# Workato Alternative: Elaichi vs Workato > Elaichi is a Workato alternative with published per-seat prices, workflows, approvals and the Elaichi Agent, all on the Black plan. Where each one wins. **TL;DR** Elaichi is a Workato alternative that puts 650+ connectors, workflows, shared tables, dashboards and AI in one place under one set of rules. The Black plan turns on the workflows, tables, dashboards and Agent, at a published $24 per user per month plus usage. The team's own AI, Claude, ChatGPT, Cursor or any MCP client, or the Elaichi Agent, writes each workflow. It test-runs the workflow on real data, with writes held back, before it goes live. Workato publishes no prices and counts usage in Tasks, one per action step. Stay on Workato for an on-prem agent, dev, test and prod environments, or 1,200+ connectors. ## Is Elaichi a Workato alternative for your team? Elaichi is a Workato alternative for a team that wants its AI clients and its automation on one set of governed connections. It publishes its price, and each workflow runs as a named person under that person's restrictions. A buyer looking for a Workato alternative asks two things: what it costs, and who the automation acts as. Elaichi answers both, on its pricing page and in its access model. Workflows, collections, dashboards, knowledge bases and the Elaichi Agent come with the Black plan. It lists at $24 per user per month. Workato is built for enterprise automation. It has 1,200+ pre-built connectors, an on-prem agent and a full recipe lifecycle. A recipe is Workato's name for an automation ([Workato pricing](https://www.workato.com/pricing), checked November 2026). Elaichi is a governed MCP control plane: one place that decides which person and which AI client may use which tool. MCP (Model Context Protocol) is the standard way an AI assistant calls tools in other apps. The [guide to Workato Enterprise MCP alternatives](/blog/workato-enterprise-mcp-alternatives/) covers MCP access methods. Here the subject is the automation itself. ## How do Elaichi and Workato compare side by side? Workato wins on depth and hosting choices. Elaichi wins on a published price, and on a workflow that runs as a named person under that person's restrictions. | Question | Workato | Elaichi | | --- | --- | --- | | Automation unit | Recipes with polling, real-time, scheduled and change data capture triggers | Workflows with up to five triggers of seven types; no trigger for an event inside a connected app | | AI agent | Genies built in Agent Studio, with skills built on recipes; prebuilt Genies are an add-on | The Elaichi Agent, in the console and in Slack, with an approval card before writes | | Tables and dashboards | Data tables; dashboards through Workflow apps Pages, an add-on | Collections of up to 1,000,000 rows each; dashboards over a collection or live app data | | Per role and per user | Environment roles, project roles and custom roles | One role per member from 58 permissions, plus restrictions on a role or one member | | Audit | Activity audit log kept one year; log streaming on specific plans | An audit log on every plan; export to your own Datadog comes with the Black plan | | Approvals | Workflow apps tasks that pause a recipe up to 365 days | Approve steps answered by a person in the console or Slack, 72 hours by default | | Hosting | Nine data centers, an on-prem agent and Virtual Private Workato | EU, US or APAC, chosen at creation; no on-prem agent | | Connectors | 1,200+ pre-built connectors | 650+ connectors | | Price | Not published; usage counted in Tasks | $24 per user per month, or $18 billed yearly, plus run minutes and storage past a free allowance | The Workato cells come from Workato's own pages: [pricing](https://www.workato.com/pricing), [triggers](https://docs.workato.com/en/recipes/triggers.html), [Agent Studio](https://docs.workato.com/agentic/agent-studio.html), [role-based access](https://docs.workato.com/user-accounts-and-teams/role-based-access/access-control-v2.html), [the activity audit log](https://docs.workato.com/features/activity-audit-log.html) and [data centers](https://docs.workato.com/security/ip-allowlists.html), checked November 2026. Elaichi's prices are US-dollar list prices. [The pricing page](/pricing/) shows yours. ## Why keep connectors, workflows, AI and dashboards in one place? Elaichi puts 650+ connectors, workflows, collections, dashboards, knowledge bases and AI in one workspace. One set of rules covers all of it. The team brings the AI it already uses. Here is the chain: - A workflow calls a connected app's tool and writes rows to a collection with collection.upsert. A collection is a shared table. - A dashboard reads that collection, or a read-only toolbox tool for live app data. A toolbox is a set of tools picked for one job. - A knowledge base holds the answers people look up. - Claude, ChatGPT, Cursor or any MCP client at https://api.elaichi.ai/mcp builds, tests and reads all of it. So does the Elaichi Agent, in the app and in Slack. The Agent runs on the organization's own AI provider keys, one key per provider. Every workflow agent step picks from the same models. One place means one set of rules: - **One restriction check.** A restriction is a rule that limits which connectors and tools a person may use. Every connected-tool call passes one restriction check for the member it acts as. It does not matter which client or workflow sends it. - **One audit log.