A business AI assistant promises to answer employees' questions, draft letters, or follow up on files without delay. The promise is appealing: fewer repetitive tasks, more responsiveness, better-shared internal knowledge. But an SMB leader quickly faces a choice: buy a ready-made solution or have a custom tool built?
Both options have their merits. What matters is the balance between your business need, the confidentiality of your data, and the level of control you want to keep. Here's how to decide without taking on a project too heavy for your organization.
Key Takeaways
- In 2024, 10% of French companies with 10 or more employees used an AI technology, up from 6% in 2023 (Insee, 2025).
- 31% of French micro-businesses and SMBs use generative AI, but only 9% have invested in AI in the past three years (Bpifrance Le Lab, 2025).
- A bought solution suits a standard, low-sensitivity need; a custom-built assistant is worth it as soon as confidentiality, compliance, or business integration matter.
- Custom projects range from a few hundred euros to several tens of thousands, depending on document volume, level of customization, and hosting chosen.
- Start with a narrow use case, measure the gain, then expand the tool: it's the best insurance against overinvestment.
What is a business AI assistant?
A business AI assistant is a tool that handles requests in natural language and carries out tasks based on your data or processes. It can answer an employee looking for a procedure, help draft a customer email, qualify a case, or extract information from a document. To see what this looks like in practice, explore our use cases.
Unlike a general-purpose chatbot like ChatGPT, the business assistant draws on your document base, your business rules, and, ideally, your existing tools. That's what makes all the difference: it doesn't produce generic text, it produces answers grounded in your business.
At NexeAI, we build this kind of tool as AI agents. They automate a specific workflow, keep data under control, and integrate with the software you already use.
Buying a solution: fast, but standardized
The first option is to subscribe to a ready-made AI assistant. These tools often connect to an office suite, a CRM, or a knowledge base, and offer preconfigured templates for customer service, HR, or sales.
The advantages
Setup is fast. Within a few hours, you have an interface, a language model, and connectors to your everyday applications. You don't have to manage infrastructure or choose an open-source model. The cost is predictable: a monthly subscription per user, sometimes with a query quota.
This route suits well-identified, low-sensitivity needs: drafting standard letters, rephrasing text, summarizing meetings, searching general internal documentation.
The limits
A bought solution imposes its own logic. You don't control the model, where the data is hosted, or the compliance terms. If your documents contain personal data, trade secrets, or regulated information, you depend on the vendor's guarantees.
But the tool stays generic. It doesn't know how your firm handles a case, or your workshop's specific quality procedure. When the need falls outside the expected cases, the assistant stalls.
According to Insee, 69% of companies using AI buy off-the-shelf software or systems (Insee, 2025). It's the most common path, but not always the best suited to regulated SMBs or highly specific trades.
Building your own assistant: control and integration
The second option is to develop your own AI assistant. This doesn't necessarily mean hiring engineers: with today's no-code tools and open-source frameworks, a specialized vendor can deliver a working AI agent within a few weeks.
When custom-building makes sense
An assistant designed for you rests on three strengths:
- Your business document base: internal procedures, contract templates, technical sheets, case law, industry regulations.
- Integration into your tools: management software, email, intranet, customer portal, CRM database.
- Control of the whole chain: choice of model, hosting in France, traceability of answers, GDPR and AI Act compliance.
It's this last dimension that appeals to law firms, accounting practices, healthcare professionals, or industrial SMBs. The assistant lives in your environment, not an American vendor's.
What it requires
Building an assistant takes scoping work. You need to choose which documents to include, define priority use cases, test the answers, and train your teams. It isn't a purely technical expense: it's an organizational project.
Insee notes that 24% of companies using AI develop in-house or modify open-source software, and 29% go through vendors (Insee, 2025). Custom builds thus remain a minority, but they often correspond to the most durable projects.
If you want to understand how to host this kind of tool while keeping control, read our article on local AI and shared computing.
Four questions to decide
The choice between buying and building doesn't depend on trends. Ask yourself these four questions before signing a quote.
1. Is your data sensitive?
If you handle customer data, patient files, financial information, or trade secrets, an assistant hosted in the United States or subject to vague terms is a risk. Prefer a solution hosted in France, or even locally, with a model you choose.
2. Is your need standard?
Drafting marketing content, rephrasing emails, or generating FAQ answers lend themselves well to an off-the-shelf tool. On the other hand, qualifying a legal case, advising based on your business knowledge base, or helping with technical diagnostics require a tool built around your business.
3. Do you have a process to integrate?
An assistant becomes more valuable when it's part of a workflow: following up with a customer, validating a step, extracting data into your management software. If the tool stays isolated, it becomes a gadget. If you want to integrate it, custom building gives you more latitude.
4. What's your real budget?
The purchase cost seems low at first: a few dozen euros a month per user. But options, extra query charges, and integration limits add up. The cost of building requires an initial investment, followed by controlled maintenance.
How much does an AI assistant cost in 2025?
Le Blog du Dirigeant published a realistic range in April 2025 for a RAG-type project, the architecture that lets the assistant draw on your documents to answer with sourced references.
| Profile | Starting budget | Monthly subscription | Suits if |
|---|---|---|---|
| Solo test | €0 to €30 | Free or low | You want to experiment alone on a simple base. |
| Assistant for one department | €500 to €1,500 | €100 to €400 | A department wants to save time on a specific case. |
| Custom project | €3,000 to €15,000 | €200 to €800 | Several departments, business integration, training. |
| Sovereign, scalable solution | €10,000 to €50,000 | €300 to €1,000 | Strong compliance, hosting in France, traceability. |
These figures aren't universal rates: they depend on document volume, frequency of use, level of customization, and security requirements. Still, they give a useful order of magnitude for calibrating a first discussion.
FAQ
Can an SMB really create its own AI assistant?
Yes, as long as it doesn't aim too broad. No-code tools and open-source models now make it possible to build an AI agent for a specific use case without hiring an engineer. AI training helps teams scope the project, choose the right tools, and maintain the agent over time. The key is to start with a narrow scope, validate it, then expand it.
Buy or build: which is cheaper?
In the short term, buying costs less. In the medium term, a poorly suited tool generates workarounds, wasted time, and compliance risks. A custom assistant, better integrated, often pays for its cost within a few months on the automated tasks.
How do you guarantee data confidentiality?
Choose hosting in France or Europe, a model you control, and an architecture that keeps your documents within your perimeter. GDPR and the AI Act require knowing where the data goes, who has access to it, and how the tool makes its decisions. Compliance isn't declared: it's built in from the design stage.
What's the first use case to automate?
Take a repetitive, well-documented, measurable task: answering frequent questions, qualifying a case, following up on a missing document. Measure the time saved over two or three weeks. This first success funds what comes next and wins teams over.
Conclusion
The choice between buying and building an AI assistant depends on your situation. If your need is standard and confidentiality is a moderate concern, a ready-made solution will save you time. If your activity relies on sensitive data, specific processes, or a compliance requirement, a custom-built assistant will be more profitable and safer.
At NexeAI, we support SMBs and independent professionals through this choice. We start with an audit of your processes to identify the use case worth pursuing, then we build a no-code AI agent, hosted in France, that stays under your control.
Torn between the two options? Let's talk about it. We'll look at your situation and tell you whether you'll gain more by buying an existing tool or building your own.
