Service model and fees

Subscription model  

You pay a monthly subscription under a service-delivery agreement:  
We design, manage and maintain your AI agent- including architecture, prompt and context engineering, system integrations, guardrails and governance.

If you are not satisfied, you cancel at the end of any month.


Control, data processing and services:

1. Consultation and diagnosis:

We study the problem and determine whether an AI agent is the right solution. If it is, we analyse which type of agent is most suitable.

2. Design and proposal:

We design the architecture, select vendors and prepare a budget with an implementation timeline.

3. Technical implementation:

We develop the agent, its data, integrations and initial settings.

4. Evaluation and optimisation:

We run tests and, based on the results, iteratively optimise prompts, paramaters, settings etc.

5. Onboarding and deployment:

We ease adoption into your organisation without disruption or much training.  

6. Maintenance and support:

We manage updates, monitor performance and provide technical support.   

Build & release model

Upon successful completion of the evaluation and testing phase, a one-off invoice is issued in accordance with the software development agreement governing the AI agent.

Control over AI agent and data:
  • Upon delivery and payment you retain full control over the agent and its integrations, iAutomator retains no further access to them.
  • The evaluation and testing process is carried out using synthetic data. The connection of the agent to your repositories is carried out by you, after delivery.
  • iAutomator has no access to your data at any point in the process.

Automator remains open to negotiating hybrid models that combine elements of the previously described ones.

How much does an iAutomator AI agent cost?

Each agent is unique and designed for each company; your agent is built around your specific needs and the cost depends on several factors:
Functionality: The number and complexity of features is the most important factor.

Documentation:
If the information is already organised and in formats easily processed by AI, the cost is much lower than when it is disorganised, requires preprocessing or recognition steps.

Internal integrations:
If your systems are modern they will be easier to connect than legacy systems, which require more development and maintenance. In the case of very old systems, integration may not be possible.

External integrations:
If there is a native connection, integration is simple; if not, it depends on MCP servers or well-documented APIs.

Platforms, tools and models:
Prices vary according to the model, the platform and the cost of tools such as vector databases.