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Agents Orchestration Frameworks · Workflow Automation

MindPal

MindPal is a no-code platform that turns proven frameworks, methodologies and standard operating procedures into branded AI agents and multi-agent workflows. Built for coaches, consultants and agencies, it publishes agents as chatbots, portals, embedded tools or APIs.

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Overview

What is MindPal?

MindPal is a no-code SaaS platform for building AI agents and multi-agent workflows that automate business processes. Its stated aim is to turn an expert's proven frameworks, methodologies and standard operating procedures into branded AI agents that work around the clock. The product is organised in three layers: Knowledge (frameworks, SOPs and supporting material), Orchestration (multi-agent workflows) and Delivery (chatbots, branded portals and embedded tools).

An agent is configured rather than coded: role, system instructions, model, brand voice, knowledge sources and tools. Knowledge comes from documents and files, websites and URLs, or structured data; agent tools include web search, web scraping and a code interpreter. Workflows chain agents through documented node types – Human Input, Info, Agent, Evaluator-Optimizer, Loop, Orchestrator-Worker, Subflow, Chat, Canvas, Code, Router, Gate, Webhook, Payment and Sticky Note – so a process can branch, iterate or pause at a human checkpoint. A native assistant called Mindie generates an agent or a workflow from a plain description or an uploaded screenshot, and a library of hundreds of templates offers a second starting point.

Model access depends on the plan: GPT-4o mini on the free tier, then GPT-5, Gemini 2.5 Pro and Claude 4 Sonnet from Pro upwards, with DeepSeek and Groq cited in the documentation. From the Pro plan you can bring your own OpenAI, Anthropic, Google Generative AI or Groq keys for unlimited credits.

Delivery is where the platform makes its case. An agent can go out as a shareable link, an embed, a chat widget, a custom domain or an API call, with custom branding on published agents and on the team workspace. Deployment integrations listed on the home page include Kajabi, Circle, GoHighLevel, WordPress, Shopify, Wix, Webflow, Framer, Squarespace, Notion, Lovable, Bolt.new, Replit, v0, Cursor and Claude Code; MCP and Composio integrations are documented, alongside Zapier and Make.

The publisher is MindPal Labs Inc., with a product team advertised in Ecopark, Hung Yen, Vietnam, and the domain was registered on 17 March 2023. The site claims more than 50,000 builders and a self-declared 4.9 rating from 120 reviews. For teams that would rather delegate the build, a managed service staffed by AI automation engineers is offered separately.

What it does

  • Build a custom AI agent with system instructions, a brand voice and its own knowledge sources
  • Chain several agents into a multi-agent workflow using more than a dozen documented node types
  • Publish an agent as a shareable link, an embedded chatbot, a chat widget or a branded AI hub
  • Feed agents with PDF, Word, PowerPoint, Excel, audio, video, YouTube and website content
  • Trigger workflows through the public API, a webhook, a form or a schedule
  • Give agents web search, web scraping and a code interpreter
  • Connect a custom domain to a published agent as a paid add-on
Audience

When to use MindPal / When not to

A quick filter to help you decide if MindPal is the right fit.

When to use MindPal

  • Coaches and consultants who want to productise a proven methodology into an agent that answers around the clock
  • Course creators and community operators delivering guided implementations, assessments and onboarding at scale
  • Agencies reselling AI assistants under their own name, using custom branding and a custom domain
  • Non-technical operations teams automating repeatable processes without Python, model training or MLOps
  • Customer support and success teams building assistants grounded in their own documentation and SOPs

When not to use MindPal

  • Organisations that require EU data residency, since everything is hosted exclusively in United States data centres
  • Buyers whose procurement asks for published security certifications such as SOC 2 or ISO 27001
  • Teams that need a mobile companion, as no iOS or Android application is referenced
  • Developers on a small budget who need API access, which starts at the Advanced plan
  • Anyone hoping to run production volume on the free plan, capped at 100 AI credits, one agent and one workflow
Get started

How to use MindPal

A typical end-to-end flow, from setup to results.

