Large organisations already have the data.
Financial results, sales performance, operational KPIs, management reports, BI dashboards and years of historical information are often spread across data warehouses, reporting environments and business systems.
The challenge is no longer collecting information.
It is getting from that information to the right answer quickly.
Talk to Your Data is an enterprise AI agent developed by Solvership that connects conversational AI with an organisation’s existing data warehouse, reports and business information.
Instead of searching through dashboards, reports and tables, users start with the business question.
The business challenge
A simple management question can require a surprising amount of manual work.
Take: “Why did profitability decline in Q2?”
To answer it, someone may need to:
- find the right reports and dashboards,
- isolate the relevant KPIs,
- compare periods and markets,
- connect revenue, cost and operational data,
- validate that the numbers come from the correct source.
And once the data is found, it still needs to be connected into a meaningful explanation.
For organisations with large data warehouses and years of reporting history, this creates a familiar problem: the information exists, but accessing it still depends heavily on knowing where to look.
The solution: start with the business question
Talk to Your Data changes the starting point.
Instead of asking: “Where can I find that number?”, users can ask the organisation’s data directly.
For example:
- “What was our revenue in Q3 2025?”
- “How did margins change across our main markets over the last three years?”
- “What may have contributed to the increase in operating costs?”
The AI agent searches the connected enterprise sources and returns the relevant information in a structured way.
The organisation's own data remains the source of truth. The AI becomes the interface that helps users reach it faster.
From finding a KPI to understanding the bigger picture
The value goes beyond retrieving a single number.
If profitability declined, management will usually want to know what happened around it:
- Was the decline concentrated in one market?
- Did revenue change?
- Did costs increase?
- Were sales volumes lower?
- Did pricing move?
Was there an operational factor that changed at the same time?
Talk to Your Data helps users investigate those relationships by bringing relevant business information together across connected sources.
The AI does not make the business decision or automatically interpret correlation as causation.
Its role is to bring the evidence together so managers can investigate faster and make informed business judgements.
How Talk to Your Data works
The conversational interface is only the visible part of the solution.
Behind it is a controlled data and AI process designed around enterprise information.
1. Connect
Relevant enterprise sources are connected, including data warehouses, databases, reports and documents.
2. Prepare
Data is cleaned, structured and enriched with the metadata required for reliable retrieval.
3. Represent
Information is transformed into formats that can be searched effectively.
4. Retrieve
When a user asks a question, the system identifies the most relevant information across the connected sources.
5. Generate
Relevant enterprise context is provided to the language model.
6. Answer
The agent generates a structured answer grounded in the organisation’s own data.
This allows the user experience to remain simple while a controlled retrieval process operates behind the conversation.
Enterprise data requires enterprise-grade preparation
Connecting an AI model to a database or document repository is only the beginning.
Enterprise information comes in many forms.
Structured data may include warehouse tables, measures and historical metrics. Business reports can contain text and tables. PDFs and presentations may include important information inside charts, figures or other visual elements.
Each requires different preprocessing.
Talk to Your Data can include:
- visual extraction for charts, figures and graphs,
- table parsing for structured tabular information,
- semantic enrichment using relevant metadata and context,
- layout metadata mapping to preserve the structure of the original information.
Better-prepared data enables better retrieval and, ultimately, better answers.
Built around your existing enterprise environment
Talk to Your Data is designed to work with the technology environment an organisation already has.
The architecture is technology-agnostic and can be adapted to environments based on Google Cloud, Microsoft technologies, Snowflake or other enterprise platforms.
The solution can integrate with the organisation’s:
Enterprise data
Existing data warehouses and business information.
Custom processing pipelines
Pipelines designed to clean, format and preprocess specific datasets.
Security and access models
Existing organisational permissions and access rules.
AI and retrieval technologies
Secure databases, AI models and semantic retrieval.
The aim is not to replace existing data infrastructure.
It is to add an intelligence layer on top of the systems organisations have already invested in.
Security, traceability and control
A generic chatbot may be sufficient for a small number of documents.
Enterprise AI has different requirements. Organisations may be working with years of historical information, sensitive commercial data and multiple systems. Different users may also have different permissions.
At the same time, users need to understand where an answer came from.
Talk to Your Data therefore builds around key enterprise requirements including:
- private enterprise data,
- large knowledge bases,
- multiple data and document formats,
- connected information across years, markets and business areas,
- traceability to underlying sources,
- controlled access based on organisational permissions.
This keeps the organisation’s data and access rules under its control.
Enterprise AI has to be tested
Connecting the data and AI model does not automatically guarantee reliable answers. Enterprise AI requires continuous evaluation.
Test questions can include factual queries such as:
“What was operating profit in Q3 2025?”
comparative questions such as:
“How did revenue develop across our main markets over the last three years?”
and interpretative questions such as:
“What may have contributed to the margin decline?”
The testing process evaluates whether the right information was retrieved, whether the source structure caused problems, whether metadata needs improvement and whether retrieval logic should be adjusted.
The agent is then refined and tested again.
The business value
Talk to Your Data helps organisations get more value from the data infrastructure they already have.
Faster answers
Spend less time searching through reports and consolidating information.
Better access to enterprise data
Users can retrieve information by asking questions directly.
Faster comparisons
Analyse performance across periods, markets and business units more efficiently.
More time for higher-value analysis
Managers can handle more routine information retrieval themselves, while analysts can focus on deeper analysis and more complex questions.
Higher value from existing investments
Extend the usefulness of existing data warehouses, dashboards and reporting environments rather than replacing them.
From “Where is the data?” to “What is the data telling us?”
Most organisations have already invested heavily in collecting, storing and reporting their data.
Talk to Your Data adds a new way to use that information.
Instead of navigating systems first, users start with what they actually want to know.
The agent handles more of the search and retrieval across connected enterprise information, while people remain responsible for interpretation and decision-making.
Your organisation already has the data.
Let AI do the digging, and let people focus on the decision.