Most small businesses that look for an AI consultant do not need another strategy deck. They need someone who looks at how work actually flows, picks the two or three tasks where AI will pay off, and then builds those automations inside the tools the team already uses. That is the job we do.
What does an AI automation consultant do?
An AI automation consultant maps how work gets done in your business, identifies the repetitive tasks where AI can reliably take over, and puts those automations into production. A good one stays accountable after launch, because an automation that nobody maintains stops working within months.
The difference with a general AI consultant is the last step. An advisor hands you recommendations; an automation consultant hands you something that runs every day. In practice the work covers:
- Process mapping. Who does what, with which documents, in which systems, and where the time goes.
- Picking the right candidates. High volume, repetitive, rule-based enough to check, costly when done by hand.
- Choosing the tool level. A no-code workflow, an AI assistant connected to your data, or a custom agent.
- Building and testing. On your real documents and edge cases, not on a demo dataset.
- Human checkpoints. Deciding what the automation does alone and what it submits for approval.
- Running it. Monitoring, fixes, and changes as your process or the AI models evolve.
Advisor, freelancer or builder: what you are really hiring
| Strategy advisor | No-code freelancer | Atlas (consultant who builds) | |
|---|---|---|---|
| Deliverable | Report and roadmap | A workflow in Zapier, Make or n8n | Software or agent in production, with its code |
| Handles messy inputs (scanned PDFs, free-text emails) | Out of scope | Often stops there | Yes, with AI extraction and checks |
| Tests before launch | Not applicable | Rarely | Written tests on our production software, acceptance on your real cases |
| After launch | Not included | Ad hoc | Monthly plan: monitoring, fixes, updates |
| Best for | Large programs, board alignment | Simple app-to-app glue | Automations that touch your core work |
No-code tools are good, and we use them when they are enough. We step in where they stop: badly structured documents, decisions that need judgment, and processes that run on your ERP or CRM.
Examples of automations we have built
- Purchase orders to ERP import. A French tableware and cutlery manufacturer received customer purchase orders as PDFs in many layouts, and the sales-admin team re-typed them into the ERP. We built a web tool that reads the PDFs and produces the ERP import file. Recurring layouts go through dedicated parsers with no AI at all; unfamiliar ones go through OCR, then a language model as a fallback. It has been in production since January 2026.
- Accessibility audits from a URL. One of our own products tests a website against 57 criteria of the French accessibility standard: 44 are checked by code and 17 by an AI model, then the tool drafts the four legal documents.
- Regulatory review of product pages. Another product reads an ecommerce product page and flags risky health or cosmetic claims with their regulatory source, then proposes replacement wording. It flags; it never decides for you.
- A company run by agents. We run our own operations with 14 AI orchestrators (12 active today) and 21 scheduled jobs. From October 2 to October 7, 2026 they completed 300 runs, 298 of them successfully. The full story is in our AI-run company case study.
How an engagement runs
- A 30-minute call to see whether your process is a good candidate.
- A discovery workshop, recorded and transcribed with your permission, so nothing said gets lost.
- A written quote: a fixed build price, plus an optional monthly plan for running and maintenance.
- A specification you approve before development starts: inputs, outputs, edge cases, approval points.
- Short sprints with a working demo at each step, then acceptance testing on your real cases.
- Launch and monthly plan: monitoring, fixes, and adjustments as your business changes.
The engineering side of this is detailed on How we work. For agents specifically, see AI agent development.
How much does an AI consultant cost?
AI consultants usually charge by the hour or the day for advice, and by the project for implementation. For an automation, the number that matters is the total: what it costs to build, what it costs to run each month, and what it costs to keep working.
We quote a fixed price for the build and a monthly plan for running and maintenance, so you know the full cost before anything starts. Our AI agent cost guide breaks those three lines down and explains what makes them go up or down.
How much do AI consultants get paid?
Pay for AI consultants varies widely with experience, location and whether they advise or build. For a buyer, the more useful question is what you get for the money: a recommendation, or software running in production.
How much does an AI automation specialist make?
Salaries for AI automation specialists depend on the market and the depth of engineering involved; hands-on profiles who can build and maintain integrations are paid more than tool operators. If you are comparing hiring someone with working with an outside builder, our page on hiring an AI developer lays out the options side by side.
Who you will work with
Atlas Software Partners is a small engineering studio based in France that works remotely with international clients. The same senior engineer runs the discovery, writes the specification and leads every build, using AI coding agents under the guardrails described on How we work.