An honest, detailed comparison of MAIA Brain and Make (Integromat) — covering AI reasoning, document intelligence, enterprise scale, on-premise compliance, and total cost of ownership. Built for European operations teams evaluating their next automation platform.
Make (formerly Integromat) is one of the most capable visual workflow automation tools on the market. For connecting cloud apps, building multi-step integrations, and automating predictable, structured tasks across SaaS platforms, it is genuinely excellent — and at modest scale, extremely cost-effective. The challenge begins when your enterprise needs more than trigger-action logic. Make has no native document intelligence, no autonomous exception handling, no on-premise deployment option, and no AI reasoning layer — all of which are standard expectations for regulated European enterprises in 2026. Its per-operation pricing model also scales in ways that can be difficult to predict and budget at high volume. MAIA Brain is a different category of software entirely: an enterprise AI automation platform with native document understanding, autonomous exception resolution, EU AI Act compliance from day one, and a flat-rate pricing model that eliminates billing surprises — all managed by MAIA's team from onboarding through to production.
We've taken Make's advertised capabilities and compared them honestly against MAIA Brain across 13 criteria that matter to European enterprise automation teams in 2026.
| What You Need It to Do | Make (Integromat) | MAIA Brain ★ BEST VALUE |
|---|---|---|
| Automate repetitive tasks across your business | Yes — visual scenario builder for connecting apps and automating structured workflows | Yes — and handles exceptions autonomously without stopping or requiring manual fixes |
| Read and understand unstructured documents | No — Make can pass files between apps but has no native document intelligence or extraction capability | Yes — native document intelligence: invoices, contracts, purchase orders, any format, included in all plans |
| Handle unexpected situations without stopping | No — scenarios fail or require manual error handling when inputs deviate from expected patterns | Yes — autonomous exception handling with full audit trail and human escalation where needed |
| Run fully on-premise (data never leaves your environment) | No — cloud-only platform; all scenario execution and data processing occurs on Make's infrastructure | Yes — full on-premise deployment included as standard across all plans |
| EU AI Act and GDPR compliance built in | Partial — GDPR compliant as a data processor; EU AI Act readiness not addressed at platform level | Yes — EU AI Act ready and GDPR by design from day one, including decision explainability |
| AI reasoning for autonomous decisions | Partial — Make can call AI APIs (e.g. OpenAI) as a step, but has no native reasoning layer; logic must be engineered | Yes — neurosymbolic AI reasoning native across all processes from day one, no engineering required |
| Get smarter over time without reprogramming | No — scenarios execute fixed logic; any improvement requires manual scenario updates by your team | Yes — continuous self-learning from every completed task cycle without developer intervention |
| Connect existing enterprise software (SAP, Salesforce, Oracle) | Partial — 1,000+ app connectors for popular SaaS tools; enterprise ERP integrations require custom HTTP modules | Yes — 500+ enterprise connectors including SAP, Salesforce, Oracle, and all major enterprise platforms |
| Multi-language support across European markets | Partial — platform UI available in multiple languages; AI language capability depends on external API configuration | Yes — native multi-language AI reasoning across all European languages |
| Time to go live for enterprise-grade automation | Partial — fast for simple integrations; complex enterprise workflows require significant internal engineering effort | Yes — 4–6 weeks to production, onboarding and configuration fully managed by MAIA team |
| Predictable, flat-rate pricing at enterprise volume | No — per-operation pricing; costs scale with every scenario run, which can become significant at high volume | Yes — transparent flat-rate enterprise pricing, no per-operation billing, no billing surprises |
| Setup and onboarding included in plan price | No — enterprise setup requires internal technical teams or a Make-certified partner at additional cost | Yes — full onboarding and configuration managed by the MAIA team, included in your plan |
| Audit logging and governance for regulated industries | Partial — basic scenario execution logs available; enterprise-grade audit trails require additional configuration | Yes — full decision audit trails, access controls, and governance reporting included as standard |
Make's per-operation model works well at low volume. But as your automation footprint grows — more scenarios, more documents, more processes — the billing scales with it. Add the engineering cost of building and maintaining complex scenario networks, the cost of certified Make partners for enterprise deployment, and the absence of onboarding support, and the total cost of ownership at enterprise scale is significantly higher than the headline subscription price suggests. MAIA Brain consolidates everything into a single, transparent, predictable plan.
