Data & Analytics

Query Your Business Data Like You’re Texting a Colleague

AI-Powered Analytics · No SQL Required

Query Your Business Data Like
You're Texting a Colleague

Stop translating business questions into SQL tickets. Our NLP analytics layer sits on top of your existing data stack and lets anyone — finance, ops, sales, leadership — ask questions and get verified answers instantly.

Built for enterprises running Power BI, Microsoft Fabric, Snowflake, or Azure.

80%
Faster time-to-answer
Zero
SQL knowledge required
100%
Works with your existing stack
Live Demo

See NLP Analytics in Action

This is what your team experiences — plain questions, instant governed answers.

Sunflower Lab — NLP Analytics Interface
💼 Finance Leader
CFO
What were our top 5 products by margin last quarter in the Midwest?
AI
Top 5 Midwest products by gross margin, Q4 2025:
Product A led at 68% · Product B at 61% · Verified against your Power BI model
CFO
How does that compare to Q3?
AI
📈 Sales Leader
VP
Show me win rates by rep for Q4, sorted lowest to highest.
AI
Win rate by rep, Q4 2025:
Rep Performance
T. Jackson22%
M. Torres31%
A. Singh44%
C. Brown58%
VP
What deals did T. Jackson lose to price objections?
AI
⚙️ Ops Director
Ops
Which production lines had the highest downtime last month?
AI
Top 3 lines by downtime, Feb 2026:
Downtime Summary
Line 4 — Chicago14.2 hrs
Line 7 — Detroit9.8 hrs
Line 2 — Columbus6.1 hrs
Line 4 accounts for 38% of total downtime. 3 unresolved maintenance tickets.
Ops
What's the cost impact of Line 4 downtime?
AI
Trusted By

Teams that stopped waiting for reports.

From manufacturing ops to healthcare finance — here's what business leaders say after deploying our NLP analytics layer.

★★★★★

"Our CFO now pulls her own revenue and margin numbers before board meetings. That alone justified the entire project in the first quarter. The BI team finally has time for real work."

JT
James T.
VP of Engineering · Mid-market Manufacturing
★★★★★

"We went from a 3-day reporting queue to self-serve answers the same afternoon. The NLP layer understood our Power BI definitions from day one — it felt like it already knew our business."

SK
Sarah K.
Head of Data · Enterprise SaaS
★★★★★

"The architecture review call gave us a clear picture of what we actually needed — no sales pitch. Within 6 weeks we had operations asking their own questions directly against our Snowflake data."

PM
Priya M.
Director of BI · Healthcare Operations
35+
Enterprise deployments
6 wks
Average time to first answer
4.9/5
Client satisfaction score
Manufacturing · Healthcare · SaaS
Industries served
What Is It?

Natural Language Data Analytics — Explained

Natural language data analytics is the ability to type or speak a business question and receive a chart, table, and written summary back in seconds. No dashboard navigation. No analyst ticket. No waiting.

Instead of your team learning how your data is structured, the AI learns your business — and translates questions into precise, governed queries against your real data.

The result: anyone in your organisation can be their own analyst, without any of the risks that come with unsupervised data access.

1

Your Governed Data

Power BI semantic model, Snowflake, Fabric — your single source of truth stays intact

2

NLP Interpretation Engine

Maps plain-English questions to your exact business logic — no hallucinated metrics

3

Verified Response Layer

Returns the right visualisation + plain-language summary, validated before delivery

Who It's For

Every team. One analytics layer.

Your BI team shouldn't be a bottleneck for every department. NLP analytics gives each team the data access they need — on their own terms.

💼
CFOs & Finance Leaders

Pull numbers before any meeting

Access margin, revenue, and cost data in plain English — before the board meeting, not after a 3-day analyst queue.

⚙️
Operations Directors

Query ops data in real time

Ask about throughput, delays, or utilisation rates without touching a dashboard or filing a request.

📈
Sales Leaders

Own your pipeline data

Query win rates, pipeline health, and rep performance in plain English — without waiting on BI or RevOps.

🧠
BI & Data Teams

Stop fielding ad-hoc requests

Redirect time from repetitive report requests to high-value analytical work. Let the NLP layer handle the rest.

How It Works

Three steps from question to answer.

