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B2B AI category

Make, n8n and OpenAI agencies: compare providers

A Make, n8n and OpenAI agency designs workflows that connect AI models, business applications and validation rules. Do not choose only by tool name: compare the process, connectors, account ownership, testing, security and maintenance.

Comparison

Providers related to this category

The data comes from AIPartnerLens profiles and their public sources. This comparison is neither a rating nor a ranking.

Open the filtered directory
Alegria.group logo

AI, no-code & automations

Alegria.group

Unclaimed profile

Commercial profile: Basic

Alegria.group presents an AI-agency offering combining consulting, agents, automations, no-code business applications and deployment of custom solutions.

Best suited for
Deployment of custom AI solutions · AI agents integrated into business processes · No-code and low-code business applications
Evidence
Official AI-agency, custom-solution and deployment pages with public examples; technical scope, exact role and outcomes of each reference should be confirmed.
Budget
Not disclosed
To clarify
Request the exact tools and deliverables.
View profile for Alegria.groupProfile not claimed · Claim
Botnation AI logo

No-code AI chatbot platform

Botnation AI

Unclaimed profile

Commercial profile: Basic

Botnation AI offers a no-code, multi-platform AI-chatbot platform focused on customer support, lead generation, e-commerce and integrations.

Best suited for
Lead generation · Customer support · FAQ
Evidence
Official website, pricing page, use cases, integrations and public case studies; custom support should be assessed.
Budget
Public SaaS pricing starts at €39/month excluding VAT; the custom enterprise offering should be confirmed.
To clarify
Calculate cost based on users, AI credits and channels.
View profile for Botnation AIProfile not claimed · Claim
G

Custom development, automation & AI

Genee

Unclaimed profile

Commercial profile: Basic

Genee is a Lyon-based custom software development agency offering business automation, AI agents, RAG, API integration and DevOps industrialization.

Best suited for
AI agent for email review and routing · RAG and search across an internal document base · Automation of reconciliations and data entry
Evidence
Detailed official website, services page, public client case studies including several anonymized cases, methodology and entry pricing for selected offerings; exact scope, outcomes and comparable references should be confirmed before a decision.
Budget
Separate public formats: first Make scenario from 3 500 € HT; complete Make program from 8 000 to 25 000 € HT; Make build & run from 1 800 €/month; MVP Factory from 8 000 € HT on the dedicated page; and an MVP generally around 15 000 € on the services page. For business applications, sources diverge: the services page states 30 000 to 150 000 €, while the homepage shows custom development from 18 000 € HT and its FAQ describes a complete application generally between 15 000 and 80 000 €. These values are not merged or used to calculate an average; scope and price must be confirmed directly with Genee.
To clarify
Which published client case study is most comparable to the targeted processes?
View profile for GeneeProfile not claimed · Claim
I

Operational automation & AI agents

IA4OPS

Unclaimed profile

Commercial profile: Basic

IA4OPS is a Bordeaux-based agency operated by LP Consulting, offering diagnostics, process automation, AI agents, custom development and hands-on training.

Best suited for
Operations-focused AI diagnostic and roadmap · Automation of reporting, meeting minutes and documents · AI agents for customer service or internal teams
Evidence
Official website, About page, detailed client case studies, France Num profiles and public testimonials; figures and outcome attribution should be confirmed for comparable cases before engagement.
Budget
Not disclosed
To clarify
Who delivers the technical work when several areas of expertise are required?
View profile for IA4OPSProfile not claimed · Claim
C

AI agency, no-code & automation

Cortex-iA

Unclaimed profile

Commercial profile: Basic

Cortex-iA is an agency based near Angers that offers AI applications, chatbots, no-code automation, audits, digital strategy and training programs for freelancers, microbusinesses and SMBs.

Best suited for
Automation of the monitoring of outreach · Chatbot and assistant for relations client · Web applications integrating AI features
Evidence
Official website, service pages, training programs, About page, case studies and active public registry; displayed outcomes, references, tools and the move toward an agent platform should be confirmed directly.
Budget
Not disclosed
To clarify
Is the current offering a custom agency service or an agent platform?
View profile for Cortex-iAProfile not claimed · Claim
Spatiaal logo

Business tools, automation & calculation engines

Spatiaal

Basic profile · provider reviewed

Commercial profile: Basic

Spatiaal designs business tools structured around data collection and processing, calculation engines adapted to client rules, and presentation of results.

Best suited for
Forms and data-collection interfaces · Processing data entered manually or extracted from documents · OCR when the project requires it
Evidence
Example CEE delivery disclosed by the provider; quantitative outcomes and named client references are not disclosed.
Budget
Not disclosed
To clarify
Exact scope of post-delivery support.
View profile for SpatiaalBasic profile · provider reviewed · Complete

Need help selecting a few profiles that fit your context?

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Who is it for?

Start from the need, not the jargon

Requests involving Make, n8n and OpenAI often start with a concrete problem: reducing copy-paste work, enriching data, generating a document or connecting a CRM. The tool can accelerate delivery, but it can also hide insufficient process discovery.

AIPartnerLens keeps this category conservative. A provider may mention automation, agents or integrations without being presented as a Make or n8n specialist unless public information clearly documents that expertise.

  • Operations teams that want to test an automation quickly with Make, n8n, OpenAI, Claude or Gemini.
  • SMBs already using CRMs, spreadsheets, Notion, Airtable, Slack, email or support tools that need to be connected.
  • Decision-makers who want to understand no-code limits before entrusting sensitive processes to automation.
  • Providers that want a genuinely specialized Make, n8n, OpenAI or AI automation offering to be reviewed.
Common use cases

Situations worth comparing

These examples help scope a conversation. They do not imply that every provider covers the entire scope.

