Ask Your Data Questions—Get Instant Answers in Plain English

Eliminate the bottleneck of SQL queries and analytics requests. Empower every team member to get data-driven answers instantly using natural language—no technical skills required.

The Data Access Bottleneck

Most employees can't access business data when they need it. They face a frustrating choice:

Wait for IT/Analytics

Submit a request to the analytics team and wait days or weeks for someone to write SQL queries and generate reports. By then, the business decision has already been made without data.

Learn Complex Tools

Spend months learning SQL, database schemas, and BI tools just to answer basic questions. Most employees never invest this time, so they remain data-blind.

Make Uninformed Decisions

Proceed without data insights, relying on intuition and past experience. This leads to missed opportunities, preventable mistakes, and competitive disadvantages.

Overload Analytics Teams

Analytics teams spend 60-70% of their time answering routine questions instead of strategic analysis, creating backlogs and frustration on both sides.

How Natural Language BI Works

Ask questions in plain English, just like you would ask a colleague. AI translates your question into the right queries, retrieves the data, and presents visualized answers.

Natural Language Understanding

Advanced NLP models understand business terminology, context, and intent—recognizing what you're asking even with ambiguous or informal phrasing.

Example Questions You Can Ask:

"What were our top 5 products by revenue last quarter?"
"Show me customer churn rate by region for the past 6 months"
"How does our average deal size compare to last year?"
"Which marketing campaigns drove the most conversions this month?"
"What percentage of support tickets are resolved within 24 hours?"

Intelligent Query Translation

AI translates your natural language question into optimized database queries, handling joins, aggregations, and filters automatically.

You Ask:

"What's the average order value for customers who bought in the last month?"

AI Understands:

  • • Time filter: Last 30 days
  • • Metric: Average order value
  • • Table: Orders + Customers
  • • Aggregation: AVG(order_total)

Generated SQL:

SELECT AVG(o.total_amount)
FROM orders o
WHERE o.order_date >=
  DATE_SUB(NOW(),
  INTERVAL 30 DAY)
GROUP BY o.customer_id

You never see this—it happens automatically

Automatic Visualization

Results aren't just numbers in a table. AI automatically selects the best visualization type—charts, graphs, tables, or maps—based on your data and question.

Bar Charts
Comparing categories
e.g., Sales by region
Line Graphs
Trends over time
e.g., Revenue growth
Pie Charts
Proportions/shares
e.g., Market segments
Tables
Detailed records
e.g., Top 10 customers
Heatmaps
Patterns/correlations
e.g., Purchase behavior
KPI Cards
Single metrics
e.g., Total revenue

Conversational Follow-Ups

Continue the conversation naturally. Ask follow-up questions, drill down into specific segments, or change time periods without starting over.

Example Conversation:

You:
"Show me monthly revenue for 2024"
AI:
[Shows line chart with monthly revenue]
You:
"Break that down by product category"
AI:
[Shows stacked area chart with categories]
You:
"Which category grew the fastest?"
AI:
"Software Services grew 45% year-over-year, the fastest of all categories."

Democratize Data Access Across Your Organization

See how natural language BI can empower every employee to make data-driven decisions. Get a demo using your actual business data and ask any questions you want.

Business Impact

80% Reduction in Analytics Requests

Business teams self-serve routine questions, freeing analytics teams to focus on strategic projects and complex analysis.

Before: 200 requests/month → After: 40 requests/month

10x Faster Time to Insight

Get answers in seconds instead of waiting days for someone to write queries and generate reports.

Before: 3-5 days → After: 5-10 seconds

5x Increase in Data-Driven Decisions

When data is accessible to everyone, more decisions are informed by actual business metrics instead of intuition.

Data-backed decisions: 15% → 75% of strategic choices

Zero Technical Training Required

New employees can ask questions on day one. No SQL training, schema documentation, or BI tool certifications needed.

Training time: 40 hours → 5 minutes

Industry Statistics

65%
of employees can't access data they need for their jobs
$600B
lost annually due to poor data accessibility
70%
of analytics team time spent on routine queries

Who Benefits Most

Sales Teams

Get instant answers about pipeline, win rates, and customer segments without waiting for sales ops reports.

Typical Questions:
• Which deals are at risk of slipping this quarter?
• What's my team's average time to close?
• Show me prospects that haven't been contacted in 30 days
Impact:
• 30% more time spent selling vs. reporting
• Better forecasting accuracy
• Faster response to pipeline changes

Marketing Teams

Analyze campaign performance, channel effectiveness, and customer segments without technical marketing analytics skills.

Typical Questions:
• What's our CAC by acquisition channel?
• Which blog posts drive the most conversions?
• How has email engagement changed this year?
Impact:
• Optimize campaigns in real-time
• Reallocate budget based on data
• Test and iterate faster

Customer Success

Monitor customer health, identify at-risk accounts, and track engagement metrics without building complex dashboards.

Typical Questions:
• Show me accounts with declining usage
• What's our NPS by customer segment?
• Which features have low adoption?
Impact:
• Proactive churn prevention
• Data-driven account prioritization
• Better expansion targeting

Executive Leadership

Get immediate answers to strategic questions without routing requests through multiple teams.

Typical Questions:
• What's our burn rate trend?
• How do cohorts compare by acquisition quarter?
• What's driving margin compression?
Impact:
• Real-time business visibility
• Data-informed strategy decisions
• Independence from reporting delays

Frequently Asked Questions

How accurate is the natural language understanding?

Modern NLP models achieve 90-95% accuracy on business questions. The system improves over time by learning your business terminology and common questions. When the AI isn't confident about interpretation, it asks clarifying questions rather than guessing. You can also provide feedback to improve accuracy.

Can it handle complex multi-step questions?

Yes. The system can handle questions requiring multiple joins, aggregations, and filters. For very complex questions, it may break the analysis into steps or ask for clarification. Most business questions—even sophisticated ones—fall well within the system's capabilities.

What happens if I ask a question the system can't answer?

The AI will explain what it doesn't understand and suggest reformulations or alternative questions. It can also route complex requests to your analytics team automatically. Over time, these edge cases help improve the system.

How do you ensure data security with natural language access?

Natural language BI respects all existing database permissions and row-level security. Users can only query data they already have permission to access. Queries are logged for audit purposes, and sensitive fields can be excluded from natural language access.

Does this work with our existing data warehouse/BI tools?

Yes. Natural language BI integrates with standard data warehouses (Snowflake, BigQuery, Redshift), databases (PostgreSQL, MySQL), and can layer on top of existing BI tools (Tableau, PowerBI, Looker). It augments rather than replaces your current stack.

Give Every Employee Data Superpowers

Transform how your organization accesses and uses business intelligence. See natural language BI in action with your own data—no technical setup required for the demo.