picks the right model and tool for each step of a job. Ask it a question and it produces a Sparkpage: a generated, cited research page rather than a list of blue links. Beyond search, Genspark bundles AI Slides, AI Sheets, AI Docs, an AI Browser and an AI phone-call agent that can ring restaurants or vendors on your behalf. That combination makes it one of the broadest consumer agent platforms currently shipping, and a practical alternative to stitching together five separate subscriptions. Credits are shared across every tool, so a single plan covers research, document creation and automation. Genspark is popular with solo founders, consultants and small marketing teams that need a generalist assistant rather than a specialised one.
OpenClaw
TrendingThe open-source AI agent framework developers actually run their own bots on
OpenClaw started as a viral, open-source desktop AI agent in early 2026 and has grown into one of the most-referenced names in the personal-agent space — investor Sheel Mohnot's line describing Instinct as "OpenClaw for normal people" only makes sense because OpenClaw itself is so widely known among developers. Its 2.0 release, shipped September 3, 2026 after 16,977 community pull requests, added native computer use through Cua's driver, cloud fleets for running agents remotely, a gateway component, and platform support spanning Mac, Linux, Windows, iPhone, iPad, Android, Wear OS and Docker. Being open-source and self-hosted is both its appeal and its risk. Nothing gates what an OpenClaw agent can do on your machine once you grant it access, which is exactly the freedom power users want and exactly what has led to real, reported incidents of OpenClaw agents deleting files on a user's Mac — incidents that get cited industry-wide as a caution about handing any agent unattended computer access, OpenClaw included. Partly for that reason, many early OpenClaw users have since moved their day-to-day work to more guardrailed mobile options like Codex Mobile and Claude Mobile, while keeping OpenClaw specifically for fully custom, self-hosted setups where they want complete control. There's no subscription: OpenClaw is free, and your only ongoing cost is your own compute plus whichever model API keys you connect it to.
Browser Use
TrendingThe open-source library with 97K GitHub stars that lets any AI agent control a real browser
Browser Use solves a specific technical problem that sat unsolved for years: giving an AI agent reliable, general-purpose control over a web browser so it can click, type, scroll and navigate like a person, without a developer hand-writing custom scraping logic for every website. It's structured around four clean primitives — act, extract, observe, agent — that make agent behavior readable and testable rather than an opaque black box, and it's fully open-source under MIT license with no vendor lock-in. That openness is a big part of why it's become the reference framework in this space: 97,000+ GitHub stars and an active community means it runs locally with any Chromium browser out of the box, with built-in session recording and replay for debugging when an agent fails partway through a task. Pairing it with a managed cloud-browser runner like Browserbase is the common production setup for teams that don't want to manage their own browser infrastructure. Compared to [OpenClaw](/tools/openclaw) in our [AI Agents category](/category/ai-agents), Browser Use is narrower and more composable — a library you build an agent on top of, rather than a ready-made personal assistant. There's no managed dashboard or published pricing because the core framework itself is free; you own the agent logic entirely, which means more setup work but zero platform lock-in.
Grok Bot
TrendingAlways-on Grok agents in a sandbox - free first month, then from $149/mo with Cursor Ultra
Grok Bot packages Grok as persistent agents that keep working in their own sandboxed computer, not as a single chat tab you must leave open. Launch was August 13, 2026 from xAI with Cursor. Pricing is the main search question: the first month of beta access is free, then access is included with SuperGrok Heavy or Cursor Ultra at about $149/month, which is cheaper than paying the standalone Grok Ultra path at about $249/month for similar depth. Confirm current bundles on x.ai and Cursor before you buy. Each bot runs in isolation with no model picker. Under the hood it is Grok (Grok 4.6 at launch, Grok 4.7 by late September 2026). Bots can talk to other bots in a way you can watch but not rewrite every message, and a bot can spin up helpers with their own identities for larger jobs. Security reuses Cursor's connector model: API keys stay hidden from the bots, and payments or account logins hand control back to a human instead of finishing unattended. Late September 2026 adds included Tesla and 1Password connections in beta. Platform support is still narrow: macOS and iOS only. If you want a phone-and-text personal agent with no IDE bundle, compare [Instinct](/tools/instinct-ai) and [Meta Muse](/tools/meta-muse). If you mainly want chat Grok without agent sandboxes, see the main [Grok](/tools/grok) listing.
