In regulated industries, one of the greatest enemies of operational efficiency is not a lack of data, but its dispersion. Each enterprise system stores information in its own format, with its own logic and in its own language. Purchasing records live in one software, production parameters in another, analytical results in a third, and quality documentation in a fourth system. The problem is not that data is missing: it’s that no one really knows where it is or how to access it when it’s needed most.
Data archaeology: the real hidden cost
When an auditor asks for the full traceability of a specific batch, a race against the clock begins—one that brutally consumes resources. The quality manager must remember which system each piece of data was recorded in, which user credentials to use, which filters to apply, and how to export the information. This means opening multiple applications, logging into each with different credentials, and dealing with interfaces designed to capture data, not retrieve it.
According to McKinsey studies on digitalization, more than 60% of manufacturing companies still rely on manual processes to consolidate critical information. The result is that a senior technician spends between 4 and 8 hours manually reconstructing the history of a single batch. Not because they are incompetent, but because information silos do not communicate with each other.
The problem isn’t searching, it’s connecting
Once the data is located, the real challenge begins: manual integration. The technician must copy information from one system into a spreadsheet, cross-reference it with production records, look up analytical results in another tool, and verify that everything matches the quality documentation. Every manual transfer is an opportunity for error: a mistyped date, a misplaced decimal, a confused batch code.
This tediousness not only consumes time, it destroys the strategic value of analysis. When a team spends 80% of its time searching for and consolidating data, only 20% remains for what truly matters: interpreting, identifying patterns, and making decisions. Critical knowledge remains buried under layers of administrative work that add no value.
Lost origin: when no one knows where the data comes from
In environments with multiple disconnected systems, an even more serious problem emerges: the loss of data lineage. A value appears in a report, but no one can confirm with certainty whether it comes from a machine sensor, a manual entry, or a calculation in an intermediate spreadsheet. This opacity generates distrust in the data, multiplies validation time, and turns every audit into a nightmare.
The lack of clear data governance not only slows operations: it can compromise regulatory compliance and expose the organization to unnecessary risks.
Intemic: The intelligence layer that connects your systems
The solution is not to replace all existing systems, an expensive and unfeasible strategy for most organizations. Intemic acts as an intelligent integration layer that connects to your current systems and transforms them into a single searchable source through RAG technology.
With Intemic, instead of remembering which system holds each piece of data, you simply ask in natural language: “Show me the complete history of batch X.” The platform simultaneously searches across all your systems, retrieves the relevant information, and presents it in a unified format with direct links to each original source. Data lineage is transparent, searches take seconds instead of hours, and your team can dedicate its time to analysis, not data archaeology.
Transform fragmentation into operational intelligence with Intemic. Stop wasting time searching for data and start using it to make better decisions.
