The first question we receive when talking about automation is "how much does it cost?". It is the logical question, but asked too soon. Before talking about price, we need to talk about what you want to automate, with which systems, at what volume, and with what level of oversight. Without that information, any figure is fiction.
Why there is no standard price
Automating the email management of a company with twenty daily emails and well-documented systems is a different project from automating the client onboarding process of a company with five different systems and unstructured data. The price range between the two can be one to ten.
The variables that determine the cost
1. Process complexity. How many steps does it have? Is the input data always the same or does it vary? Are there exceptions requiring special handling? A linear process with structured data is much faster to develop than one with multiple decision branches.
2. Number of integrations. How many external systems does the automation need to connect to? Each integration has its own API, its own authentication, and its own particularities. More integrations means more development.
3. Current data quality. If data is well-structured and consistent, development is more straightforward. If there is inconsistent data or variable formats, a normalisation layer needs to be added.
4. Supervision and audit requirements. A system with detailed logging, alerts, and an audit panel requires more development than one that simply executes.
5. Maintenance and evolution. Is it a system built once and left fixed, or will it evolve with the business? The initial development cost varies depending on the architecture required.
Indicative ranges by project type
Without prior analysis it is not possible to give an exact figure, but it is possible to give reference frameworks by project type. These ranges include development, testing, go-live, and an initial monitoring period to ensure the system behaves correctly in production:
- Simple single-process automation (automatic response to a type of email, document generation, conditional notification): scoped projects with a single integration and linear flow. These are the fastest to implement and the first to produce a return.
- Multi-integration process automation (CRM + email + database + notification): complexity increases with each system to connect. Each integration has its authentication, API limits, and particularities. Development time grows non-linearly.
- AI agent with decision-making (request classification, contextual response, intelligent escalation): these projects include a natural language component that needs calibration, tuned prompts, and a quality evaluation system. They are more technically involved and require more iterations before going live.
- Integrated system with audit panel: when the client needs complete visibility of every execution — what the system did, when, with what result, and what errors occurred — a logging layer, alerts, and a monitoring panel are added. This is especially common in regulated projects.
Most projects we build for SMBs fall into the first or second category. The return on investment in those projects typically occurs within six months.
The hidden cost: what you pay if you do not automate
Calculating the cost of automation is easy. Calculating the cost of not automating is the part that is usually ignored.
Take any repetitive process in your business. Calculate how much time the team dedicates to that task each week. Multiply by the hourly cost of the people involved. That annual figure is what you are currently paying to keep that process manual.
To that you need to add the hidden costs: errors from distraction, delays from absences, bottlenecks that block other processes, and the opportunity cost of the time those people could dedicate to higher-value tasks.
Practical example: if a process takes three hours weekly from a person costing the company 2,000 euros per month, those three hours represent approximately 18% of their time — around 360 euros per month in labour cost dedicated exclusively to that task. In a year, that is more than 4,300 euros in human time spent on a process a system can execute automatically. The comparison speaks for itself.
Maintenance and evolution: the cost after development
A well-built automation does not need intensive maintenance, but it does need periodic attention. External systems change their APIs, language models are updated, client processes evolve.
The projects we deliver include documentation on how the system works, how to monitor it, and what to do if something fails. The goal is for the client to have independence to operate the system without depending on us for every query.
For projects that will evolve with the business, we offer maintenance agreements that include periodic adjustments, integration updates, and one consultation hour per month. Maintenance cost is usually significantly less than the initial development cost because the infrastructure is already built.
What can generate additional costs are scope changes that were not anticipated: new integrations, new decision branches, changes to the original process. These are budgeted separately when they arise. They are not surprises — they are new projects on an existing foundation, which is always more economical than starting from scratch.
Questions that do not work for requesting a quote
- "How much does it cost to automate my company?" — There is not enough information to answer.
- "What do you charge per hour?" — The hourly model incentivises slowness, not results.
- "Can you give me a price without seeing the process?" — Any figure without prior analysis has no foundation.
Questions that do make sense
- "Does it make sense to automate this specific process given its volume and structure?"
- "What realistic result can I expect in the first months?"
- "What happens if the process changes — is the system adaptable?"
How we approach the budget
The budget cannot exist without prior analysis. A price given without understanding the process is a number without foundation that only creates wrong expectations. That is why our process always starts the same way: before any figure, we have a 30-minute analysis call. We understand the process, the necessary integrations, the volume, and the objectives. With that on the table, we deliver a detailed budget with a clear scope, realistic timelines, and no hidden items — no surprises on the final invoice.
Frequently asked questions about the cost of automating with AI
Is it better to pay per hour or per project?
Per project, whenever possible. Hourly pricing incentivises slowness and transfers the estimation risk to the client. With project pricing, the provider assumes the risk of their own estimation and has an incentive to be efficient. The condition is that the scope is well defined before starting.
What happens if the scope changes mid-project?
Scope changes are normal and need to be managed transparently. If during development a need emerges that was not in the original scope, it is documented, the impact on time and cost is estimated, and a decision is made whether to include it in the current phase or a subsequent one. There are no surprises if there is communication.
Do I need a long contract or can I start with a small project?
You can start with a concrete, scoped project. In fact, we recommend it. The best way to evaluate whether the collaboration works is to build something real together. If the result is as expected, it is natural to continue with larger-scope projects.
Does the price include the cost of AI APIs (OpenAI, Anthropic, etc.)?
It depends on how the project is structured. In some cases the client has their own API credentials and bears that cost directly, which is usually marginal for SMB volumes. In other cases we manage it and it is reflected in the budget. It is always clarified in the proposal.
What guarantee is there that the system will work correctly?
All projects include a testing period with real cases before production activation. During that period the system is adjusted until the client validates that the behaviour is correct. We do not activate anything in production without that prior validation.
Can I automate if my data is in Excel or Google Sheets?
Yes. Google Sheets and Excel are two of the most common data sources in SMB automation projects. They are perfectly integrable as a data source, as a destination to write results, or as both. If the data is there and the process has structure, automation is possible without needing to migrate to any more sophisticated system.
How long does it take to implement an automation from scratch?
A simple single-process automation can be operational in one to two weeks. A medium-complexity project — with multiple integrations and decision logic — typically requires three to six weeks. More complex projects, with AI agents and an audit panel, can extend to eight to ten weeks. The factor that most accelerates or delays development is the client's availability to validate progress and the quality of the original process documentation.