Meta Muse
TrendingMeta's 24/7 personal AI agent that books, buys, and negotiates on your behalf
Muse is Meta's first standalone personal AI agent, launched September 8, 2026 under chief AI officer Alexandr Wang and pitched by Mark Zuckerberg as a step toward "personal superintelligence." Unlike a chatbot that answers and stops, Muse takes a goal, builds a plan, and keeps working after you close the app — coming back only when it needs your approval for something sensitive. It runs on Muse Spark 1.3 inside a dedicated Muse Secure VM, a private cloud computer with its own visible browser. A separate agent called Sentinel acts as the sole permission authority for every outbound request and connected-service action; Muse itself never sees your real login tokens, only swappable surrogates. It connects to Gmail, Calendar, WhatsApp, Instagram, Facebook Marketplace, health and fitness apps, and smart-home tools, and pays through a dedicated Stripe Link integration that issues single-use virtual cards rather than handing over a real credit card. The free tier includes 100 million tokens per week, which Meta says covers most people. Two paid tiers exist for power users at $20/month and $100/month, covering the extra compute. Meta has been unusually candid about the risk: its own security write-up states plainly that "prompt injection remains an open problem in the industry" and that Muse will sometimes get things wrong, backed by a bug bounty of up to $300,000 (with $130,000 specifically for prompt-injection exploits). A Confidential VM project, built with Signal founder Moxie Marlinspike, is coming later this year so that even Meta itself cannot access what Muse sees. Rollout is currently US-only across iOS, Android and the web, with WhatsApp access live and AI-glasses support planned.
Stagehand
TrendingThe free browser automation framework built by Browserbase, aimed at reliability over raw autonomy
Stagehand, built by the team behind Browserbase, takes a slightly different philosophy from a fully autonomous framework like [Browser Use](/tools/browser-use) in our [AI Agents category](/category/ai-agents): it's designed for developers who want AI-assisted browser automation that's genuinely reliable in production, blending deterministic, hand-written automation steps with AI-driven steps only where flexibility is actually needed — rather than handing an agent full autonomy over every action. That hybrid approach matters in practice: pure AI-driven browser agents can be unpredictable on complex, multi-step workflows, while Stagehand lets you lock down the parts of a flow that must work every time (logging in, navigating to a specific page) and use AI only for the genuinely variable parts (finding and clicking the right element when a site's layout changes). It's entirely free and open-source, consistent with Browserbase's broader developer-tooling approach. It pairs naturally with Browserbase's managed cloud browser infrastructure for teams that don't want to run their own browser instances, though it also works standalone with a local Chromium install. For teams that got burned by unpredictable full-autonomy agents in production, Stagehand's more controlled, deterministic-plus-AI hybrid is a genuinely different trade-off worth evaluating against a pure-agent framework.
Instinct
TrendingInvite-only personal AI agent you text or call - free in beta, no new app
Instinct is a personal AI agent with no separate app to learn: you text or call it over iMessage, WhatsApp or a normal phone line, and it uses a phone and a computer the way a person would. Most people landing on this page want the same answers first: is it free, how do you get in, and what does it actually cost later? Right now it remains invite-only and free while the team scales compute. There is no public paid price sheet yet; the product is still in private beta, and future paid tiers are expected but not published. It is built by Spear Street Technology, Inc., a San Francisco company registered in April 2026 by founder and CEO Noah Shinn, a former research scientist at Sierra. Instinct entered private beta in February 2026 and grew mainly through invites. Early use cases people report include rebooking travel, canceling subscriptions, negotiating bills, cleaning up dropped email threads, and Concierge calls where the agent phones a business on your behalf. Newer pieces include a Trusted Person network so your agent can coordinate with someone else's, and a dedicated email address so it can sign up for services without filling your inbox. The company raised a $250 million Series B in August 2026 co-led by Index Ventures and Benchmark, at a $2.5 billion valuation, after an earlier $50 million round. That funding story explains the hype; it does not change the access model. You still need an invite or the waitlist. Privacy is a real trade-off: current terms allow training on user data, which matters because the agent may touch messages, email and device actions. If you are comparing personal agents rather than developer agent frameworks, see also [Meta Muse](/tools/meta-muse) and [Grok Bot](/tools/grok-bot) on ToolVerse.