  1. Create a free account on the MindPal app: no credit card is required and 100 AI credits are included
  2. Choose a starting point for your first agent: let Mindie generate it, pick a ready-made template, or start from a blank build
  3. Configure the agent's role, system instructions, model and brand voice
  4. Attach knowledge sources: documents and files, websites and URLs, or structured data
  5. Enable the agent tools you need, such as web search, web scraping or the code interpreter
  6. Build a multi-agent workflow the same way – generated, from a template, or node by node
  7. Add human checkpoints with Human Input and Gate nodes wherever a decision must stay with a person
  8. Test the result, then publish it as a shareable link, an embed, a chat widget, a custom domain or an API endpoint
  9. Set a trigger if the workflow must run on its own: public API, schedule, form or webhook
  10. Lean on the public documentation and the 'MindPal for Beginners: From Zero to Hero' playlist; support runs through a Facebook group on the free plan, email on paid plans and live calls from Advanced upwards
Quick read

Pros & Cons

Pros

  • No-code building that is genuinely reachable for non-technical users
  • Unlimited agents and workflows from the Pro plan: billing follows credits, not the number of agents
  • Multi-model choice (OpenAI, Anthropic, Google, DeepSeek, Groq) and bring-your-own-key from Pro upwards
  • Publishing and white-labelling built in: embed, chat widget, custom branding and custom domain
  • Clear commitment that customer data is not used to train foundation models, with a DPA available for enterprise customers
  • A permanent free plan without a credit card, plus a 14-day money-back guarantee on paid plans
  • Substantial public documentation and a large library of agent and workflow templates

Cons

  • No postal address and no legal notice published anywhere on the site
  • No security certification of MindPal itself is published, neither SOC 2 nor ISO 27001
  • Hosting is exclusively in the United States, with no EU data residency option
  • GDPR compliance is never claimed explicitly, even though the privacy policy covers legal bases and transfer safeguards
  • The public API is reserved for the Advanced plan and above, and a custom domain is a paid add-on on Pro and Advanced
  • Credit-based pricing makes the real cost hard to forecast, since consumption depends on the models used
  • No mobile application, and every contact address sits on mindpal.io rather than on mindpal.space
Pricing

Pricing & Plans

MindPal offers a permanent free plan at 0 USD with no credit card required, limited to 100 AI credits, 50 MB of knowledge, one agent and one workflow. The lowest paid entry point is the Pro plan at 49.00 USD per month on monthly billing; the pricing page displays 39 USD per month when annual billing is selected, invoiced 468 USD per year. The higher tiers are 179 USD and 449 USD per month on monthly billing (149 USD and 374 USD per month billed annually). Add-ons are charged separately: 9 USD per 1,000 extra credits per month, 1 USD per GB per month, 9 USD per custom domain per month, 29 USD per Editor seat per month and 5 USD per User seat per month. All paid plans carry a 14-day money-back guarantee, cancellation is possible at any time, and payment is processed through Lemon Squeezy. An Enterprise plan is available on quotation.

Free – 0 USD, forever
  • 100 AI credits
  • 50 MB of knowledge
  • 1 agent
  • 1 workflow
  • GPT-4o mini
  • no credit card required
Advanced – 179 USD per month billed monthly, or 149 USD per month billed annually; flagged as most popular and best for innovative teams
  • 5 Editor seats plus 20 User seats
  • 30
  • 000 credits per month
  • 25
  • 000 MB
  • team workspace branding
  • sharing and collaboration
  • public API and live support calls
Ultra – 449 USD per month billed monthly, or 374 USD per month billed annually; presented as best for growing businesses
  • unlimited seats
  • 100
  • 000 credits per month
  • 100
  • 000 MB
  • unlimited custom domains and top-priority support
Plan 5
  • Enterprise – on quotation
  • with SAML SSO cited at this level
Plan 6
  • MindPal Managed – a managed service delivered by MindPal's AI automation engineers
Plan 7
  • Custom domain – a paid add-on at 9 USD per domain per month on Pro and Advanced
  • included on Ultra
Special offers — Annual billing lowers the monthly rate, with advertised savings of 120 USD per year on Pro, 360 USD on Advanced and 900 USD on Ultra · The Ultra plan billed annually includes one month with a dedicated AI automation engineer, presented as a 2,000 USD value · A promotional code, APRIL30, was advertised on the home page as a limited-time offer (April 2026 capture) · Seasonal Black Friday and Cyber Monday campaign pages were run in 2024 and 2025 · An affiliate programme pays a 20% recurring commission, hosted on Lemon Squeezy
Prices and plans listed above may evolve. Always check the official pricing page before subscribing.
Trust & Privacy

Data, GDPR & hosting

A consolidated view of how MindPal handles your data.

GDPR overview

MindPal never states, in so many words, that it is GDPR-compliant. 'GDPR' appears once in the terms (section 10), only to point enterprise customers towards a data processing agreement, which is available. The privacy policy, effective 25 October 2025, nevertheless sets out several GDPR-shaped elements: legal bases for processing – contract performance, legitimate interests, consent and legal obligation (4.4); Standard Contractual Clauses for transfers from the EEA, the United Kingdom and Switzerland (9); and rights of access, rectification, erasure, portability, objection and withdrawal of consent (10), answered within 30 to 45 days. Global Privacy Control signals are honoured where the law requires it (12), and the service is not intended for under-16s (13). No Article 27 EU representative and no data protection officer are named; every request goes to support@mindpal.io.

