AskIndra

We live surrounded by environmental data (AQI numbers, weather charts, UV alerts) but still end up unsure what to do.

AskIndra was built to close that gap.

Instead of showing you more charts, AskIndra lets you ask questions in plain language: Is it safe to go for a walk right now? Should I exercise outdoors today? Do I need to take precautions during my commute?

Behind the scenes, AskIndra pulls real-time data from trusted air quality and weather sources, normalises it across providers, and translates it into clear, context-aware guidance based on your location and situation.

This project emerged from Bhaskar Labs, a new experimental space focused on Indic AI and culture-tech - technology grounded in local realities, not generic global assumptions.

AskIndra is early, evolving, and intentionally simple. We’re sharing it now to learn, improve, and build alongside the community.

✨ Key Features
🌍 Location-aware environmental guidance
Real-time air quality and weather insights, interpreted for where you actually are.
💬 Conversational interface
Ask questions in natural language instead of decoding AQI charts and indices.
🧠 Decision-focused, not data-heavy
Clear recommendations instead of raw numbers.
🔄 Normalized data from multiple sources
Consistent interpretations even when providers use different standards.
🔐 Privacy-first by design
Minimal data collection, encrypted storage, advisory (not prescriptive) guidance.

Excited to see AskIndra launch here.

What drew me to this project was its focus on decision-making, not data exposure. Environmental information often fails not because the data is wrong, but because it’s communicated without context or relevance.

AskIndra is an early but thoughtful attempt to rethink that layer—especially from an Indic AI perspective, where local conditions, density, and health impacts vary widely.

I’m particularly interested in how this could evolve for communities, public health use cases, and policy support. Looking forward to feedback and conversations from this community.

Hey Product Hunt 👋
I worked on the backend and data layer for AskIndra.

One of the hardest problems we ran into was inconsistency—different air-quality providers use different scales, thresholds, and update cycles. If we passed that directly to users, the advice would change unpredictably.

So a big part of the backend work was building a normalization layer that standardizes AQI and weather data into a consistent internal model before it ever reaches the user. The AI doesn’t invent anything—it interprets verified data and turns it into guidance.

We’d love feedback from folks who’ve worked with environmental or real-time data pipelines. What did we miss? What would you expect next?

Hi everyone! I worked on the frontend and interaction design for AskIndra.

Our biggest design constraint was avoiding the usual “dashboard trap.” Most environmental apps overload users with numbers and charts, so we intentionally chose a conversation-first interface.

Every screen, interaction, and response is designed to answer one question clearly, without asking the user to interpret metrics or learn new terminology.

This is still very early, and we’re actively experimenting with how much context is enough without becoming overwhelming. Would love thoughts from designers and UX folks on what feels clear vs. what feels missing.

Just tried the platform and love the idea. Most apps focus on showing data. AskIndra focuses on interpreting it. Instead of dashboards, you ask a question and get context-aware guidance you can act on.

Just tried AskIndra and this is surprisingly refreshing.

I usually check air quality through 2–3 different apps and still end up guessing what the numbers actually mean for my day. Being able to ask a simple question like “Is it okay to go for a walk right now?” and get a clear answer feels easier.

It’s early, but I like that it doesn’t push charts or overwhelm you with metrics. Curious to see how this evolves, especially with forecasting and more personalized guidance. Following along 👍