You have three proposals to automate with AI. One promises an agent up and running in two weeks, another starts with a two-month assessment and the third brought a demo that answered everything without missing a beat. All three say "artificial intelligence," but they aren't talking about the same thing.
Choosing an AI automation company is more like hiring an ERP implementation partner than buying software: you're buying a process that has to work with your data and your team.
In this guide you'll see what "fast delivery" means, the types of vendors, 10 questions to evaluate them, which commitments to demand and the red flags to watch for before signing.
What an AI automation company is (and what "fast delivery" means)
An AI automation company is a vendor that designs, builds and integrates workflows in which an artificial intelligence model interprets information (emails, conversations, documents) and carries out steps in your systems, such as the CRM or ERP, with defined rules and human oversight. Its deliverable isn't a tool: it's a working process.
That's why a fast AI implementation is measured by the time it takes to reach a first workflow in production: real people, real cases and a measured KPI. A demo with sample data, an isolated prototype or the full transformation doesn't count.
The timeline depends on how many systems need to be connected, the state of your data and who signs off; anyone who sets it before understanding your process is guessing. To understand the building blocks of a workflow, read what workflow automation is and AI process automation.
Automation pilot: what it should include
An automation pilot is a scoped first version of a workflow, with real data and users over a defined period. It should set out in advance the process boundaries, a baseline (current time, errors and volume), who reviews the AI and when it gets scaled up or stopped.
Types of vendors: no-code agency, AI consultancy, ERP integrator and vertical SaaS
There's no single best vendor, only the right one for your case:
| Vendor type | What it does best | Typical risk | When it makes sense |
|---|---|---|---|
| No-code agency | Connects apps quickly with Zapier, Make or n8n | Fragile workflows, in the agency's accounts | Simple integrations |
| AI consultancy | Custom agents and development | Prototypes that never go live | Cases with no standard solution |
| ERP or CRM integrator | Knows your data, permissions and processes | AI as an add-on if it lacks agent experience | Workflows that read from and write to the ERP |
| Vertical SaaS | Ready-made product for one use case (customer service, collections) | Little customization and usage-based cost | High-volume standard cases |
Combining them often makes sense: to sell and provide customer service over WhatsApp, at KPB we work with Vambe, whose AI agents connect to the Odoo CRM. If you're looking for an AI consulting firm in Chile or Mexico, also make sure the workflow performs well in Spanish and that they know your ERP's local integrations.
AI agent vendors: watch out for the label
An AI agent decides which steps to take to achieve a goal and uses tools (querying the CRM, creating a task) within defined limits. A chatbot with fixed answers isn't one.
Gartner uses the term agent washing for rebranding assistants, RPA or chatbots as agents. In June 2025 it estimated that only about 130 of the thousands of companies selling agentic AI are the real thing, and that more than 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear business value or inadequate risk controls (Gartner). Ask every AI agent vendor to separate what the agent decides from what runs on fixed rules.
Checklist: 10 questions to evaluate an AI automation company
A good AI automation partner answers with examples, not promises:
- Which process do we automate first, and how do we measure it? A scoped proposal with a baseline.
- Can I see a similar workflow with real data? A case shown with the client's permission or a test with your data.
- Which systems does it integrate with, and how? APIs, connectors and permissions.
- At which points does a person review? Defined in writing.
- What happens when the AI gets it wrong? Escalation, logging and correction.
- What data leaves my company, and where does it go? Model, processing location and retention.
- Who owns what gets built? Workflows, prompts, code, accounts and documentation.
- What recurring costs will I have? Licenses, model usage and AI credits.
- What support is there after go-live? Owner, channel and adjustments.
- How do we exit if it doesn't work? An exit plan agreed at the start.
If the workflow lives in Odoo, add the checklist for choosing an Odoo Partner in Chile.
What support and service commitments to ask your vendor for
A service commitment is what the vendor is bound to deliver after go-live. Keep it separate from what depends on the platform, which the vendor doesn't control:
| Depends on the vendor | Depends on the platform |
|---|---|
| Incident response time | Service availability (uptime) |
| Monitoring of errors and escalated cases | Model version changes and usage-based pricing |
| Prompt and rule adjustments when your process changes | Usage limits and API quotas |
Get them in writing and by criticality level; to evaluate the platform, use the SLA checklist in our guide to n8n for business.
Integration with your systems and human in the loop
AI pays off when it writes where your team works, such as a task in the CRM. If it stays in a separate chat, you're back to entering data twice. Ask early:
- Does your plan allow external connections? In Odoo, the external API and agentic AI are only available on the Custom plan (checked in October 2026 on Odoo's pricing page).
- What permissions does the AI operate with? In Odoo 20, the MCP server uses an API key tied to a user's identity and permissions (Odoo 20 documentation), so the agent operates with that user's permissions: it's best to set up a dedicated user with minimal access. Availability depends on your version and plan; see what MCP is.
Human in the loop
Human in the loop means a person reviews, approves or corrects what the AI proposes at defined points in the workflow. There are three levels: the AI suggests and the person decides (a draft reply); the AI acts with approval (it sends the proposal once the sales rep confirms); and the AI acts and notifies (it logs the meeting in the CRM). A good vendor starts with more review and dials it back when the workflow warrants it. You'll find applied examples in customer service and sales.
Security, personal data and ownership of what gets built
Agree on these before signing:
- Least-privilege access: the AI accesses only what the workflow needs.
- Action logs: everything it does is traced and auditable.
- Personal data: what is sent to the model, with what notice or consent (for example, when recording meetings) and how long it's kept. In Chile, Law 21.719 updates the rules on personal data protection; see what changes for your CRM and your AI agents.
Ownership of what gets built is the most often overlooked point: accounts in your company's name, and the workflows, prompts, code and documentation in your hands. In September 2026, Gartner predicted that by 2028, 70% of enterprises will abandon agentic AI built by vendor engineers working alongside the client (forward-deployed engineering), due to rising costs and their inability to evolve it on their own. It recommends agreeing from the start on intellectual property, knowledge transfer and an exit plan (Gartner).
Red flags in an AI proposal
Ask for more detail if you see any of these:
- Demos that never use your data.
- Promises of full autonomy, like "the agent replaces your team."
- Guaranteed timelines or savings before the assessment.
- No one explains what happens when the AI fails.
- Everything in the vendor's accounts, with no documentation or exit plan.
- Usage costs that aren't projected against your volume.
Why do it with KPB Solutions: from assessment to your first workflow in operation
At KPB, with Kersify, we design custom AI assistants and agents that work inside your CRM, whether it's Odoo or another one: they log conversations, qualify leads or prepare proposals, with human review at the points we define with you.
We work in phases (assessment, design, integration, adoption and ongoing support) to get a first high-value workflow up and running quickly and scale from there. As an Odoo Gold Partner with more than 70 active clients in 6 countries, we pair AI with deep knowledge of the ERP where your data lives.
Want to apply this checklist to your case? Book your meeting and let's review which process you should automate first.
