About QuerySafe
We started with a question.
Why should getting an answer from business data require knowing where that data lives?
Years of working with analytics through MetricVibes exposed a recurring problem. Organizations had data, dashboards, reports and analytics tools. Yet new questions still created new work.
QuerySafe emerged from the belief that interacting with business information could become dramatically simpler. Instead of learning how the data is structured: ask what you want to know.
That idea became QuerySafe Intelligence. And QuerySafe Intelligence became the foundation for a broader vision.
Through MetricVibes
Years of analytics work across implementations, dashboards and reporting for businesses in several markets.
The pattern
The data existed. The answer still took time. Every new question meant another query, another spreadsheet, another request.
The question
What if people could simply ask their business?
QuerySafe Intelligence
A way to ask the data directly, beginning with BigQuery.
People
Built by people who have lived the problem.
Anuj Bansal
Founder, QuerySafe · Managing Director, MetricVibes
Anuj has spent years helping organizations across India, the Middle East, the UK, Europe and the US make sense of their data through MetricVibes, an analytics and MarTech consultancy. QuerySafe grew out of the problem he kept seeing: the data existed, but the answer still took days.
- Based in
- Noida, Delhi NCR, India
- Status
- In production with a large Indian public-sector energy enterprise
- Experience across
- India, Middle East, United Kingdom, Europe, United States
Why QuerySafe
We aren't trying to build another chatbot.
We're working toward an intelligence layer that sits between people, data and software.
| Traditional approach | QuerySafe direction |
|---|---|
| Search dashboards | Ask |
| Request reports | Understand |
| Write queries | Explore |
| Navigate applications | Decide |
| Move information manually | Act |
QuerySafe principles
QuerySafe principles
- Natural.
- People should communicate with technology in the way they naturally communicate.
- Contextual.
- Intelligence becomes useful when it understands the environment in which a question exists.
- Controlled.
- AI capability should respect organizational boundaries and permissions.
- Connected.
- Intelligence should work with existing business information rather than becoming another isolated tool.
- Adaptable.
- The platform should evolve as models, infrastructure and business requirements change.
- Independent.
- Our long-term direction is toward greater organizational control over where intelligence runs.