Who owns the data?

Under the terms of service you keep all ownership rights to the Customer Content you upload (section 6.1), and you own the Outputs generated for you (section 9.2), although MindPal gives no guarantee that comparable outputs will not be produced for other users. You grant MindPal a limited, worldwide, non-exclusive, royalty-free licence solely to operate the service; it ends when you delete the content or close your account, subject to backup cycles (6.2). Section 6.3 rules out selling your content, using it for advertising or claiming your ideas and intellectual property. Feedback is the one exception: MindPal keeps a perpetual, unrestricted licence over it (6.4).

Reuse rights

Because you own both your inputs and the outputs generated for you, no further permission from MindPal is needed to reuse them; the terms only warn that similar outputs may be produced for other users, so uniqueness is not guaranteed. On its side, MindPal states that customer content is used to run the service, execute agents, detect fraud, test quality and improve the product (privacy policy 4.1), and that prompts, files, outputs and third-party integration data are not used to train foundation AI models by default (section 5); a future anonymised data-contribution programme would require separate, explicit consent that can be withdrawn. Content may be aggregated and anonymised for analytics, research and product improvement (terms 6.2). Data is shared with named providers – AWS for hosting, OpenAI, Anthropic and Google for models, Lemon Squeezy for payments (privacy 7.1) – with no sale of personal data and no cross-site behavioural advertising. Connected integrations such as Google Workspace, Slack or GitHub only reach the scopes you authorise, and that access can be revoked.

Data retention & training

Retention summary
The privacy policy, effective 25 October 2025, sets retention by category. Customer content – prompts, files and outputs – is kept for 90 days after creation, or until you delete it, and deletion can be done directly in the product. Agent execution logs are kept for 180 days. Account and billing data is retained for the life of the account plus seven years to meet legal and tax obligations. Security and error logs are kept for 12 to 24 months. Backup copies follow a rolling 35-day retention. When an account is closed, data is deleted or de-identified on the same schedule, subject to any legal hold. Section 15.4 of the terms restates the same timetable, including the 90-day window for prompts and files and the 35-day backup cycle.
Trains on customer data
No
Subprocessors disclosed
Yes
DPA available
Yes
GDPR contact

Hosting summary

MindPal states that all user data is stored in AWS S3 and MongoDB databases hosted exclusively in data centres in the United States. No EU or other regional hosting option is offered, and transfers from the EEA, the United Kingdom and Switzerland are covered by Standard Contractual Clauses. The published security practices describe TLS 1.3+ in transit and AES-256 at rest through S3 default encryption, least-privilege AWS IAM access controls with multi-factor authentication and key rotation, VPC isolation with security groups and network ACLs, CloudTrail and CloudWatch logging, bcrypt password hashing, secrets held in AWS Secrets Manager, tenant-level data isolation, environment segregation, access limited to authorised technical staff with detailed access logs, and regular security audits and vulnerability assessments. No external certification of MindPal itself is published, neither SOC 2 nor ISO 27001, and the certifications referenced on the data security page are those of the cloud providers. A data processing agreement is available for enterprise customers. Note that the privacy policy still carries an unfilled placeholder, 'primarily in [US regions]', where the hosting regions should be named.

Hosting countries
🇺🇸 United States
Watch-outs

Things to keep in mind

Risks and trade-offs to weigh before adopting MindPal.

  • Corporate identity is thin: 'MindPal Labs Inc.' appears only in the footer of the careers page, no postal address or legal notice is published, and an email address is the only channel offered
  • Every contact address sits on mindpal.io, a domain distinct from mindpal.space, and the relationship between the two is documented nowhere
  • All data is hosted in the United States with no EU option, and no external certification of MindPal is published; the certifications mentioned on the data security page belong to the cloud providers
  • The privacy policy still carries an unfilled template placeholder, 'primarily in [US regions]', which suggests the document was produced from a template without a full review
  • The liability cap in the terms is very low – 100 USD or twelve months of fees – under Delaware law, with no arbitration clause and no named venue
  • Published information is not always consistent: the pricing meta description quotes 49/179/449 USD while the annual toggle shows 39/149/374 USD, the home page's structured FAQ does not match the one displayed, the footer still reads '2025' on 2026 captures, and the blog subdomain returns an HTTP 402 error
  • Handing a proven methodology to an always-on agent moves judgement onto the model: outputs are not guaranteed to be unique or correct, so keep the human checkpoints (the Human Input and Gate nodes exist for that) on anything client-facing
Setup

