u/FindingSecret942

The idea is to unify:

• geospatial intelligence
• entity/link analysis
• live sensor feeds
• AI-assisted workflows
• video + detection pipelines
• collaborative investigation tools

into a single operational workspace instead of forcing analysts to jump between disconnected systems.

Current stack includes:

• React + FastAPI
• PostGIS + Neo4j
• Kafka + Redis
• Leaflet + D3
• YOLO-based detection pipelines
• ontology-driven entity architecture

A big focus is India-native operational data layers (ISRO, disaster, geospatial, public intelligence datasets, etc.) and low-cost edge deployment concepts.

Still very early-stage and a lot is prototype/simulation right now, but I’d love feedback from people working in:

• OSINT
• GIS
• defense tech
• security engineering
• disaster response
• sensor fusion
• operational software

Main thing I’m trying to solve:
“How do you reduce analyst overload and unify fragmented operational data into one usable decision-support system?”

Would genuinely appreciate technical feedback, criticism, architecture suggestions, or thoughts on real-world use cases.

Hi everyone,

I’m a 20-year-old founder currently building ParadoxAI Lab, an AI-native operational intelligence and decision-support startup focused on defense, border security, and mission-critical environments.

At a high level, we’re building something conceptually similar to platforms like Gotham/AIP from Palantir Technologies — but with an India-first focus for defense and strategic operations.

The system we’re developing combines:

• multi-sensor fusion
• geospatial intelligence
• surveillance analysis
• autonomous threat detection
• AI-assisted operational reasoning
• mission coordination workflows

The long-term vision is larger than defense alone. We also aim to build AI-native enterprise operating systems that help organizations integrate fragmented data and operational workflows using AI.

Right now, we are in the prototype and infrastructure-building phase. I’ve been building aggressively with limited resources, and the biggest challenge at this stage is runway and strategic access.

I’m posting here because I’m looking for:

• early-stage investors
• defense-tech operators
• strategic advisors
• engineers/researchers interested in the space
• founders who’ve navigated deep-tech fundraising

I know this is an extremely ambitious problem space, especially from India, but I genuinely believe India will need sovereign AI-native operational intelligence infrastructure over the next decade.

Would love feedback, advice, connections, or even hard criticism from people who understand deep-tech, defense-tech, AI infrastructure, or enterprise systems.

Happy to share more details, demos, and roadmap privately.

Thanks.
— Anupam Singh
Founder, ParadoxAI Lab

I’ve been heads-down on a project for a few months and I'm hitting that wall where I can't tell if what I'm building is actually useful or if I'm just deep in a rabbit hole.

I'm trying to move past the "chatbot" phase of AI. I’m building a system that’s basically a reasoning layer for high-stakes decisions—like simulating the impact of a pivot or deconstructing a messy market entry into a workflow. Think Palantir-style logic but for early-stage teams.

I’m applying to YC soon and I’m terrified of pitching something that’s actually just a "toy" in disguise.

I don't have a landing page or anything to sell, I literally just want to know: as a builder, would you actually use a "reasoning OS" to map out your strategy, or do you just trust your gut?

If anyone is working on something complex right now and wants to see if my logic-engine actually holds up (or if it's total BS), I’d love to get some honest feedback. No links, no fluff, just want to talk to people who are building real stuff.