Fits
When yes.
- The company already uses multiple SaaS that need to talk to each other.
- There is a repetitive, high-volume task consuming qualified people's time.
- There is willingness to measure before and after deployment.
AI process automation.
Integrations, automations and agents connected to real business data, not to isolated demos.
Impressive demos appear every week and never reach production. The difference between a pilot that stays on the whiteboard and an automation that offloads real work is picking a case with a clear before/after metric, wiring it to the data the business already uses and assigning an internal owner to validate.
Cross-platform integrations.
E-commerce, accounting, ERP and payment gateways talking to each other without manual exports. Orders, invoices and stock reconciled.
Self-hosted automations.
Versioning, encrypted credentials and reviewable logs. No opaque components hosted by third parties.
AI agents, evaluated.
AI models connected to real business data (catalog, calendar, knowledge base), with prior evaluation of the use case.
Automation audit.
Retries, failure alerts, permissions and an assigned owner per workflow.
Doesn't fit
When no.
- The goal is to ship AI without a concrete use case.
- Processes are not internally documented.
- There's no room to tolerate mistakes in a pilot phase.
When does it make sense to apply AI in the company?
When several SaaS platforms already need to talk to each other, when a high-volume repetitive task is consuming qualified people's time, or when there is willingness to measure before and after deployment.
Do AI agents replace employees?
No. Agents are applied to repetitive, high-volume tasks so people can spend time on qualified work. Every case is evaluated before deployment with before-and-after metrics.
Can the infrastructure be self-hosted?
Yes. Automations live in the client's runtime with versioning, encrypted credentials and reviewable logs. No opaque components hosted by third parties.
When doesn't it fit?
When the goal is to ship AI without a concrete use case, when processes are not internally documented, or when there is no room for pilot-phase mistakes.
