VK_2018Q: Difference
How is it different from asking chatGPT paid subscription model? What is your underlying model, what is proprietary and how workflow moves? It seems this is wrapper built on top of foundational model.
Kai_Kavout
Dec 24, 2025A: Hello VK_2018
Kavout isn’t just “ChatGPT for finance.” We use foundation models, but we also layer in financial-market data, real-time quotes, and our own research engines so the output is grounded in investable signals—not generic text.
What’s proprietary is our domain layer: hundreds of proprietary factors and signals, plus financial know-how and workflows built specifically for investing (screening, portfolio factor analysis, optimization, and multi-signal interpretation). That’s the part you won’t get from a general AI subscription on its own.
Best,
Kai
Verified purchaser
so true looks like a wrapper of gemini and chatgpt as its just chatbot with a stock feed
Verified purchaser
Fair point — foundation models are part of our stack, just like ChatGPT/Gemini are built on transformers.
The difference is what’s around the LLM: Kavout runs proprietary research agents and workflows that use real-time market data plus hundreds of in-house factors/signals to generate structured, investable analysis (screening, multi-signal views, portfolio diagnosis/optimization).
Verified purchaser
What do you mean by research engine? Which data feeds are being used in real time and how is it different from, Robinhood data feeds. Give me few examples from hundreds of proprietary factors and signals and one end to end workflow explanation please.
Tier 3 is substantial investment so I need to understand your product.
Verified purchaser
Our “research engine” is the system behind the chat that pulls market/fundamental data, runs our in-house factors & signals, and routes your request through specialized AI agents (technical, fundamentals, sentiment, swing trade) to produce structured, decision-ready output.
Verified purchaser
What's background and experience of founders, who has given know how and how that has been incorporated in product? What high level architecture?
Verified purchaser
Our founders have many years of experience building AI products for finance and working with / managing large quantitative investment strategies. That institutional know-how is a big part of what drives Kavout’s approach and product direction.
Verified purchaser
Hello,
Can you tell me which data feeds you are using, is it scrapping using some RPA or subscription feed like Bloomberg. Again you didn't tell me how data feed (from practical perspective) is different from Robinhood. I also need few examples of factors and signals. This looks interesting, do you have some vacancy, I am in Texas.
Verified purchaser
Also why there are six research agents, what's job of each? Are they part of domain layer, what's high level architect?
Verified purchaser
Please check out this: https://www.kavout.com/research and https://www.kavout.com/academy/quick-guide