An AI agent takes over recurring work without removing judgment from your organisation. Your team gets time back, exceptions stay with the right people and the agent becomes part of your daily operation.
In this research step, we work with the people who know the process. We examine the problem, exceptions, data, systems, ownership and the outcome that matters.
Outcome
Three possible decisions: build, first improve data, a process or an integration, or do not proceed. Only a build decision leads to a concrete build plan.
We build the AI agent and connect it to the relevant systems and processes. The agent takes over the agreed work and passes exceptions to the people who need to decide.
Outcome
A working AI agent that becomes part of your daily operation.
Security, monitoring, management and human oversight are part of delivering every agent and keeping it running. We track how it performs, fix errors and improve it when processes or circumstances change.
Outcome
The next evidence-based investment: improve the agent, expand its work, build another agent or adapt the technical foundation when it demonstrably creates a constraint.
We start with the work that gets stuck and the result that demonstrably needs to improve. Sometimes an AI agent fits. Sometimes data, a process or an integration needs attention first. And sometimes not building is the best outcome.
These AI agents are already running or have been applied live. The foundation exists; systems, agreements and exceptions are investigated and configured for each organisation.
Reads and checks orders from email, PDF, portals or Excel and prepares them for the ERP. People decide on exceptions.
Explore OrderPilotLive at VHC JongensMatches supplier and competitor price lists to the company’s own range. Powered by MatchPoint.
Explore QuotePilotLive in useMakes supplier files and product data usable and flags missing fields. Powered by Origo.
Explore ProductDataPilotIn a free 30-minute conversation, we only determine whether the challenge is promising. If you choose to continue, the paid Prove session follows. We build and connect the agent only after a positive build decision, making it part of your daily operation.
That is the starting point. During the Prove session, we determine which systems, data sources and integrations are needed without replacing your IT landscape unnecessarily.
Security, monitoring, management and human oversight are part of delivery and ongoing operation. We track whether the agent is doing its job, where errors or exceptions arise and when human attention is needed. We agree the division of responsibilities between rb2 and your team in advance.
People who understand the process and its exceptions, access to relevant information and someone who can decide on scope and working methods. During the Prove session, we make the required time commitment concrete.
The Prove session has a fixed fee that you know in advance. The outcome is a substantiated decision: build, first improve data, a process or an integration, or do not proceed. A separate proposal with a fixed build fee follows only after a positive build decision. After that, a fixed monthly fee per agent covers management and improvement. There is no obligation to continue.
When the work has too little volume or repetition, the data is missing or no one owns the process. The outcome may be to improve data, a process or an integration first, or to do nothing. We will say so plainly.
In 30 minutes, we determine whether an AI agent is a meaningful solution. There is no obligation to continue.
Plan a 30-minute conversation