Use cases
See how organizations use thaink² to turn enterprise data into faster analysis, recurring workflows and decision-ready outputs.
Use cases
See how organizations use thaink² to turn enterprise data into faster analysis, recurring workflows and decision-ready outputs.
Customer use case
Belgatrans
Customer use case
Belgatrans
Customer use case
OVR PERFORMANCES
Customer use case
OVR PERFORMANCES
Industry use case
How an e-commerce wholesaler unified support, sales and customer data
Industry use case
How an e-commerce wholesaler unified support, sales and customer data
Customer use case
SCEI
Customer use case
SCEI
Industry use case
How a pharmaceutical wholesaler cut collection delays and stock issues
Industry use case
How a pharmaceutical wholesaler cut collection delays and stock issues
Customer use case
SOLéHo
Customer use case
SOLéHo
Start with the business problem, not the AI feature
The most useful enterprise AI projects usually begin with work that teams already perform.
A report that needs to be rebuilt every week. A KPI that someone has to monitor manually. A variance that repeatedly needs investigation. A forecast that depends on several datasets. A document that is difficult to find when a decision needs to be made.
These are AI use cases before they are technology projects.
Explore practical enterprise AI workflows
Our use-case library shows how thaink² can support real analytical work across reporting, forecasting, root-cause analysis, KPI monitoring, enterprise knowledge and decision support.
Each page focuses on one business problem and explains how an AI agent or workflow can help address it.
The objective is not to automate everything.
It is to identify processes where AI can reduce repetitive analytical work while keeping the relevant business context and human control.
From one task to a repeatable workflow
A useful use case should be repeatable.
It can begin with a person asking a question or with a condition being detected automatically.
From there, the agent can retrieve the relevant information, perform the analysis and generate the expected output.
Explore the use cases below to find the business workflow closest to the problem you want to solve.
Related Resources
Related Resources
Bring AI agents to your enterprise data
See how thaink² can work with your data, systems and recurring business workflows.
What types of business problems can thaink² agents address?
thaink² is designed for data- and knowledge-intensive workflows such as analysis, reporting, enterprise search, forecasting, root cause investigation and recurring business monitoring.
How does thaink² connect to enterprise data?
thaink² works with enterprise data and knowledge sources such as databases, business applications, documents and APIs. The exact integration path depends on the target environment and should be validated during implementation.
What is the difference between Exploratory Mode and Proactive Mode?
Exploratory Mode lets users ask questions, investigate data and refine their analysis interactively. Proactive Mode is designed for recurring or scheduled work, where agents can run workflows and deliver results without repeating the same manual process each time.
How are thaink² agents operated in production?
thaink² AgentOps provides monitoring, evaluation and usage/cost visibility so teams can understand how agents are running, assess output quality and track AI consumption.
Bring AI agents to your enterprise data
See how thaink² can work with your data, systems and recurring business workflows.
What types of business problems can thaink² agents address?
thaink² is designed for data- and knowledge-intensive workflows such as analysis, reporting, enterprise search, forecasting, root cause investigation and recurring business monitoring.
How does thaink² connect to enterprise data?
thaink² works with enterprise data and knowledge sources such as databases, business applications, documents and APIs. The exact integration path depends on the target environment and should be validated during implementation.
What is the difference between Exploratory Mode and Proactive Mode?
Exploratory Mode lets users ask questions, investigate data and refine their analysis interactively. Proactive Mode is designed for recurring or scheduled work, where agents can run workflows and deliver results without repeating the same manual process each time.
How are thaink² agents operated in production?
thaink² AgentOps provides monitoring, evaluation and usage/cost visibility so teams can understand how agents are running, assess output quality and track AI consumption.
What if your next analysis were ready before your next meeting?
Show us your environment and a use case. See how thaink² can query, monitor, and act on your data.
Our mission
Our vision
Move from data you look at to data that works continuously for your business.
We believe the next generation of Data platforms will do more than show what happened. They will monitor, explain, anticipate, and prepare decisions before some questions even need to be asked.
What is an Agentic Data Platform?
An Agentic Data Platform uses specialized AI agents to work with enterprise data. Unlike a static dashboard or a simple chatbot, agents can explore multiple sources, run analyses, generate visualizations, produce deliverables, and execute recurring missions.
