you can actually trust.
Ask anything about your data. Get the answer, the chart, and the exact SQL + Python behind it — verified against your data, with no hallucinated numbers. From CSV to board-ready decision in 60 seconds.
REVENUE BY PRODUCT
SELECT product,
SUM(revenue) AS total
FROM df
GROUP BY product
ORDER BY total DESCConnects to the data you already have
- PostgreSQL
- MySQL
- Snowflake
- BigQuery
- Redshift
- Google Sheets
- REST API
- CSV · Excel · Parquet
The wedge no analyst tool gives you for free
Cohort retention,
vs a ~15% D2C benchmark.
Every D2C analysis surfaces an M0→M6 retention curve with a commonly-cited industry benchmark hairline. If you’re below it, the report tells you. Auto-derived from your orders + customers tables — no SQL needed.
⚠ M1 retention 18% — above benchmark, but the dropoff to 12% by M2 is the real problem.
Specialized pipeline · not chat-with-CSV
Five specialized stages.
Each doing what it's best at.
Generic AI tools throw one model at every problem. Workliq routes each stage to the engine that natively excels — deterministic maths where the number has to be exact, then a reasoning model for analytics, an executive writer for narrative, a refiner for polish, and a fast chat layer for follow-ups. Cost-aware: simple queries skip stages.
Data
DuckDB · scikit · SHAP · ARIMA. No LLM. Zero hallucination.
Analysis
Root cause. Confidence ranking. Statistical reasoning.
Executive
Board-grade narrative. Decision card. 90-day plan.
Refine
CEO-tier polish. Active voice. <22 word sentences.
Chat
Sub-second follow-ups. Interactive UX. Suggestions.
Cost stays ₹0 on free tier — most queries skip 3 of the 5 stages.
Capabilities
Six analyst-grade engines.
One simple chat.
Drop a CSV. Ask in plain English. Get the SQL, the Python, the chart, and the consultant-grade insight — in 60 seconds.
Pre-loaded with retail sales — no signup needed
Metrics vs diagnosis
A number is not an answer.
Knowing refunds rose 12% doesn't tell you which segment moved, how much of the change it accounts for, or what to do on Monday. Everything below is in the product today — verifiable on the live demo.
What a dashboard leaves you with
The questions a metric raises
- · Refunds are up — which products, which cohort?
- · Is this a real move or normal variance?
- · How much of the total change does it explain?
- · Is this number even correct?
- · What is the one thing to do next?
Answering these is the analyst's actual job — and where the hours go.
What Workliq returns
1 diagnosis. 3 ranked actions. Rupee tradeoffs.
Diagnosis · 85% confidence
PMF erosion — 4 co-moving symptoms
Next move: 30-customer cohort interview · ↑ ₹2.4L upside · 30-day reversibility
Why WorkLiq
Trust every number you ship
Checked Two Ways
Every number is recomputed by a second, independent method — deterministic SQL cross-checked against a pure-pandas pass. Answers come back marked Verified or Disputed. When two methods disagree, you see both, not a confident guess.
Says What It Doesn't Know
Each answer carries its confidence and the specific reason: sample below 30 rows, a model wrote the query, a summary claim it couldn't verify. Reports end with a "what we could not determine" section most tools never write.
Answers "Why", Not Just "What"
Revenue moved? It decomposes the change by segment, ranks what actually accounts for it, and states the counterfactual: had this segment held flat, the move would have been X instead of Y. Plus what-if projection on your own data.
Scientist-Ready
Picks the correct statistical test and tells you why it picked it. Compares several models on held-out data and names the trade-off. Segmentation, regression with SHAP, backtested forecasting.
How it works
From raw data to a clear decision in 60 seconds
s
from upload to a board-ready answer
Who it's for
See yourself in the product
Data Analysts
Stop writing the same SQL queries.
Ask in English, get verified results. See the exact SQL and pandas code behind every answer.
Startups
Get analyst-grade insights without hiring a data team.
Upload your CRM export or ops CSV. Board-ready insights in minutes, not days.
Researchers
Run real statistics without writing the code.
t-test, ANOVA, chi-square, regression — each with effect size and a plain-English read. Export-ready for your paper.
Students
Learn with real data — see the code behind every answer.
Every result shows the SQL and Python. The fastest way to actually learn data analysis, not just get an answer.
Pricing
Simple, honest pricing
Start with the demo — no account needed.
Starter
- ✓5 datasets
- ✓3,000 credits / month
- ✓SQL + Python output
- ✓Anomaly detection
- ✓Basic insights
- ✓All chart types
Pro
- ✓Unlimited datasets
- ✓12,000 credits / month
- ✓Full ML suite (regression, clustering)
- ✓ARIMA forecasting
- ✓Statistical tests
- ✓Email digest reports
- ✓PDF + Excel export
- ✓Shareable reports
Team
- ✓Everything in Pro
- ✓Team workspaces + RBAC
- ✓60,000 credits / month
- ✓14 connectors (DBs, Shopify, Stripe, Meta, Google, GA4)
- ✓Scheduled reports
- ✓Audit log (CA-ready)
- ✓Priority processing
INR today · USD & global card payments rolling out. A fraction of US-priced alternatives.
Early access
Built with feedback from early users
WorkLiq is in early access. We ship weekly based on direct feedback from finance teams, audit firms, and operators across India. Want to shape the product?
Join the early-access program→Stop guessing.
Start knowing.
Upload your first dataset free. No credit card, no setup fees.
SQL transparency · deterministic results · built in India 🇮🇳