The AI agent platform built for teams that ship, not researchers.

What is an AI agent platform

Four things every real AI agent platform has to do.

Most products labelled "AI agent platform" only cover one or two of these. If you're evaluating tools, use this list as a checklist before you pick. A platform that ships agents to production needs all four — and the gaps are where teams get stuck six weeks in.

• Build

  A way to define an agent — its goal, the tools it can use, the rules it follows — without writing custom orchestration code for every scenario.

• Deploy

  A runtime to run that agent on a schedule, on a trigger, or on demand — with reliable execution, retries, and human-in-the-loop checkpoints when stakes are high.

• Integrate

  Pre-built connectors so the agent can actually do work — read from your CRM, write to your warehouse, send the email, file the ticket — without you wiring each API by hand.

• Observe

  Logs, traces, and analytics so you can see what each agent did, why it made each decision, and which steps are failing or burning tokens.

Why teams pick Arahi

Four things we do differently than the rest of the category.

• 01 — The builder

  Noilder (AgentNEO) — describe it, ship it.

  Skip the drag-and-drop. Tell Arahi what you want an agent to do in one sentence and a running, tool-wired agent shows up in minutes. No flowcharts, no DAGs, no code.

  • Most teams ship their first production agent in under 30 minutes.

• 02 — Integrations

  1,500+ apps via Composio.

  Slack, Gmail, HubSpot, Salesforce, Notion, Stripe, Asana, Jira, Linear, Zendesk, Intercom, Google Drive, Calendly, QuickBooks — plus the long tail of tools your team actually uses. OAuth-scoped, revocable, audit-logged.

  • If an app has a public API, your agent can use it without you writing code.

• 03 — Orchestration

  AI Departments — specialist agents that coordinate.

  One agent can do a lot, but a department can do a job. Build a sales department where an SDR agent hands off to a researcher agent, which hands off to a follow-up agent — each with its own tools and scope, all coordinated by Arahi.

  • Same metaphor your team already uses to organise people.

• 04 — Memory

  A shared memory layer every agent reads from.

  Your docs, past decisions, customer history, and SOPs become on-demand context for every agent. No re-uploading PDFs, no per-agent knowledge bases that drift out of sync — one source of truth, one retrieval layer.

  • New agents inherit institutional knowledge from day one instead of starting blind.

How Arahi compares

Arahi vs Lindy vs Relevance AI vs LangChain vs Stack AI.

We've tried to be honest about where each tool wins. If you want developer-level control, LangChain is hard to beat. If you want a personal AI assistant for one user, Lindy is excellent. Arahi is built for teams who want production agents shipped this week, without code, across the tools they already use.

Competitor pricing and feature claims reflect publicly listed details at the time of writing. Confirm on each vendor's site before committing.

• No-code builder

  • Arahi — Yes — describe the agent in plain English
  • Lindy — Yes — flow-based builder
  • Relevance AI — Mostly — low-code with some scripting for advanced cases
  • LangChain — No — Python / TypeScript framework
  • Stack AI — Yes — drag-and-drop with templates

• Multi-agent orchestration

  • Arahi — Yes — AI Departments coordinate specialist agents
  • Lindy — Limited — agents trigger each other manually
  • Relevance AI — Yes — multi-agent teams built in
  • LangChain — Yes — LangGraph is the most flexible option here
  • Stack AI — Basic — chained nodes inside a single workflow

• Integrations

  • Arahi — 1,500+ apps via Composio
  • Lindy — ~3,000 actions, narrower per-app depth
  • Relevance AI — ~100 native + custom HTTP
  • LangChain — Unlimited — but you build each one
  • Stack AI — ~100 native connectors

• Shared memory across agents

  • Arahi — Yes — a single memory layer every agent reads from
  • Lindy — Per-agent memory only
  • Relevance AI — Yes — vector store + agent memory
  • LangChain — DIY — memory primitives you wire yourself
  • Stack AI — Per-workflow knowledge bases

• Hosting

  • Arahi — Fully hosted (AWS)
  • Lindy — Fully hosted
  • Relevance AI — Fully hosted
  • LangChain — Self-host the framework; LangSmith is hosted
  • Stack AI — Fully hosted

• Code required

  • Arahi — No
  • Lindy — No
  • Relevance AI — Optional, for advanced steps
  • LangChain — Yes — Python or TypeScript
  • Stack AI — No

• Entry pricing

  • Arahi — $49 / month
  • Lindy — Free tier; paid from ~$49.99 / month
  • Relevance AI — Free tier; paid from ~$199 / month
  • LangChain — Free (open source); LangSmith paid
  • Stack AI — Free tier; paid from ~$199 / month

• Best for

  • Arahi — Teams who want production agents shipped this week
  • Lindy — Solo operators and personal AI assistants
  • Relevance AI — Data-heavy ops teams comfortable with low-code
  • LangChain — Engineering teams who want code-level control
  • Stack AI — Internal AI apps built from templates

What teams build

Three jobs an Arahi agent can take off your plate this week.

Each of these is wired up using off-the-shelf Arahi connectors and templates — no custom code. Outcomes are described qualitatively because every team's baseline is different.

