Your questions, answered clearly.

An agent can prepare or carry out tasks using authorized information and tools. Start with a specific process, a clear goal, boundaries and success criteria.

RAG supports retrieval and answers grounded in sources. A copilot helps a user at work. An agent can also carry out a sequence of steps and use tools within a defined scope.

No. Rules, a form or a conventional integration may be sufficient. AI is useful when a step involves interpreting content or handling variable situations, with appropriate controls.

Start with a recurring problem, accessible data and an observable result, such as finding information, preparing a response or processing a request. Discovery checks whether AI is suitable and identifies dependencies.

The level of review depends on the context and the consequences of an action. Some tasks can be automated; others should remain subject to review. Permissions and checkpoints are defined during discovery.

Yes. Product engineering covers building and evolving applications, integrations and software modernization. AI may assist parts of the development process without becoming a mandatory product feature.

The Studio supports the journey from an idea to a usable product: use-case discovery, user experience, architecture, development and evaluation. Deliverables and acceptance criteria depend on the project.

Yes. We start by understanding the product, its architecture and constraints. Changes may involve features, integrations, quality improvements or modernization of selected parts.

Define representative examples and business-specific criteria: usefulness, expected accuracy, sources, authorized actions and error handling. Tests should cover ordinary cases and situations where the system should ask for help.

They can help explore code, prepare changes or produce tests. Their use must follow project rules. Architecture decisions, reviews and release approval remain assigned to identified people.

A project with defined goals and deliverables, engineering capacity integrated into your team, or technical leadership support. The choice depends on what you want to build and your existing capabilities.

Yes. Responsibilities, tools, review practices and communication with decision-makers should be clarified. The aim is to fit into your way of working and identify useful adjustments.

When senior perspective is needed to prioritize technical decisions, assess an architecture or structure an engineering organization. The engagement may include an assessment, a roadmap and support for decisions.

Yes. Discovery or a first increment can help test assumptions before expanding the project. Even this initial scope should have a goal, acceptance criteria and explicit boundaries.

They depend on scope, existing systems, integrations, data and expected responsibilities. The first conversation clarifies these points so that a suitable proposal can be prepared, rather than promising one timeline for every project.

The project should specify authorized sources, identities, permissions and actions. An AI system should not receive additional access merely because it can use tools.

Possible connections depend on APIs, access rights and constraints in your environment. Discovery confirms the required integrations and the adaptations needed before committing to them.

This is defined according to the tools, models, hosting and project requirements. It should be made explicit in the appropriate discussions and documents; no processing location or retention policy should be assumed.

Rights, deliverables and handover arrangements are governed by the engagement documents. Project-specific code, third-party components and their licenses should also be distinguished.

Define monitoring, incident handling, user feedback and ongoing changes. For an AI solution, also plan to reassess answers and actions when data, models or tools change.