** The audit log is the record of who did what. Each row records where the call came from (app, mcp, api or console) and how it was approved. - **One approval rule.** A person answers every approval. No AI does. - **One bill.** Seats, plus usage pooled across the workspace. AI apps never count as users. Workato sells some of these pieces separately. Its pricing page lists Workflow Apps and Pre-Packaged Genies as add-ons beside the four editions ([Workato pricing](https://www.workato.com/pricing), checked November 2026). ## How does an Elaichi workflow run? An Elaichi workflow is built as a draft and tried with a test run. Then it is published as a version and turned on. It runs as the person who owns it, with that person's access and restrictions. A workflow starts from up to five triggers. The seven types are: - a manual run - a cron schedule, which repeats - a one-time schedule - a webhook, a message an app sends to a web address when something happens - a Slack message or reaction - a collection row change - another workflow's run There is no trigger type for an event inside a connected app. So the app has to send a webhook. A workflow holds up to 50 steps, among them call_tool, branch, foreach, approve, agent and code. Runs are kept for 30 days. A failed run can run again from the failing step. ## How does your own AI write and test a workflow before it goes live? Your team's own AI writes the workflow. A test run proves it on real data before anyone turns it on. Claude, ChatGPT, Cursor or any MCP client builds it through Elaichi's elaichi__automation__ operations. The Elaichi Agent, in the console or tagged in Slack, gets the same operations. The loop has five steps, and each one is an operation the AI can call. 1. **Draft.** draft__create and draft__update write the definition. A draft saves even while it has validation issues. 2. **Validate.** draft__validate checks the definition without saving it. It names the step that is wrong. 3. **Test run.** dry_run over MCP runs the latest draft against real data. In the console it is "Test run (changes nothing)", in the Run now dialog. Tools that only read run for real, as the person running the test. Tool calls that write are recorded as what would have been called, and never sent. So are collection writes, knowledge writes and state writes. A notify step sends nothing. An approve step reports what it would ask. 4. **Publish.** publish turns the draft into a numbered version. It is refused while validation finds errors. 5. **Turn on.** enable starts the triggers. Turning a workflow on is a separate step from publishing it. A test run costs no run time, so the AI can iterate as often as it needs. A webhook trigger has its address while the workflow is still a draft. A test run can replay a sample delivery as the trigger's payload. When the Agent does it, validating and a test run need no approval. Publishing or turning on a workflow asks the person every time and can never be remembered. A test run the Agent starts acts as the person chatting. If a published version goes wrong, "Restore this version" makes an earlier one live again. It sits under the workflow's Details and Versions. The AI that writes a workflow cannot answer its approvals. Dashboards follow the same pattern. Edits land in a draft, and publishing makes it the version everyone sees. ## Why does a workflow that runs as its owner matter? A workflow that runs as its owner can never reach more than that owner can. The organization's restrictions on the owner apply while the run goes. So a restriction change reaches a run already under way. Elaichi re-checks the owner about every minute. If the owner leaves or can no longer act, the run fails with owner_invalid. The workflow is paused instead of running on. The console says so: "This workflow runs with its owner's access." Removing or suspending a member also stops their MCP clients on the next call. Retries are built for writes. A step that writes is never sent again when its outcome is uncertain. It ends as outcome_unknown, for a person to check in the app. ## How do approvals work in Elaichi? A person approves, in Elaichi or in Slack, before the step runs. The AI never approves its own work. An approve step asks named people or teams. It also asks the workflow's owner, unless the step leaves them out. It can bar the person who started the run from approving it. The request reaches approvers on the console's Approvals page, in Slack and by email. The email carries only a link to the console. A Slack card has Approve and Reject buttons only when no destructive step waits behind it. A request expires after 72 hours by default, and the range is five minutes to 30 days. No AI client, Elaichi Agent or workflow can approve or reject. The wait is not billed. A destructive step with no approve step before it is flagged as a warning. That happens when the workflow is validated or published. ## What do collections, dashboards and knowledge bases add? Collections hold the records a workflow keeps. Dashboards show them, or live app data. Knowledge bases hold the documents an agent searches. All three come with the Black plan. A collection holds up to 100 fields, 1,000,000 rows and 1 GB. Row history is off until someone turns it on. Then any version of a row can be restored. A collection widget on a dashboard is read for each viewer as that viewer. A public link shares a copy of a dashboard, not live