Based on comparable enterprise deployments. Individual results vary. Make pricing based on publicly available information as of February 2026. Verify current pricing and plan details directly with Make.
A detailed look at how MAIA Brain handles the use cases where Make excels — and the enterprise scenarios where MAIA goes significantly further — across every capability that matters to operations and IT teams evaluating automation platforms.
MAIA Brain reasons over your data and makes autonomous decisions — it understands context, applies business logic, and resolves ambiguity without stopping. Make can call external AI APIs as a workflow step, but the AI logic must be engineered and maintained by your technical team. MAIA's reasoning capability is built in from day one, with no AI API configuration required.
MAIA Brain reads, classifies, and extracts structured data from any unstructured document — invoices, purchase orders, contracts, claims forms, delivery notes — and routes the extracted data through your automation workflow. This is native capability, included in all plans. Make has no document intelligence; document processing requires third-party tools connected via Make's API modules.
When an automation encounters a situation it hasn't seen before, MAIA Brain reasons through it and resolves it autonomously — or escalates to a human with full context, only when genuinely necessary. Make scenarios halt on errors and require manual review and restart. At enterprise volume, this difference in exception resilience is significant.
MAIA Brain is designed from the ground up for full on-premise deployment. All AI processing, document understanding, and workflow orchestration runs on your own infrastructure. Your data never leaves your environment. Make is a cloud-only platform — there is no on-premise deployment option. For European enterprises with data sovereignty requirements, this is a structural limitation, not a configuration choice.
MAIA Brain is built with EU AI Act readiness and GDPR compliance by design — decision explainability, full audit trails, access controls, and data minimisation are standard, not add-ons. Make is a GDPR-compliant data processor for the data it handles, but it was not architected with the EU AI Act in mind and does not address AI system transparency, risk classification, or conformity obligations.
MAIA Brain improves with every completed task cycle. It learns from variations in documents, adapts to changes in your data formats, and refines its exception handling over time — without developer intervention or scenario updates. Make executes fixed scenario logic. Improvements require manual updates to the scenario builder by a technical team member.
MAIA Brain is live in 4–6 weeks. Our team handles everything from discovery through to go-live — so your operations team is running improved processes, not managing a software implementation project.
MAIA's team works with your operations team to identify and prioritise the highest-impact automation opportunities. No technical prerequisites, no lengthy workshops — we map your processes and configure MAIA to match them.
MAIA Brain is configured to your specific processes, document types, and business rules. Integrations with your existing systems — ERP, CRM, document management, communication platforms — are established using MAIA's pre-built enterprise connectors. No custom development required.
Your first automations go live within 4–6 weeks. MAIA Brain begins processing tasks immediately, handling exceptions autonomously, and learning from every completed cycle. Your team manages outcomes — MAIA manages the work.
Both MAIA Brain and Make are excellent tools — for different contexts. Here's an honest guide to help you decide which is the right choice for your organisation.
We started with Make for our supplier invoice workflow and it worked well at first. But as volume grew and invoice formats became more varied, we were spending more time fixing failed scenarios than the automation was saving us. The per-operation costs were also climbing in ways we hadn't anticipated. MAIA Brain handles every invoice format we throw at it, resolves exceptions on its own, and runs entirely on our own infrastructure. We haven't manually intervened in a document workflow in four months.
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Whether you're comparing platforms, evaluating use cases, or ready to start — these pages will help you take the next step.
Honest answers to the questions European enterprise teams most frequently ask when evaluating MAIA Brain against Make (Integromat).
Talk to our team about your specific automation requirements. We'll show you exactly how MAIA Brain handles your use cases — document processing, exception handling, compliance — and give you a clear picture of what deployment and cost look like for your organisation.