What’s the difference between Proactive Mode and Exploratory Mode?
In Exploratory Mode, the user asks a question and thaink² runs the analysis on demand. In Proactive Mode, a mission is defined in advance: agents monitor the data based on a set schedule or specific conditions and automatically deliver the relevant results.
Do I need to know SQL to use thaink²?
Not for business use cases. Users can ask questions in natural language and get analyses, tables, charts, and dashboards without writing SQL queries themselves.
What data sources can thaink² connect to?
The platform is designed to work with the systems already in place across your organization: databases, data warehouses, ERP, CRM, APIs, files, and document repositories. Available connectors depend on your environment and use case.
What types of outputs can the agents produce?
Depending on the agent and use case, outputs can include analyses, tables, charts, dashboards, forecasts, alerts, summaries, and reports. The goal is to deliver an actionable result, not just a text response.
Can thaink² be deployed on our own infrastructure?
thaink² supports deployment options designed around enterprise requirements, including organizations that need greater control over their infrastructure, models, and data. Our teams help define the architecture that best fits the project.
Which part of the thaink² ecosystem is open source?
ApowerB is the open-source agentic framework developed by thaink². It enables technical teams to build and operate their own agents, with support for RAG, Text-to-SQL, multi-LLM setups, and APIs.
How do I get started with thaink²?
The easiest way to start is with a concrete use case: reporting, analysis, forecasting, document search, or monitoring. An initial session helps define the available data, expected outcomes, and the most suitable deployment approach.
Join our Discord community
Connect with builders, Data teams, and AI practitioners. Share ideas, get technical help, discuss agentic architectures, and follow the latest developments around ApowerB.
Our newsletter (Soon)
Data that takes action, straight to your inbox.
Field insights, agentic architectures, benchmarks, use cases, and the latest from ApowerB. Only what’s worth reading.
What if your next analysis were ready before your next meeting?
Show us your environment and a use case. See how thaink² can query, monitor, and act on your data.
Our mission
Our vision
Put the power of data in the hands of decision-makers.
Today, too many business questions still depend on an export, a dashboard, or the availability of a Data team. thaink² changes that by letting teams query their data directly, while agents handle the analysis and recurring work.
What is an Agentic Data Platform?
An Agentic Data Platform uses specialized AI agents to work with enterprise data. Unlike a static dashboard or a simple chatbot, agents can explore multiple sources, run analyses, generate visualizations, produce deliverables, and execute recurring missions.
What’s the difference between Proactive Mode and Exploratory Mode?
In Exploratory Mode, the user asks a question and thaink² runs the analysis on demand. In Proactive Mode, a mission is defined in advance: agents monitor the data based on a set schedule or specific conditions and automatically deliver the relevant results.
Do I need to know SQL to use thaink²?
Not for business use cases. Users can ask questions in natural language and get analyses, tables, charts, and dashboards without writing SQL queries themselves.
What data sources can thaink² connect to?
The platform is designed to work with the systems already in place across your organization: databases, data warehouses, ERP, CRM, APIs, files, and document repositories. Available connectors depend on your environment and use case.
What types of outputs can the agents produce?
Depending on the agent and use case, outputs can include analyses, tables, charts, dashboards, forecasts, alerts, summaries, and reports. The goal is to deliver an actionable result, not just a text response.
Can thaink² be deployed on our own infrastructure?
thaink² supports deployment options designed around enterprise requirements, including organizations that need greater control over their infrastructure, models, and data. Our teams help define the architecture that best fits the project.
Which part of the thaink² ecosystem is open source?
ApowerB is the open-source agentic framework developed by thaink². It enables technical teams to build and operate their own agents, with support for RAG, Text-to-SQL, multi-LLM setups, and APIs.
How do I get started with thaink²?
The easiest way to start is with a concrete use case: reporting, analysis, forecasting, document search, or monitoring. An initial session helps define the available data, expected outcomes, and the most suitable deployment approach.
Join our Discord community
Connect with builders, Data teams, and AI practitioners. Share ideas, get technical help, discuss agentic architectures, and follow the latest developments around aPowerB.
Our newsletter (Soon)
Data that takes action, straight to your inbox.
Field insights, agentic architectures, benchmarks, use cases, and the latest from ApowerB. Only what’s worth reading.