Step 01
💬

You ask in plain English

Type your question via a chat interface or embedded input. No SQL, no DAX, no dropdown menus. Just ask like you'd ask a colleague.

→ No technical knowledge needed
Step 02
🔍

The NLP engine interprets it

Your question is mapped to your actual governed business definitions — Power BI DAX measures, security rules, and data relationships — not generic LLM guesses.

→ Grounded in your business logic
Step 03

You get a verified answer

Results are validated before delivery and rendered as the right chart, table, or plain-language summary — safe to share with leadership immediately.

→ Ready to present, export, or act on
Why Sunflower Lab

What makes our NLP layer different.

Most AI analytics tools are generic — they query your data without understanding your business. Ours is built around your existing governance, security, and definitions from day one.

Grounded in your Power BI / DAX definitions

We mine your existing PBIX files and semantic model so the AI already speaks your business language — not a generic approximation of it.

Row-level security carries through

Power BI RLS is fully respected. The CFO sees company-wide numbers. A regional manager sees their territory only. Enforced at the model level, not the UI.

No rip and replace

We work on top of your existing stack — Power BI, Fabric, Snowflake, Azure. No migration, no downtime, no disruption to current dashboards or workflows.

Validated before delivery

Every query is checked for unauthorised access, missing RLS filters, and errors before it reaches your warehouse. No raw AI outputs delivered unchecked.

Leadership-safe summaries

Plain-language analytical summaries highlight trends, anomalies, and actions. Verified against your data model and safe to present without analyst review.

Consistent with your BI standards

Visuals match your existing Power BI design standards. Charts, colour schemes, and formatting stay on-brand — not generic AI-generated outputs.

Compatible Stack

Works with what you already have.

No migration required. Our NLP layer integrates with the enterprise data tools your teams already run on.

Power BI
Native DAX integration — queries run against your governed semantic model
Microsoft Fabric
Direct Lake mode — zero-copy queries on OneLake without data movement
Snowflake
Pushdown SQL — NLP queries execute natively inside your Snowflake warehouse
Azure Synapse
Serverless SQL pools — query structured and semi-structured data without ETL
Dynamics 365
OData connector — ERP and CRM entities mapped to natural language entities
Salesforce
SOQL abstraction — pipeline, opportunity, and account data queryable in plain English
dbt
Metric layer sync — MetricFlow definitions pulled directly as NLP query context
BigQuery
Slot-based compute — NLP queries scale with your existing BigQuery reservations
Azure Data Lake
Gen2 hierarchical namespace — queries across raw, staged, and curated zones
SharePoint / Teams
Embedded interface — ask questions directly inside the tools your team already uses
FAQs

Common questions answered.

What is natural language data analytics?+
Natural language data analytics lets business users query their data by typing plain-English questions instead of writing SQL or navigating dashboards. An NLP engine translates the question into a governed query against your actual data model, then returns a verified chart or summary as the answer.
Do we need to replace our existing BI tools?+
No. Our NLP analytics layer is built on top of your existing stack — Power BI, Microsoft Fabric, Snowflake, or Azure. Your current dashboards, reports, and data pipelines stay exactly as they are. We add a natural language interface on top of what you already have.
Is this the same as Microsoft Copilot for Power BI?+
Microsoft Copilot is a great starting point, but it works best when your semantic model is already clean, governed, and well-defined. We build and optimise that foundation first — then integrate NLP querying on top of it. Without a governed model, Copilot produces inconsistent results. We fix the root cause before adding the AI layer.
How is the NLP layer governed and secured?+
Every query passes through a validation layer before reaching your warehouse. Power BI Row-Level Security is fully enforced — each user only sees data they're authorised to access. We also audit query logs, implement rate limiting, and ensure no raw AI outputs are delivered without validation.
What data sources does it connect to?+
Power BI Semantic Models, Microsoft Fabric / OneLake, Snowflake, Azure Synapse, Azure Data Lake Gen2, Dynamics 365, Salesforce, dbt, BigQuery, and flat file / API sources. If your source isn't listed, reach out — we'll assess compatibility on your free architecture review call.
Get Started

Ready to let your team ask their own questions?

We'll map your current data stack and show you exactly how NLP analytics would work in your environment — in one 30-minute call.

No commitment. No sales pitch. Just a practical roadmap.

Book a Free Assessment
Published by
Ronak Patel

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