Setup & Integrations

Technical difficulty

Low to get started, moderate to go further. MindPal is a no-code product: you describe what you want to Mindie in plain language, or start from a template, and no Python, model training or MLOps skill is required. Publishing an agent means pasting an embed snippet or calling the API. Friction appears on advanced work – Code, Webhook and Router nodes, MCP servers, the public API and credit budgeting – where technical comfort helps. Public documentation and a beginners' video playlist cover the basics, and the paid MindPal Managed service exists for teams that would rather delegate the build.

Deployment

Web appAPI

Integrations

Kajabi Circle GoHighLevel WordPress Shopify Wix Webflow Framer Squarespace Notion Lovable Bolt.new Replit V0 Cursor Claude Code Google Workspace Google Drive Slack Microsoft Teams GitHub Composio Zapier Make
Company

Behind MindPal

Company name
MindPal Labs Inc.
Founded
17/03/2023
Country of origin
🇺🇸 United States
UBO
INFORMATION_NOT_FOUND
UBO country
INFORMATION_NOT_FOUND
Domain registrar country
🇺🇸 United States
Legal contact
Support contact

Social

Official links

Resources

All the official URLs gathered for verification and reference.

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FAQ

Frequently asked questions

Is there a free version of MindPal?
Yes. Signing up is free, requires no credit card and comes with 100 AI credits, one agent, one workflow, 50 MB of knowledge storage and GPT-4o mini. The free plan is permanent rather than a time-limited trial.
What is an AI credit?
An AI credit is the unit consumed each time a task runs. The cost varies with the model: MindPal cites GPT-4o mini and Llama among the cheaper options and Claude 3.5 Sonnet among the more expensive ones.
What happens when my credits run out?
You can buy more at 9 USD per 1,000 credits per month, or connect your own OpenAI, Anthropic, Google or Groq API key from the Pro plan onwards for unlimited credits.
How many agents and workflows can I create?
Unlimited on paid plans. MindPal counts credits, not the number of agents or workflows you build.
Does MindPal train AI models on my data?
No. The data security page and section 5 of the privacy policy state that customer content is not used to train foundation models by default. A future anonymised contribution programme would require separate consent that can be withdrawn.
Where is my data hosted?
In AWS S3 and MongoDB databases hosted exclusively in data centres in the United States. Transfers from the EEA, the United Kingdom and Switzerland rely on Standard Contractual Clauses.
Is a data processing agreement available?
Yes. A DPA is available for enterprise customers, and section 10 of the terms points customers with GDPR obligations towards it.
Can I get a refund?
All paid plans carry a 14-day money-back guarantee. Requests are sent to support@mindpal.io and processed within 5 to 10 business days.
Can I publish agents under my own brand?
Yes. Custom branding applies to published agents and to the team workspace, and a custom domain costs 9 USD per domain per month, included on the Ultra plan.
Is there an API?
Yes. The public API is available from the Advanced plan, alongside webhooks and scheduled triggers.
Conclusion

Should you pick MindPal?

MindPal knows what it is: not a generic chatbot, but a way to productise expertise. The three-layer pitch – knowledge, orchestration, delivery – is backed by real functional depth: more than a dozen workflow node types, human checkpoints, MCP and Composio integrations, a public API, bring-your-own-key model access and white-label publishing on a custom domain. For a coach, a consultant or a small agency that wants to serve more clients without hiring, it is a credible option, and the permanent free plan makes it cheap to evaluate.

The counterweight is corporate transparency. No postal address, no legal notice and no external certification of MindPal itself are published, and every contact address sits on mindpal.io, a domain distinct from the site. Data is hosted exclusively in the United States, with no EU residency option, and GDPR compliance is never claimed in so many words – the privacy policy, effective 25 October 2025, does set out legal bases, Standard Contractual Clauses and data subject rights, but an unfilled template placeholder suggests it was not reviewed end to end. The liability cap in the terms is low: 100 USD or twelve months of fees.

Pricing deserves modelling before you commit. Everything runs on AI credits whose cost varies with the model chosen, the public API only appears at the Advanced tier, and a custom domain is a paid add-on below Ultra. The displayed price also depends on the billing toggle: 49 USD per month on monthly billing, 39 USD per month when paid annually.

In short, strong product value for expertise-driven businesses, weaker assurance for buyers with procurement, residency or compliance requirements. Start on the free plan, price the credits against your real volume, and ask for the DPA early.