access. Public links are off until an admin turns them on. They expire after 90 days by default, and can be revoked. A document a workflow writes into a knowledge base is saved as untrusted. Only a person in the console can mark it reviewed. ## What does the Elaichi Agent do? The Elaichi Agent works inside Elaichi, in the console and in Slack, for an organization on the Black plan. It sits beside Claude, ChatGPT, Cursor or any MCP client, and it is not one of them. In the console, the Agent opens from the "Agent" row at the top of the sidebar. Before a write it shows an approval card with "Deny", "Allow once" and, when the action can be remembered, "Always allow". A remembered choice skips the card next time. The organization's automatic-writes setting is off by default, and it covers only Elaichi's own writes. The Agent also runs a prompt-injection check that can stop a write. Prompt injection is hidden instructions inside the data a tool returns. Tagging @Elaichi in Slack reaches the same Agent. One limit to plan around: Elaichi does not browse, search or fetch the web for a workflow or the Elaichi Agent. A workflow has no fetch step. A recipe that scrapes a page belongs elsewhere. ## How do governance and audit compare per user and per role? Elaichi governs each member through one role, and through restrictions on that role or on the member. Workato governs collaborators through environment and project roles. Elaichi's permission catalog has 58 permissions, and a member holds exactly one role. A restriction allows or restricts whole connectors or single tools. It targets a role or one member. A role or restriction change takes effect within about two minutes. A person kept off a tool can file an access request for an admin to decide. Custom roles, SSO with SAML or OIDC, and SCIM come with Gold and with Black. SSO is one company sign-in. SCIM adds and removes users from your identity provider. The Elaichi audit log is on every plan and is kept for 90 days. It keeps one entry for each connected-tool call that reaches execution (a call refused earlier writes none). Each row shows who called, which tool, which connection, how the call was approved and whether it worked. For a longer history, export to your own Datadog comes with the Black plan. Workato's docs describe environment roles, project roles such as Builder and Project operator, and custom roles at both levels ([Workato role-based access](https://docs.workato.com/user-accounts-and-teams/role-based-access/access-control-v2.html), checked November 2026). Workato keeps activity audit logs for one year from the event. Audit log streaming to Amazon S3, Azure, Splunk, Datadog or Sumo Logic is on specific plans ([Workato audit log streaming](https://docs.workato.com/features/activity-audit-log-streaming.html), checked November 2026). ## What does each one cost? Elaichi publishes its price. Workato does not, so the useful comparison is the unit each one counts. The Black plan lists at $24 per user per month in US dollars, or $18 per user per month billed yearly ($216 a year). Usage past a free monthly allowance costs extra. The allowance is 1,000 run minutes and 1 GB-month of storage, pooled across the organization. Past it, a run minute is $0.02 and a GB-month is $5. Waiting for an approval or a timer is free, and test runs cost nothing. Guests, Billing Admins and Auditors do not take a billable seat. AI apps never count as users. [The pricing page](/pricing/) shows the price for your country. Workato's pricing page lists four editions: Standard, Business MCP, Enterprise MCP and Workato ONE. It shows no prices, only a "Get a quote" path ([Workato pricing](https://www.workato.com/pricing), checked November 2026). Its docs define a Task as "a single action step that a recipe executes". Triggers and control steps are not counted, and each loop iteration is one Task ([Workato Tasks](https://docs.workato.com/recipes/tasks.html), checked November 2026). Some plans count Business actions instead. The difference in units matters for loops. A Workato recipe that loops over 500 records pays per iteration in Tasks. An Elaichi workflow that loops over 500 records pays for the minutes it spends working, and nothing for steps. ## Where does Workato win? Workato wins wherever an enterprise needs depth, hybrid hosting or a formal release process. Said plainly, these are reasons to stay. - **On-prem agent.** Workato's on-prem agent runs on a server behind your firewall. It connects out over a TLS WebSocket tunnel, with no inbound ports ([Workato on-prem agent](https://docs.workato.com/en/on-prem.html), checked November 2026). Elaichi has no equivalent. - **Environments and recipe lifecycle.** Workato documents built-in development, test and production environments, and deployments from Development. It also documents export and import of recipe packages ([Workato environments](https://docs.workato.com/en/features/environments.html), checked November 2026). - **Compliance programs.** Workato's docs list PCI-DSS v4.0.1 Level 1, ISO 27001, 27701 and 42001, and HIPAA. They also list SOC 1, SOC 2 and SOC 3 reports, IRAP and NIST 800-171A ([Workato security compliance](https://docs.workato.com/security/security-compliance.html), checked November 2026). Elaichi's compliance reports are in its Trust Center at [https://trust.elaichi.ai](https://trust.elaichi.ai). - **Data centers.