30 seconds vs 2 days
Ad-hoc questions get answered in seconds instead of queuing behind the analyst. No more "I'll get back to you on Monday."
BigQuery-Native AI Analytics
Klaviyo says ₹4L.
Finance says ₹1.2L.
Get the SQL-Grounded Truth in 30 seconds.
Platform dashboards inflate numbers. Analyst tickets take days. QuerySafe Intelligence runs the actual SQL on your BigQuery and shows you the answer with the query it ran. No data movement. No guessing.
Works with your warehouse
Google BigQuery
Snowflake
Redshift
querysafe@bigquery: ~
GROUNDED
Trusted by
The problem
Why your team can't get a straight answer
Four reasons it takes days to answer a question a five-year-old could ask.
Ask for the SQL
No hallucinations. Every answer comes from a real SQL query against your warehouse. Click to see the exact tables, columns, and query that produced it.
PII masked by default
Aligned with DPDP Act 2023 and GDPR. Customer names, emails, and phone numbers are masked at the query layer. Raw tables never leave your cloud.
Free your analyst
Repeat questions eat your analyst's week. Route those to QuerySafe so the data team can spend their time on the work that actually moves the business.
The Moat
Why you can't just paste a customer CSV into ChatGPT
General-purpose LLMs are great at drafts and terrible at warehouses. They lack schema context, hallucinate aggregations, expose PII to public servers, and choke on real data volumes.
Direct warehouse reads via read-only service accounts
Metric definitions pinned globally, not redefined per chat
Full audit trail: every query, every user, every table
| Capability | ChatGPT / general LLMs | QuerySafe Intelligence |
|---|---|---|
| Numerical accuracy | Fails on joins, invents stats | SQL-grounded aggregates |
| Metric definitions | Drift mid-conversation | Pinned per workspace |
| Data security & PII | Raw files to public servers | Stays in your warehouse, masked |
| Multi-source joins | Cannot join campaign events | Joins GA4, Klaviyo, orders |
| Audit trail | None | Every query logged |
Inside the product
What every answer looks like
Every result shows the source tables, the SQL it ran, and an explanation in plain English.
See the exact tables and SQL behind every answer
Source tables, rows scanned, date range, and the full SQL query that produced the result. Your data team can audit any answer in one glance.
- Source table references on every query
- Row counts and time range visible upfront
- Complete SQL shown alongside the answer
Insights without exposing customer identities
When you ask about top customers, QuerySafe shows aggregates and masked previews, never raw IDs or personal data. The privacy layer is on by default and works across every dataset you connect.
- Aggregate summaries instead of raw IDs
- Masked previews of sensitive fields
- Policy applies across BigQuery datasets
Who are my top 100 customers and how much have they spent with us?
Forecasts grounded in your real history
Project where the business is heading with bear and bull cases pulled from your own data. Every projection cites the historical pattern it learned from, so you can see why the model arrived at a number.
- Bear and bull cases from real history
- Year-over-year pattern matching
- Business insight in plain language
What revenue should I expect in March based on last year's pattern?
Customers
What founders are saying
From the teams already running QuerySafe Intelligence on their data.
★ ★ ★ ★ ★
"We tried other AI tools but the answers always felt like guesses. With QuerySafe Intelligence, every result comes back with the source tables and the exact SQL it ran, so my team can verify the numbers themselves. For a service business like ours, that level of grounding is the difference between using AI confidently and not using it at all."
★ ★ ★ ★ ★
"Our security team is usually the bottleneck on any new tool. With QuerySafe Intelligence, they signed off in one review. The engine runs on our BigQuery directly, our customer and order data never leaves our infrastructure, and every answer comes with a full audit trail. That made the conversation simple."
Fit check
Is QuerySafe Intelligence right for your team?
Three quick questions and we'll route you to the right next step.
Where does your business data live today?
How big is the business?
Where should we send your invite?
Pricing
Simple, per-workspace pricing
Annual billing saves 20%. Self-hosted Enterprise option deploys inside your own GCP project.
