We start with one workflow
A specific case with a verifiable outcome, not a transformation plan.
IaGents AI-powered business automation
AI deployment consulting: we discover where to automate, run a pilot with a success measure, and operate agents with a person deciding.
Organizes the work and applies your rules
Report ready. Review the result before authorizing the next action.
We deploy AI in specific workflows at your company. We discover where automation is worth it, give people and agents the same knowledge, keep the decisions agents make, and put them to work with a person deciding. We call this practice IaGents.
One agent receives the request, another gathers context, and another executes or reviews. We design the coordination, persistent state, and tools so the workflow can continue, report progress, and recover from an interruption.
We start with a specific workflow and measure the result. We define what runs automatically, what needs approval, and what happens when information is missing. We then expand based on the data, permissions, and pilot results.

A specific case with a verifiable outcome, not a transformation plan.
We agree on what runs on its own, what gets approved, and who can change the rules.
Quality, cycle time, exceptions, and cost before and after, to decide whether to expand.
Start with a specific process. Then connect the tasks, teams, and systems around it.
Agents that prepare the work across your applications, and a person who decides what matters.
A guided interview turns what your team knows how to do into a specification that is ready for a decision.
A single, versioned, permission-aware source of knowledge that your team and your agents query the same way.
Stop rebuilding context across apps: Jarvis sorts your inbox and moves work forward.
What you decide with your agents is not lost when the session closes: it stays current until you change it.
We define what to automate, when a person should step in, and how to verify that the work is done correctly.
We review tasks, systems, volume, and current cost to choose where to start. We agree on scope, available data, and the success measure before development.
We deploy the workflow on a real process, validate it with users, and compare it with the baseline. We train the supervising team and define who approves, changes rules, and handles incidents.
We operate and improve the system under the agreed scope: results monitoring, cost reviews, connector updates, and expansion to new workflows. Support hours, responsibilities, and objectives are specified in the proposal.
We select a specific workflow, agree on data and permissions, and measure a pilot against a baseline. Results determine how to expand scope.
It depends on the workflow, data, and available permissions. We can connect anything from one recurring task to a process spanning teams and systems. The pilot establishes which steps can run independently and which require a human decision.
We start with your existing systems and evaluate their APIs, connectors, or MCP servers. Specific integrations depend on available access; you do not need to replace the entire environment to start.
Yes. Workflows can trigger from events or schedules at any time, and they are designed with limits, monitoring, and recovery. Support coverage and availability objectives are agreed separately for each deployment.
Tell us which tasks repeat, which tools your team uses, and where work gets stuck. We will define a first automation use case with you.