Sencor

Inspiration

Most high-stakes research is still painfully fragmented. People bounce between search, PDFs, spreadsheets, notes, and chat tools, but still struggle to produce a source-backed point of view they can trust, revisit, and share. Sencor exists to turn messy research work into a durable, auditable research asset instead of another disposable AI answer.

I started working on Sencor on February 1, 2026. Today it is a working product and we are still pre-revenue. We have already used early feedback from PhD scholars at IISc to sharpen the workflow for both early-stage researchers looking for strong problem statements and advanced researchers trying to publish better work.

What it does

We are building Sencor, a platform that helps people create researchbooks for important decisions. A user can start with a question, a few links, or a PDF, and Sencor turns that into a structured body of work with chapters, cited sources, confidence signals, notes, and AI-assisted synthesis. The goal is not just to answer a question once, but to help teams build a reusable research layer around it.

How we built it

Our stack is Next.js 16, React 19, TypeScript, Express, MongoDB, Mongoose, NextAuth, and Dodo Payments. On the AI side, we use web agents and work with models including Gemini 3.1 Pro, GPT-5.4, GPT-4o mini, and Claude, depending on the workflow.

Accomplishments that we're proud of

I tested the product with PhD scholars at IISc, and those conversations were useful because they showed the same pain from a different angle. Early researchers were constantly searching for solid problem statements, while more advanced researchers cared about producing and defending publishable work. That gave me confidence this is a broad workflow problem, not a niche prompt problem.

What's next for Sencor

Companies like NotebookLM, Perplexity, Elicit, Consensus, AlphaSense, Tegus, and CB Insights all touch some part of this problem, and large incumbents could expand further if they wanted to. But most of them are optimized either for search, summarization, or data access, not for creating a living research artifact that a person or team can continuously refine.

Our advantage is focus. We are building around the workflow of turning research into structured conviction: chapters, evidence, memory, notes, collaboration, and outputs that can actually be reused in future decisions. If we execute well, we become the system of record for high-stakes research, not just another place to ask questions.