Make or n8n workflows for follow-ups, notifications, enrichment and synchronization between tools.

OpenAI, Claude or Gemini calls for controlled summarization, classification, rewriting or content generation.

CRM automation for enrichment, simple scoring, task creation or message preparation.

Document, meeting-note or summary generation from structured data.

Form, email or inbound-request processing with human validation.

Simple AI agents connected to a knowledge base or business tools.

Monitoring model costs, API limits, failures and scenario maintenance.

Stack selection

Make, n8n, custom APIs or a hybrid architecture

A fast demo does not prove that a workflow will be maintainable. Compare account ownership, volume-based costs, failure handling, access and operational responsibility.

Criteria for selecting between Make, n8n, custom APIs and hybrid architectures
ApproachBest fitOwnership to clarifyEvidence to requestMain risk
MakeFast visual automations with many SaaS connectors and a sufficiently stable process.Accounts, workspaces, connections, permissions, delivery history and transfer to the client.Demonstrable workflow, error handling, operations estimate and documentation.Cost or fragility increasing with volume, branching and exceptions.
n8nMore technical workflows, controlled hosting requirements or advanced custom orchestration.Instance, hosting, secrets, backups, updates, logs and operational responsibility.Architecture, test environment, error handling, supervision and update procedure.Operational workload being underestimated or an instance left without an owner after delivery.
Custom API and codeCritical processes, complex rules or strong performance, security or integration constraints.Repository, documentation, cloud accounts, secrets, tests, deployment and reversibility.Automated tests, acceptance criteria, architecture, monitoring and maintenance plan.Vendor dependency if code, access and documentation are not transferred.
Hybrid architectureNo-code for orchestration with custom components for sensitive or complex parts.Clear boundaries across tools, code, data, secrets, support and responsibilities.Architecture diagram, end-to-end tests, volume-based costs and incident procedure.A stack of tools with no single owner or simple failure diagnosis.

Broaden the comparison to AI automation agencies, AI integrators and the AI project budget guide before selecting a tool.

Comparison criteria

What should be explicit before a proposal

Use cases

Describe the workflow step by step, including trigger, data, validation and expected output.

Budget / scope

Compare discovery, build, testing, documentation, handover and maintenance.

Available evidence

Ask for scenario examples, anonymized demos, known limits and evidence of ongoing maintenance.

Tools

Make, n8n, OpenAI, Claude, Gemini, Zapier or APIs should be selected for the environment rather than by habit.

Internal maturity

An internal owner should understand the workflow, approve changes and monitor failures.

Risks

No-code limits, API costs, overly broad access rights and undocumented scenarios are common risks.

Best suited for / may not fit

Best suited to clear, repetitive processes; less suitable for unstable business logic or sensitive data without proper controls.

Maintenance

Check who fixes scenarios when tools change or volume increases.

API security

Review keys, technical accounts, data sent to models and access rights.

Before signing

Questions to ask the provider

1

Is the provider genuinely specialized in Make, n8n or OpenAI, or does it offer automation more broadly?

2

Which scenarios will be delivered, and who can modify them after the engagement?

3

How are API keys, technical accounts and access rights managed?

4

Which recurring costs depend on tools, models and volume?

5

Does the workflow include human validation for sensitive actions?

6

What happens if an API changes or a scenario fails?

7

Is the documentation sufficient for the company to take ownership of the project?

8

What evidence shows that comparable workflows have been maintained over time?

Points to clarify

Risks to scope without overstating them

  • Building a workflow quickly until it becomes critical without documentation or an internal owner.
  • Sending sensitive data to a model or connector without clear rules.
  • Underestimating no-code limitations as business exceptions increase.
  • Accumulating automations without monitoring, logs or regular review.
  • Confusing expertise in a tool with the ability to frame the underlying business process.
AIPartnerLens method

How AIPartnerLens compares this category

AIPartnerLens compares this category conservatively across use case, budget, evidence, tools, risk, security, fit and maintenance. Without sufficient public information, a profile is not presented as a strict Make or n8n specialist.

Editorial scores, risks and recommendations cannot be bought. Specialist providers may have their offering reviewed to clarify tools, evidence and scope.

use casesbudgetevidencetechnical environmentrisksbest fit / poor fitpublic dataprovider review status

FAQ: Make, n8n & OpenAI agencies

How should we choose a Make and OpenAI agency?

Describe the workflow, tools to connect, data used, human approvals and expected maintenance first. Then compare evidence, documentation, security and budget.

Make or n8n: which should we choose?

It depends on your environment, hosting constraints, internal technical skills, required connectors and maintenance model. The decision should not be based only on the provider's preference.

Is OpenAI enough to automate a process?

No. The model is one component. The project also needs data handling, connectors, prompts, validation, failure handling, cost controls and security.

What are the risks of no-code AI automation?

Tool dependency, undocumented scenarios, silent failures, unexpected API costs, excessive access rights and weak supervision after delivery.

Why might no provider be listed even though the category exists?

Because AIPartnerLens does not infer specialization without evidence. Providers are listed when public or verified information clearly supports the positioning.

Can I request a shortlist for Make, n8n or OpenAI?

Yes. The request can specify your workflow, tools, security constraints and expected maintenance level before a manual search.

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Pillar page

B2B AI provider comparison

Sources and editorial framework

Verify the information used

Public sources are displayed on each provider profile. Collection methods, data limitations and independence rules are described in the reference pages. Technical terms are defined in the B2B AI glossary.

MethodologyTransparencyGlossary