• Sales ops

  Inbound lead triage

  AEs stop digging through dashboards — they wake up to a short, ranked queue.

  • New lead lands in HubSpot
  • Agent enriches with firmographics + recent funding
  • Agent scores against your ICP
  • Hot leads drop into #sales-hot on Slack with a 1-line summary
  • Integrations: HubSpot, Clearbit, Slack

• Marketing ops

  Brief → draft → publish

  Cycle time from brief to published asset collapses; the editor's job becomes review, not writing from scratch.

  • PM files a brief in Notion
  • Researcher agent pulls source material from Drive + the web
  • Writer agent drafts in your brand voice and hands off for review
  • On approval, publisher agent pushes to the CMS
  • Integrations: Notion, Google Drive, Webflow

• Customer support

  Ticket triage with KB lookup

  Tier-1 volume gets handled overnight; your team focuses on the tickets that actually need a human.

  • New ticket opens in Zendesk
  • Agent classifies intent and pulls the relevant KB article
  • Drafts a reply, attaches sources, flags for handoff if confidence is low
  • Logs the resolution + missing-KB-article suggestions back to Notion
  • Integrations: Zendesk, Notion, HubSpot

Pricing

Transparent pricing. 7-day free trial. No credit card.

• Need custom integrations, volume pricing, or SSO?
• Talk to us about Enterprise.

• $49 / mo

  Starter

  Small teams up to 2 people.

  • 5,000 credits / month
  • Unlimited agents
  • 1,500+ apps

• $149 / mo

  Growth

  Teams up to 10. Most teams pick this.

  • 16,000 credits / month
  • Shared workspaces
  • Priority support

• $349 / mo

  Pro

  10–50 people, separate workspaces.

  • 32,000 credits / month
  • SSO ready
  • Dedicated CSM

Questions teams ask before they sign up.

How much does an AI agent platform like Arahi cost?

Arahi starts at $49/month (Starter, 5,000 credits) for small teams of up to 2 people. Most teams pick Growth at $149/month (16,000 credits, up to 10 people). Pro is $349/month (32,000 credits, 10–50 people, separate workspaces). Enterprise is custom. Every plan includes a 7-day free trial, unlimited agents, and access to 1,500+ app integrations.

What integrations does Arahi support out of the box?

Arahi connects to 1,500+ apps via Composio — including Slack, Gmail, Notion, HubSpot, Salesforce, Stripe, Asana, Jira, Linear, Zendesk, Intercom, Google Drive, Calendly, QuickBooks, and the long tail of tools small teams actually use. If an app has a public API, your agent can use it without you writing code.

Is there a learning curve if I've never built an AI agent before?

No. You describe what you want an agent to do in plain English and Arahi builds it. There are no flowcharts to learn, no DAGs to wire, and no code. Most teams get their first agent running in under 30 minutes; pre-built templates cover the common patterns (lead triage, ticket routing, drafting, research) so you start with a working agent and tweak it.

Where is the platform hosted and what are my hosting options?

Arahi is a fully hosted, multi-tenant platform on AWS — your team logs in at app.arahi.ai and starts building. There's nothing to install or operate. Enterprise customers can talk to us about dedicated environments, regional data residency, and SSO.

How does Arahi handle data security and privacy?

Your data is encrypted in transit and at rest. We never train foundation models on your data. Integration credentials are stored as scoped OAuth tokens you can revoke at any time, and you control which tools each agent can touch. Enterprise plans add SSO, audit logs, role-based access, and a signed DPA.

What AI agent tools does Arahi include?

Out of the box, every Arahi agent gets a working toolbox: 1,500+ pre-built integration tools (Gmail, Slack, HubSpot, Notion, and the rest), a shared memory layer, a code tool for custom logic, web search, file handling, and a human-in-the-loop approval tool. You can also expose any HTTP API or OpenAPI spec as a custom AI agent tool without leaving the platform. Tool choice is up to the agent — not a hand-drawn flowchart.

How does Arahi handle AI agent workflows?

An AI agent workflow on Arahi isn't a rigid step-by-step DAG — it's a goal you describe in plain English plus the tools and permissions the agent is allowed to use. The agent decides which step comes next based on the actual situation. That means one workflow definition handles edge cases, partial information, and unusual requests without you wiring every branch by hand. Triggers (schedule, webhook, email, Slack message, form submission) kick off the workflow; humans get pinged only when something needs judgment.

Does Arahi have an AI agent app, or is it web-only?

Arahi runs in the browser at app.arahi.ai — no install required on any platform. Agents can be triggered from anywhere you'd expect: Slack, email, web forms, browser extension, mobile-friendly chat, and API. We don't ship a separate native AI agent app because the agents themselves live across the apps your team already uses (Slack, Gmail, your CRM) rather than being trapped in a standalone window.

Why is Arahi the best AI agent platform for small teams?

Three reasons. First: it actually works for non-developers — plain-English builder, pre-built templates, 1,500+ integrations live on day one. Second: pricing scales with usage, not seats — $49/month gets a small team a real working agent, not a demo. Third: the platform handles the boring infrastructure (auth, retries, observability, memory, integrations) so you focus on what the agent should do, not how to plumb it. Compare with framework-only options that require an engineer for every workflow.

Start building today

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