Making market data ready for AI
Market data has to be aligned, defined and governed before an AI tool can be relied on to read it. Optia Data's approach is that AI interprets the question and governed data calculates the answer, so large language models are used as the interface, not as the system of record. Optia's view is that only organisations that have built a data foundation and context can expect an accurate answer when they ask AI a question.
Why the data has to come first
For Starbucks EMEA, Optia built an intelligence layer that reads the underlying reporting and drafts monthly commentary, with distinct perspectives for a brand manager, a strategic leader and a data specialist. It was built and tested against real market extracts.
That testing showed that where the underlying files were structured differently, AI could not make those inconsistencies disappear: the data had to be aligned first.
What Optia builds
Optia Data is a UK data and AI consultancy that harmonises syndicated market, retailer and internal data into governed commercial reporting. The first layer is one harmonised, analysis-ready baseline across retailer, syndicated and internal data.
On top of that, Optia builds a governed catalogue of definitions, business rules and lineage, giving standardised metrics and pre-calculated datasets so that an LLM has no room to invent numbers.
Optia can make harmonised data available through the Model Context Protocol (MCP), so Copilot and other AI assistants can query it under the same permissions, lineage and named-analyst accountability as the rest of the platform, where the data licence allows.
Can Copilot answer questions about market data accurately?
An AI assistant's answer depends on the data underneath it. When standardised metrics and pre-calculated datasets sit behind the assistant, the LLM has no room to invent numbers.
Check what your data licence allows before connecting any AI tool to syndicated data.
The risks, and how Optia controls them
Optia uses AI agents in an attended setup to help write logic and processes, and does not deploy them to take autonomous, unattended decisions on client data. Every data exception is understood, corrected and validated by a person.
Optia does not use customer data to train generalised AI or machine learning models, and does not pass customer data to third-party AI or ML tools.
Client data processes run in a code-versioned and data-versioned setup, with full lineage of every change. Optia's processes are certified to ISO/IEC 27001:2022. Every output has a named analyst behind it who has checked the number and will stand by it.
Optia recommends predictive modelling, workflow automation or AI assistance only where it genuinely fits, and says so when AI is not the answer.
How Optia uses AI in its own work
Optia's analysts use an MCP connection between an AI assistant and Power BI to speed up DAX development.
See also: data preparation and cleansing.
Frequently asked questions
How can a food and drink company make its market data ready for AI?
Align the data first, then define it. Testing on Starbucks EMEA's real market extracts showed that AI could not make inconsistencies between differently structured files disappear. Optia Data builds a harmonised baseline and a governed catalogue of definitions, business rules and lineage, so that an LLM has no room to invent numbers.
Can AI tools like Copilot answer questions about syndicated market data accurately?
The accuracy depends on the data the assistant reads. Optia uses large language models as the interface, not as the system of record: AI interprets the question and governed data calculates the answer.
What are the risks of using AI to analyse syndicated market data?
Inconsistent source files that AI cannot fix on its own, and models left to invent numbers. Optia does not deploy AI agents to take unattended decisions on client data, and does not pass customer data to third-party AI or ML tools.