AI Agent for Analytics
Direct access to operational metrics
Eliminate reliance on data analysts and BI wait times. Query your operational database directly and get specific answers instantly, without writing a single line of SQL.

Static analytics slows down decision-making
Traditional dashboards answer the "what" but not the "why." When an anomaly arises, relying on data teams and navigating the SQL barrier delays diagnosis and paralyses operational optimisation.

With traditional dashboards
Question → Ticket → Wait
Hours or days to receive a personalised report.
Descriptive metrics
You know it's happening (AHT spikes), but not why.
Technical barrier
Requires SQL or BI experts to cross-reference variables.
Blind spots
Conversation content remains an unindexed "black box".

With the AI Data Analyst
Question → Answer
Direct consultation and results in seconds.
Root cause diagnosis
In case of any unforeseen query, the system transfers the question to a human.
Natural language
Chat interface to query your database.
Conversational data
Unstructured text becomes analyzable data.
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FEATURES
Query and indexing architecture
The technology that translates your questions into accurate data queries and ready-to-use charts.
![Search bar with placeholder text 'Ask a question about your data' and example queries: '[Agent] Resolution Time', 'Total of [Active Conversations]', and 'Total of [Tickets]'.](https://cdn.prod.website-files.com/67d188e7beaa8de43bd46fc0/69caa6c03e4dc36b51eb030f_Natural%20Language%20Querying%20(NLQ)_.avif)
Natural Language Querying (NLQ)
Instant translation of complex questions into SQL queries on the conversation history and Inbox metrics.
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Semantic indexing
Ability to quantify free text from chats to convert contact reasons and sentiment into structured data.
Conexiones superficiales
Capture, sale and after-sales without leaving the chat.
Conexiones superficiales
Capture, sale and after-sales without leaving the chat.
Conexiones superficiales
Capture, sale and after-sales without leaving the chat.
![Search bar with text '[Agent] Resolution Time' above a colorful vertical bar chart with three rounded bars in purple, pink, and orange gradient.](https://cdn.prod.website-files.com/67d188e7beaa8de43bd46fc0/69caa6c1deb4a7516b9ca9ac_Visualizacio%CC%81n%20dina%CC%81mica%20on-the-fly.avif)
Dynamic on-the-fly visualisation
Automatic generation of custom tables and charts based on your query, eliminating the rigidity of static dashboards.
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Root cause exploration (Drill-down)
Chain questions together to dig deeper into operational anomalies and pinpoint the exact origin of a problem.
Conexiones superficiales
Capture, sale and after-sales without leaving the chat.
Conexiones superficiales
Capture, sale and after-sales without leaving the chat.
Conexiones superficiales
Capture, sale and after-sales without leaving the chat.
Start automating beyond what you thought was possible
Stop waiting for reports.
Start querying your data directly.
We answer your questions
What is Hubtype's AI Agent for Analytics?
Hubtype's AI Agent for Analytics eliminates reliance on data analysts and BI (Business Intelligence, the team that analyzes data using SQL) wait times. You query your operational database directly in natural language and get answers instantly, without writing a single line of code.
Why isn't a traditional dashboard enough to understand what's happening in my operation?
A dashboard tells you what changed (for example, that resolution time went up), but not why. Hubtype's AI Agent for Analytics analyzes the context behind your chats to reveal the reason behind the metric, saving days of waiting on cross-referenced analysis.
Can it turn the content of thousands of conversations into measurable data?
Yes. Through semantic analysis, Hubtype processes the free text in your chats and converts contact reasons and sentiment into structured data. That turns an unruly volume of conversations from a black box into clear metrics.
Does a bot with a good technical score guarantee the customer is satisfied?
Not necessarily. Hubtype's solution cross-references technical quality criteria with actual customer satisfaction (CSAT), catching cases where a "technically correct" bot is creating dissatisfaction the company hasn't noticed.
Can it tell me if one of my AI agents needs more training?
Yes. Hubtype monitors the resolution rate and performance of each agent, identifying patterns and specific areas for improvement before the problem turns into customer complaints.











