Built by the engineers behind Ziqara's AI-native memory engine

It started at PennApps

We met at a hackathon while we were both at UPenn. Within the first conversation, we realized we were both itching to build something real—not just a side project, but an actual company that solves a problem too big to ignore.

Our skills just clicked. Nirav had already gone through the grind of running a Delaware C-Corp and knew the B2B SaaS world inside out. Neel was the backend architect who got excited about hard technical problems that most people would avoid.

At that hackathon, we shipped our first thing together. Nirav handled the full-stack work and product decisions. Neel built out the backend and infrastructure. It just worked. No friction, no awkward handoffs—we naturally complemented each other's strengths.

Every company has the same broken system

Before building, we talked to managers across different industries—tech startups, financial firms, consulting companies, universities. We asked them what's keeping their teams slow and why they're not adopting modern AI tools despite knowing they need them.

The same problems came up over and over:

• Information is scattered everywhere—Google Drive, Slack, email, Notion, Confluence, SharePoint
• Search doesn't work—traditional search matches keywords, not meaning
• AI tools can't access company data—ChatGPT is powerful but has zero context about your business
• Security blocks everything useful—companies are terrified of putting sensitive data into third-party AI tools
• Knowledge walks out the door—when employees leave, their entire knowledge base disappears

We realized this isn't a productivity problem—it's an infrastructure problem. What's missing is an AI-native memory engine that sits underneath all your tools and actually understands your business.

What we mean by AI-native memory

When we say AI-native memory, we don't mean another chatbot bolted on top of file storage.

AI-native memory is:

• Structured, connected knowledge built from your documents, chats, tickets, and meetings
• Continuously updated so the system never falls out of sync with reality
• Permission-aware by default, so answers always respect who can see what
• Searchable and answerable, so you can ask questions in natural language and get grounded, traceable responses

Most companies have storage. Some have search. Almost none have a fast, secure AI-native memory layer that AI can reliably think on top of. That's what we're building with Ziqara.

Deep technical builders who understand the problem firsthand

Two months from concept to enterprise-ready

We officially started working together two months ago, but we were both already solving similar problems independently before we met. When we connected at PennApps, we realized our visions aligned perfectly, so we merged what we'd built. About 40% of the work was already done between us.

Over the past two months, we've been working full-time—8-9 hours a day minimum, most days even longer. We're in different cities (Surrey, BC and Dallas, TX), but we're on calls constantly, doing long work sessions together and moving fast.

In those two months, we took the product from 40% to a fully polished AI-native memory platform that is enterprise-ready.

What we built:

• Near-zero data loss ingestion engine with parallel processing architecture
• The most accurate retrieval system on the market combining six different methodologies
• Enterprise-grade security with three-tier permission system and database-level isolation
• Native meeting intelligence with transcription, summarization, and permission-aware storage
• Real integrations with Google Drive, Slack, Microsoft Teams, OneDrive, Jira, Confluence

Beyond enterprise—reimagining how organizations learn and operate

We're starting with enterprise knowledge management because that's where the pain is most acute and the market is ready. But this is just the beginning.

The same architecture that powers Ziqara's AI-native memory for companies will transform education. Universities are stuck with Canvas, Moodle, and Blackboard—outdated learning management systems that are glorified file storage with discussion boards.

We're going to replace them with an AI-native learning and memory platform where students and professors interact with a shared institutional knowledge brain. Every organization—companies, universities, hospitals, governments—needs a system that captures, preserves, and makes accessible their institutional knowledge. Not just search. Not just storage. Not just AI chat. The complete cognitive infrastructure: AI-native memory for organizations.