Standard
Starter
For teams that already have BigQuery and want it answerable in plain English.
$
499
/ workspace / month
or ₹39,000 / workspace / month
- Connect any BigQuery project (read-only)
- Natural language to SQL with full audit trail
- PII masking on by default
- Pattern-based forecasting
- DPA and SCCs available to sign
- Email support, 1 business day SLA
Enterprise
Self-hosted inside your own Google Cloud project. Zero data egress.
Custom
annual
Talk to us for scope-based pricing
- Deployed inside your GCP project / VPC
- Zero data egress, runs in your boundary
- Custom LLM routing (Gemini, Claude, OpenAI)
- SSO, SAML, custom audit log export
- Custom DPDP / GDPR legal review
- Named CSM, SLAs to spec
Book a demo
Pick a 30-minute slot
We'll connect QuerySafe Intelligence to a sample BigQuery, walk you through it on your kind of data, and answer one tough question you bring to the call.
No data movement, runs on your warehouse
Bring one question we'll answer live
No pitch deck, just the product
Book your 30-min slot
Pick a time below. We'll confirm by email and send a calendar invite.
Calendar not loading? Open it in a new tab
FAQ
Common questions
Does QuerySafe Intelligence move my data out of BigQuery?
No. QuerySafe Intelligence runs queries inside your own Google Cloud project using a read-only service account you control. Your row-level data never leaves your BigQuery warehouse. We do not copy, sync, replicate, or cache it on our servers.
How does QuerySafe Intelligence prevent AI hallucinations?
QuerySafe Intelligence generates SQL queries that are validated against your BigQuery schema before execution. Every answer is shown alongside the exact SQL, source tables, rows scanned, and date range used. If you don't trust an answer, you can audit it in one click. Answers are grounded in your data, not invented.
Do I need to know SQL to use QuerySafe Intelligence?
No. QuerySafe Intelligence translates plain-English questions into SQL automatically. Founders, marketers, product managers, and operations teams can ask their own data questions without SQL knowledge.
How long does it take to set up QuerySafe Intelligence on BigQuery?
Setup takes about 15 minutes. You create a read-only service account in your Google Cloud project, grant it access to the BigQuery datasets you want QuerySafe to query, and the product is live. No ETL pipelines, no infrastructure to install.
How much does QuerySafe Intelligence cost?
Plans start at $499 per workspace per month, or ₹39,000 per workspace per month. Annual billing saves 20%. Custom pricing is available for enterprise deployments. Book a demo for a quote.
Is QuerySafe Intelligence GDPR compliant?
Yes. QuerySafe Intelligence is GDPR-aligned and compliant with the India Digital Personal Data Protection Act 2023. A Data Processing Agreement is available to sign with every customer. SOC 2 Type II is in progress.
Can my security team audit what QuerySafe Intelligence does with our data?
Yes. Every query is logged with the user identity, the question text, the generated SQL, the tables and columns referenced, and the timestamp. The audit trail is exportable from the QuerySafe console. The service account access is read-only and can be revoked at any time. Full details on the Security page.
How does QuerySafe Intelligence handle PII?
PII fields are masked in results by default. Aggregated summaries are shown in place of raw customer IDs unless an authorized administrator explicitly enables raw-data access. The privacy layer applies across all BigQuery datasets you connect.
Who is QuerySafe Intelligence built for?
D2C brands, mid-market and enterprise companies that use BigQuery and want to give non-technical users self-serve access to their data without losing governance, security, or accuracy. Typical buyers are founders, heads of growth, revenue operations, and finance leaders.
What is the difference between QuerySafe Intelligence and Looker or Tableau?
Looker and Tableau are BI tools built for pre-modeled dashboards and governed reports. QuerySafe Intelligence is built for ad-hoc questions answered in seconds. Looker needs LookML modeling and dashboard authoring. QuerySafe answers natural language questions on the fly with the SQL shown. They can complement each other.