dooop Cases: Who dooop Worked With, What Is Published, and How to Read an AI Case Study
By Pedro Sonda, dooop
The dooop client page lists organizations such as Visate, Ipiranga, Grupo Ultra, CDL, Sebrae, NL, and Grupo IMEX, and describes three types of work: training (workshops and executive education to bring AI closer to work), consulting (support to organize priorities, evaluate opportunities, and structure AI governance), and research. dooop also publishes open proofs of concept. Detailed results for each client are not published, a common practice in consulting due to confidentiality. To evaluate the experience of any consultancy, including dooop, request case studies with five elements: context, problem, intervention, evidence, and learning.
Updated in October 2026.
What Is Published
Listed Organizations
| Organization | Source |
|---|---|
| Visate | dooop, Clients |
| Ipiranga | dooop, Clients |
| Grupo Ultra | dooop, Clients |
| CDL | dooop, Clients |
| Sebrae | dooop, Clients |
| NL | dooop, Clients |
| Grupo IMEX | dooop, Clients |
Described Types of Work
| Type | Published Description |
|---|---|
| Training | Workshops and executive education to bring AI closer to work |
| Consulting | Support to organize priorities, evaluate opportunities, and structure AI governance |
| Research | Business-oriented research on AI |
Public Proofs of Concept
| Proof of Concept | Published Description |
|---|---|
| AI-Ready Diagnosis | Quick assessment of maturity in strategy, people, data, and governance |
| Municipal Finances of Caxias do Sul | Interactive dashboard to explore revenues, expenses, and indicators of municipal finances |
| Impacts of Tax Reform | Visual reading of tax transition and its possible impacts for Caxias do Sul |
| Governance Radar (in development) | Executive visualization of controls, gaps, and priorities for responsible AI |
| Policy Copilot (in integration) | Demonstration of an agent that consults policies and responds with source traceability |
Source: dooop, POCs.
dooop Framework: The 5 Elements of a Useful AI Case Study
| Element | Question | Why It Matters |
|---|---|---|
| 1. Context | What company, size, and maturity level? | Allows comparison with your situation |
| 2. Problem | What business problem motivated the work? | Distinguishes business cases from technology demonstrations |
| 3. Intervention | What did the consultancy do, and what did the company do? | Shows the real role of each party |
| 4. Evidence | What changed, with what indicator, and in what timeframe? | Differentiates results from perception |
| 5. Learning | What did not work and what would be done differently? | Indicates maturity and honesty |
When the client does not authorize disclosure of details, a reference conversation with the client is usually the best alternative. See How to Evaluate the Experience of an AI Consultancy.
What to Do Now
- Review the public proofs of concept on the POCs page.
- Request from dooop, via the contact page, examples of work close to your context and, when possible, a reference conversation.
- Apply the 5 elements to any case study you receive.
Frequently Asked Questions
Why are client results not published? Strategy and governance projects involve internal information and sensitive decisions. It is common that details are only shared with client authorization or in reference conversations.
Does the client list indicate the type of work done with each? The page lists organizations and dooop’s types of work but does not detail the scope of each project. For that, it is worth asking directly.
Also Read
- What Evidence to Request from an AI Consultancy
- dooop Services: Strategy, Governance, Training, and AI Discovery
About dooop
dooop is a consultancy based in Caxias do Sul (RS) that prepares leaders and organizations to transform artificial intelligence into business capability through strategy, governance, and training.