EXPLORE YOUR DATA DIFFERENTLY
Start with a business question—not another dashboard
Give retail and CPG teams a faster path from commerce data to contextual answers and better decisions.
Yarnit brings a commerce intelligence layer to enterprise data, allowing teams to explore performance in natural language. Ask a question, investigate what changed, drill into the drivers and uncover where to act next. Specialist AI agents work across your data, business definitions and analytical tools to deliver contextual answers—not simply generated SQL.
Retail and CPG teams have more data than ever. Getting a trusted, contextual answer still takes too long.
Dashboards explain what they were designed to show. Every new question creates another filter, report or request for the analytics team.
Generic BI tools can query tables, but they do not inherently understand products, categories, customers, stores, retailers, promotions or commerce KPIs.
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A performance change is only the starting point. Teams still need to investigate its drivers, compare segments and determine the next action.
A coordinated agentic workflow takes every question from business intent to a decision-ready answer.
Combine enterprise data, commerce context and coordinated AI agents in one governed analytical experience.
Give AI a working understanding of your products, categories, customers, channels, stores, retailers, promotions and commercial KPIs.
Connect business terms, entities, metrics and relationships so questions are interpreted in the context of how your organisation operates.
Translate complex business questions into accurate, executable queries across enterprise data models. Yarnit combines schema intelligence, semantic context, query planning and validation to improve NL-to-SQL reliability beyond literal text-to-query generation.
Present every answer in the most useful form—from comparisons and trends to concise narratives explaining what changed and where attention is required.
Move from a headline metric to its underlying drivers through follow-up questions that retain the context of the analysis.
A router, compiler and specialist agents coordinate intent interpretation, data retrieval, SQL generation, validation, visualisation and response creation.
Conversational BIallows users to explore business data by asking questions in natural language.Yarnit interprets the question, retrieves and analyses the relevant data, andreturns the answer as a chart, narrative or structured insight. Users can then askfollow-up questions and drill into the result.
A general chatbotgenerates responses from language and available documents. Yarnit’sConversational BI is connected to governed enterprise data and uses analyticalagents, business context and validated queries to calculate its answers.
Yarnit adds acommerce intelligence layer that understands entities and relationships such asproducts, SKUs, categories, customers, stores, retailers, channels, promotionsand commercial KPIs. This helps the system interpret questions in the contextof retail and CPG operations.
Yarnit interpretsthe business question, identifies the relevant metrics and dimensions, mapsthem to the underlying data model, generates the query and validates theresult. This combination of context, query planning and validation deliversgreater reliability than generating SQL from the question alone.
Yes. Users cancontinue the analysis without starting again. They can change the time period,compare regions, filter a customer segment or drill from a category intoindividual brands and SKUs while retaining the context of the originalquestion.
Depending on thequestion, Yarnit can generate charts, tables, KPI summaries, comparisons andwritten narratives. It can also highlight important drivers, anomalies andareas that merit further investigation.
Yarnit canconnect to relational databases and modern enterprise data platforms, includingSnowflake and Databricks. The specific connection model depends on thecustomer’s architecture, security policies and data governance requirements.
Yes. Yarnit cansupport deployment within the customer’s cloud, virtual private cloud oron-premises environment when required for security, governance or dataresidency.
Notnecessarily. Yarnit can complement existing dashboards and reporting tools byproviding a conversational exploration layer for questions that are not alreadyanswered by predefined reports.
The solution canuse governed metric definitions, access controls, context graphs, ontologiesand app contracts. Queries and analytical steps can be made traceable so userscan understand the data and logic behind an answer.
Give retail and CPG teams a faster path from commerce data to contextual answers and better decisions.
Giving shape to intelligence
