Interactive Information Services

Agentic AI understands the intent behind a query and can perform tasks autonomously or semi-autonomously. It selects suitable data sources, tools and methods, executes multi-step processes and delivers context-aware results.

Unlike basic chatbots, it does more than respond to individual questions. It dynamically plans the steps required to complete a task.

Retresco provides ready-to-use agentic AI applications for publishing, editorial, commerce and information platforms.

The system understands search intent, considers conversational context, orchestrates internal and external data sources and delivers precise, real-time streaming responses. Results can include source references, filters, timeframes, tables and structured data.

The solution is particularly suitable for media companies, specialist publishers, digital commerce businesses and public sector organisations.

Retresco is designed for environments where extensive or distributed information repositories need to be made accessible through interactive services, and where up-to-date information, source quality, scalability and control are essential.

Conventional RAG systems often simply retrieve relevant text passages and pass them to a language model.

Retresco also analyses search intent and conversational context. Its agentic AI dynamically determines which datasets, search methods, filters and tools are required for a particular query. It can combine multiple sources, ask follow-up questions and present results in structured formats.

This transforms static retrieval into a flexible, agentic information process.

Each data source is connected, processed and made accessible through suitable search and retrieval methods.

For every query, agentic AI determines which sources, filters and methods are relevant. Conventional search, semantic retrieval, vector search, metadata filters and external tools can all be combined.

The most relevant information is then prioritised and brought together into a coherent, traceable answer.

Yes. Retresco combines your own content, such as article archives, databases, documents and product catalogues, with external information sources.

These may include weather, traffic, financial market, sport, event, election or product catalogue data. The AI system determines which sources to use based on intent, context, recency and access permissions.

Your own content is particularly valuable and reliable, but it often covers only a limited range of information.

External data sources complement it with up-to-date, domain-specific and professionally maintained information. Source citations, timestamps and metadata ensure that results remain transparent and traceable.

New and updated content can be processed in real time or near real time, depending on the data source.

Timestamps and metadata indicate how current the information underlying an answer is. This enables agentic AI to reliably incorporate the latest developments.

Retresco can be integrated into existing systems via API or the Model Context Protocol (MCP).

CMS platforms, archives, databases, document repositories and external interfaces are connected to the Retresco infrastructure. Agentic capabilities such as intent recognition, data orchestration, retrieval, streaming responses and structured output are available directly as a service.

No. Retresco can be integrated as the underlying AI engine within an existing frontend or deployed using a ready-to-use, responsive frontend widget.

This allows interactive information services to be embedded in websites, apps, online shops, editorial systems, intranets or customer portals.

Retresco is fundamentally model-agnostic. Retrieved information and structured results can be provided as context to different large language models, including those from OpenAI, Anthropic and comparable providers. Data preparation is optimised for low latency and efficient token usage.

Answers are delivered as real-time streaming responses and formatted according to the specific use case.

Supported formats include continuous text, lists, tables, comparisons, source citations, timeframes, filters and structured datasets. Downstream systems can display the results directly or process them automatically.

The cloud-native infrastructure is designed to handle high query volumes and extensive information repositories containing large numbers of documents.

Data sources, indexes and search processes can be scaled independently. Retresco manages infrastructure setup, operation, monitoring and continuous development.

Internal datasets are processed through dedicated content pipelines, indexes and endpoints.

Access rights, permissions and available information sources can be configured individually. Different customers’ datasets remain technically and logically separated.

Retresco makes usage and interaction data available through integrated dashboards or via API push.

Metrics can include frequently discussed topics, questions asked and left unanswered, interactions per session, response times, source clicks and content blind spots. These insights help organisations continuously optimise their information services.

Core components such as intent recognition, retrieval, data orchestration, streaming responses and structured output are already available as a service.

This means organisations do not need to develop a complete agent, search and data infrastructure from scratch. Retresco can be adapted to existing content, platforms, workflows and use cases, starting with a clearly defined initial application.