** Workato names nine: US, EU, JP, SG, AU, IL, CN, KR and UK ([Workato data centers](https://docs.workato.com/security/ip-allowlists.html), checked November 2026). Elaichi has three: EU, US and APAC. APAC is best-effort placement, not a residency guarantee. - **Connector and trigger depth.** Workato's pricing page lists 1,200+ pre-built connectors. Its docs describe real-time triggers that listen for app events, and change data capture for databases ([Workato triggers](https://docs.workato.com/en/recipes/triggers.html), checked November 2026). ## Switch to Elaichi if these hold Switch to Elaichi when your automation should run on the same governed connections your AI clients use. These are the hard cases for it. - You want a published per-seat price and usage you can estimate before you sign. - You want your own AI to write each workflow and test-run it on real data, with writes held back, before it goes live. - Every write to a business app should run as a named owner, under that owner's restrictions, and stop when the owner leaves. - A person should approve the risky step, in Slack or the console, and no AI should ever answer that request. - Your systems are SaaS apps, and none of them sits behind your firewall. Every new workspace gets a 14-day Black trial, no credit card to start. Buying Gold or Black during the trial keeps its remaining days rather than granting a fresh 14, so it is one continuous trial, and the seats are first charged when it ends. A workspace that buys nothing moves to the free Personal plan. Nothing is deleted. The trial is the Black plan itself, with every Black feature on: workflows, collections, dashboards, knowledge bases and the Elaichi Agent. Its one limit is the free monthly usage of 1,000 run minutes and 1 GB. That limit is a hard stop until you buy the Black plan. For what Black includes, read [the Black plan](/blog/elaichi-black-plan/). For the workflow builder itself, read [how Elaichi workflows work](/blog/elaichi-workflows/). To check that your apps are covered, browse [the connector catalog](/connectors/). The trial is Black with every feature on. Have your AI draft a workflow and test-run it. [Start the 14-day Black trial](https://app.elaichi.ai/signup) ## FAQ ### How much does Workato cost compared with Elaichi? Workato's pricing page lists no prices. It names four editions, Standard, Business MCP, Enterprise MCP and Workato ONE, and sends buyers to sales for a quote ([Workato pricing](https://www.workato.com/pricing), checked November 2026). Elaichi's Black plan lists at $24 per user per month in US dollars, or $18 per user per month billed yearly. Usage past a free monthly allowance of 1,000 run minutes and 1 GB-month of storage costs $0.02 a run minute and $5 a GB-month. The pricing page at elaichi.ai/pricing/ shows the price for your country. ### What does Workato count as a Task? Workato's docs define a Task as a single action step that a recipe runs. Triggers and control steps such as IF conditions, loops, Stop job and Handle errors do not count. A looped step counts once per iteration ([Workato Tasks](https://docs.workato.com/recipes/tasks.html), checked November 2026). Elaichi does not count steps. It bills seats, plus the minutes a workflow spends working past the free allowance. Time spent waiting for a person or a timer is free. ### Can an Elaichi workflow start when a record changes in Salesforce? Only through a webhook. An Elaichi workflow starts from manual runs, schedules, a one-time schedule, a webhook, or a Slack message or reaction. It can also start from a change to a row in an Elaichi collection, or another workflow's run. There is no trigger type for an event inside a connected app. So the app has to send a webhook to the workflow's own address. Workato documents polling and real-time triggers that watch apps directly ([Workato triggers](https://docs.workato.com/en/recipes/triggers.html), checked November 2026). ### Who approves a step in an Elaichi workflow? A person. An approve step asks named people or teams, plus the workflow's owner unless the step leaves them out. They answer on the Elaichi console's Approvals page or in Slack, and an email carries a link to the console. No AI client, Elaichi Agent or workflow can approve or reject. A request expires after 72 hours by default, and the time a run waits is not billed. ### Does Elaichi have an on-prem agent like Workato? No. Elaichi runs as a hosted service in three regions, EU, US and APAC, chosen when the organization is created. Workato documents an on-prem agent. It opens an outbound tunnel from a server behind your firewall, with no inbound ports ([Workato on-prem agent](https://docs.workato.com/en/on-prem.html), checked November 2026). If you need to reach systems inside your own network, that is a reason to stay on Workato. ## Read next - [Workato Enterprise MCP alternatives: how to choose](/blog/workato-enterprise-mcp-alternatives/) — Workato Enterprise MCP alternatives come in three shapes. Here is what each one is built for, and what to check before you buy. - [Zapier MCP alternative for a whole company](/blog/zapier-mcp-alternative/) — Elaichi is a Zapier MCP alternative: one organization endpoint with role restrictions and an audit log. What each costs, and when Zapier fits. - [Automation platform vs MCP access: which job?](/blog/n8n-automation-vs-mcp-access/) — Scheduled workflows and ad hoc assistant calls are two jobs. How to split automation platform vs MCP access, and when one tool covers both.