Best free ai agents
Lindy
Prebuilt 'AI employees' for everyday business operations
Lindy's pitch is the fastest path from zero to a working AI agent handling real business operations: prebuilt "AI employees" for common tasks — email triage, meeting scheduling, CRM updates, customer support — that you can stand up in minutes via a drag-and-drop builder, rather than assembling an agent from scratch. It includes 4,000+ integrations and voice-agent capabilities alongside its core workflow automation, positioning it as more turnkey than Relevance AI's build-your-own-workforce approach. Its credit-based pricing meters every action, with cost scaling by complexity: a simple step costs roughly 1 credit, while email parsing or multi-step workflows burn 5-10 or more credits per run — worth understanding before assuming a flat monthly rate covers unlimited usage. Independent comparisons consistently place Lindy as offering better value than Zapier per dollar of task automation, largely because its pricing tiers include a meaningfully larger effective task allowance per plan level. With a free tier (limited agents and tasks) and paid plans starting around $50/month, Lindy sits above Relevance AI's $19/month entry point but below CrewAI's technical, developer-oriented positioning. It's the strongest fit specifically for non-technical teams wanting fast, ready-made automation of everyday operational tasks — email, scheduling, CRM hygiene — without the setup overhead of a code-first framework or the build-your-own-agent-team complexity of Relevance AI.
AgentGPT
Browser-based autonomous agents — free hosted demo or self-hosted
AgentGPT was among the earliest browser-accessible autonomous agent tools, letting you set a goal in plain language and watch an AI agent break it down into sub-tasks and attempt to complete them with minimal ongoing supervision — no local installation required for the hosted demo version. It's built on the same autonomous-agent philosophy as tools like AutoGPT, but with a more accessible, browser-first entry point that made it a popular way for non-developers to first experience agentic AI. Its pricing structure is genuinely two-tiered in a way worth understanding clearly: the hosted demo offers limited free usage with no setup, while a separate self-hosted, open-source version follows a bring-your-own-infrastructure cost model — you pay only for VPS hosting (roughly $5-20/month) plus your own LLM API key usage, with no platform subscription fee at all for the self-hosted path. Managed/paid tiers on the hosted platform run around $40/month for higher usage limits and premium features. The honest limitation shared across early autonomous-agent tools like AgentGPT: they tend to consume more API tokens than more targeted platforms, since the autonomous, exploratory approach generates more LLM calls per completed task than a narrowly-scoped agent would. It remains a reasonable low-commitment way to experiment with autonomous agent behavior — set a goal, watch it work — before committing to a more structured, business-operations-focused platform like Lindy or a developer framework like CrewAI for production use.
CrewAI
Open-source multi-agent orchestration, free framework plus a managed cloud
CrewAI is both a free, MIT-licensed open-source Python framework for orchestrating multiple collaborating AI agents and a managed hosted platform (CrewAI AMP) for teams that don't want to run it themselves — a dual identity that's core to understanding its actual cost. The open-source framework, with over 50,000 GitHub stars and a reported 2 billion agent executions in the trailing 12 months as of 2026, lets developers build "crews" of specialized agents (a researcher, a writer, a reviewer) that divide and coordinate complex multi-step tasks, and it's used by a majority of Fortune 500 companies according to the company's own disclosures. CrewAI's public cloud pricing has genuinely changed multiple times and is worth getting straight: a $25/month Professional tier (100 executions/month) existed from its October 2025 AMP launch through spring 2026, then was removed entirely. As of mid-2026, the public cloud pricing is two tiers only — Basic, free with 50 workflow executions/month and full core platform access (not a crippled trial), and custom-quoted Enterprise for organizations needing compliance certifications and dedicated support (estimated $60,000-$120,000 annually in third-party analysis). If you're reading an older article citing a $99/month or $25/month self-serve mid-tier, that pricing has been discontinued. The cost that catches most teams off guard isn't the platform fee at all — it's LLM API usage. Because CrewAI counts one "execution" as a full crew run regardless of how many agents are involved or how many tokens they consume internally, a crew with 10 agents making extensive LLM calls costs the same one execution as a single-agent crew, but the underlying API bill can be dramatically higher. Production costs for token-hungry multi-agent workflows commonly run $1.50-12/hour depending on task complexity — budget for that separately from whatever CrewAI's own platform tier costs.
