Most "AI for equity research" tools are the same thing under the hood: an LLM bolted onto a financial data feed. Ask a question, get an answer. Great demo, shaky foundation.
We think the real unlock isn't a smarter chatbot; it's a stack. Four layers, each reducing noise and increasing decision confidence:
Data Platform the foundation of truth. Clean ingestion, knowledge graphs, and guardrails where every claim traces back to source.
Orchestration decides what actually matters now (which filing change is material, which analysis should run).
Workflows repeatable analytical processes that compound depth every time they run.
Agents synthesise and communicate, but never invent truth. They stand on the certainty built below them.
The shift: alpha isn't about who has the most data anymore. It's about who has the best system to turn data into decisions.
Hey Hunters 👋 Shams here, one of the makers.
Honestly, this started as a problem of our own. We were investing on the side, doing our own research, and tracking our own ideas. Then life got busy, and keeping up with everything we'd found just fell apart. The signal was there; we didn't have the time to stay on top of it.
So we started building agents to do it for us: surface ideas, dig into them, and follow up before the window closed. Coming from cybersecurity, it felt familiar. Pull scattered signals into one place and act before the moment passes.
That side project became KnowYourCompany.ai: a cognition platform to discover, research, and act on any of India's listed companies, with every claim cited to the exact filing, page, and line, so you never have to just trust the AI.
The lesson for us was that research isn't a time problem; it's a systems problem. You can't read 500 filings a day, but your stack can. It should be watching, filtering, and digging for you, so your time goes into thinking and deciding, not searching and verifying.
So I'm curious: what does your research stack look like today? Screener tabs, Telegram tips, a spreadsheet, Claude ? Drop it below. I'd love to compare notes on what's working and where things fall through the cracks.
Congratulations on the launch, guys!! The UX is pretty clean :)
The line-level citations are the standout for me. "Never just trust the AI" is exactly the right posture for anything touching money.
Curious about one thing: how often do the agents re-examine an existing thesis? Is it event-driven- a new filing drops and the agent re-checks or on a schedule? Would love to understand how it flags when something you already hold has quietly changed.
@naman_shukla Trust through transparency was one of the key pillars when we embarked on developing this product.
And yes – it's dynamically updated in real time with the latest filing we receive. It checks the recency as well as the document type before updating the thesis. Not all documents are the same.
p.s. You'd be surprised how often a company changes their EPS value in the financial results & then in the subsequent press release. :p
The link-back to filings feature is genuinely useful, made me trust the summaries way more than usual AI research tools. Coverage alerts sound promising too.
@arinburtakpq70 Thanks, Arin! Our aim is to give full visibility to investors as they deploy their precious capital.
Love the tech here. Even as a fresh product, it is (almost) bug free and so easy to use. For someone who finds to very difficult to read through finances and follow updates on news and markets, it is definitely going to take the edge off while investing. Looking forward to making the most of it.
@shubhransh_srivastav Really appreciate the feedback.
Pro tip – Switch on updates and stay up-to-date about all your investments.
Happy investing :)
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This is great! Will really help simplify my work to figure out which companies I should be invested in!
@aditya_bhattacharyya Thanks, Aditya, for the kind words! This is just the start. There is a lot more in the pipeline yet to come. Onwards and upwards !!