Manus
TrendingGeneral AI agent that completes real tasks end to end
Manus is a general-purpose autonomous AI agent that goes beyond chat: give it an objective and it plans, browses the web, writes and runs code, manipulates files and delivers a finished artifact — a research report, a spreadsheet, a slide deck or a deployed web page. Each task runs inside its own cloud sandbox with a live view of what the agent is doing, so you can watch the browser tabs, terminal commands and files it creates in real time and step in when needed. Tasks continue running even after you close the tab, and Manus notifies you when the deliverable is ready. The platform is credit-based: simple tasks cost a few credits, long autonomous research runs cost more. Teams use Manus for competitive research, lead list building, data cleanup, market analysis and prototype generation — work that used to take an analyst a full day.
Devin
Autonomous AI software engineer — now 96% cheaper than its original $500/month
Devin, built by Cognition AI, was introduced in March 2024 as "the world's first AI software engineer" — an agent that works more like a remote contractor than an in-editor assistant: hand it a well-scoped engineering ticket, and it plans the approach, works inside its own sandboxed cloud environment with shell, browser and editor access, writes and tests code, and opens a pull request for human review, all with minimal step-by-step supervision. That's the core distinction from tools like Cursor or Claude Code, which sit inside your editor and wait for you to drive each interactive step. The headline change worth knowing before evaluating Devin in 2026: Cognition slashed pricing by 96% in late 2025. The original $500/month plan — which became genuinely famous as a talking point in every competitor's marketing — still exists as the Team tier (250 Agent Compute Units included, additional ACUs at $2.00 each), but a new self-serve Core tier now starts at just $20/month plus pay-as-you-go ACUs at $2.25 each. One ACU represents roughly 15 minutes of active autonomous work, so an hour of Devin running on Core costs around $9 — meaningfully more accessible than the original enterprise-only positioning suggested. Cognition's own July 2026 benchmarks (vendor-reported, not independently verified) put Devin's current SWE-1.7 model at 77.8% on SWE-bench Multilingual and 81.5% on Terminal-Bench 2.1, and the company raised $1 billion at a $25 billion valuation in May 2026 with annualized revenue near $492 million — rapid growth that followed the price restructure. Devin fits well-scoped, repetitive engineering work best: large migrations, framework upgrades, CI failure triage, documentation for legacy code — tasks with enough time and ticket clarity to justify autonomous, unsupervised execution. For interactive, moment-to-moment coding, reviewers consistently note Cursor or Claude Code remain faster and cheaper.
Relevance AI
Build a coordinated 'AI workforce' of role-based agents
Relevance AI's core concept is an "AI workforce": rather than one general-purpose assistant handling every request, you build narrowly-scoped agents with distinct roles — a research agent, an SDR agent, an ops agent — that work together as a coordinated team, each using only the tools and information assigned to its specific job. That multi-agent orchestration approach makes it particularly strong for go-to-market teams building sales and revenue-operations workflows where several specialized tasks need to hand off to each other. A significant pricing restructure took effect in September 2025 and remains the current model: costs split into Actions (what an agent actually does — API calls, tool use) and Vendor Credits (the underlying LLM model costs), with no markup on Vendor Credits and the option on paid plans to bring your own API keys to bypass them entirely. The free tier includes 200 Actions/month plus $2 in bonus vendor credits — useful for initial testing, but genuinely difficult to forecast real monthly spend from, since usage compounds quickly once agents run continuously or handle complex, multi-step tasks. Paid plans run from roughly $19/month for individuals up to about $199/month for teams, positioning it as more affordable at the entry level than Lindy (~$50/month) but with real usage-based cost uncertainty that Lindy's flatter-feeling tiers avoid. It's best suited to teams that want a genuine multi-agent "workforce" model for sales or ops specifically, and are comfortable actively monitoring Actions and Vendor Credit consumption rather than a fully predictable flat bill.