Introducing FinAilyse: Financial Markets Analysis as Fast as Your Brain
Ask any equity analyst or risk manager how they spend their day, and a surprisingly large portion of the answer will have nothing to do with actual analysis. It will involve downloading data from market data portals, reformatting it in Excel, building the right formulas, running calculations, fixing broken references, and — after all of that — assembling results into a presentable output. Hours of preparation for minutes of insight. The analysis itself, the part that actually requires financial judgement, often comes last.
This is the friction FinAilyse is designed to eliminate. Ask a question in plain language. Let AI do the mundane job. Free your time and brain for deeper thinking.
Why does “simple” GenAI fails in financial markets analysis?
Generic AI models are not designed for financial calculations. When you ask a publicly available chatbot to calculate something, it can produce results that look correct — well-formatted, confidently stated — but contain statistical errors that are difficult to spot without running the numbers independently. Even if the results turn out to be correct, there is no guarantee that they will be consistent when the same question will be asked in the future. For standard deviation, VaR, correlation analysis, or more complex scenario simulations, that represents an unacceptable degree of uncertainty.
How does FinAilyse work
You describe what you need in plain language — for example, "compare the risk-return profile of Tesla, Microsoft, and Nvidia over the past three years" — and FinAilyse handles the rest. It identifies the relevant instruments, retrieves the appropriate market data, performs the calculations, and returns an interactive result. No spreadsheet setup. No manual data download. No formulas to maintain.
The key distinction from “simple” chatbots is that FinAilyse never lets the AI perform calculations by itself. It does not “invent” market data based on its memory and training data. Instead, it retrieves market data from the sources you trust - public, licensed, or your own proprietary datasets. It builds the plan, and processing logic based on your natural language request. Calculations are executed outside of AI’s reach, eliminating hallucinations and exposure of your highly valuable data to external parties.
Core Capabilities
Market data coverage. In the demo version, FinAilyse connects to Yahoo Finance for global equities, and to Stooq.pl for the Polish market. In production - it can connect to any dataset you need, external or internal. Just type in natural language what data you need and for which time range.
Custom file uploads. Users who want to analyse the data of their own portfolios, files containing exposure to commodities or FX rates, or any other internal dataset in CSV or Excel format can upload it directly. The file can be used standalone or combined with external market data - allowing to make an instant link between your own dataset and market data, without the need to manually merge the two datasets.
Interactive visualisations and reports. By default, every analysis produces an interactive chart rendered directly in the browser — users can hover over data points, zoom into specific periods, and compare series without leaving the interface. For outputs that need to travel — risk committee packs, client-facing materials, internal documentation — FinAilyse generates static reports on request, saved as PNG or PDF files.
Multiple LLM providers. FinAilyse is not dependent on any specific large language model. You can select the model that fits your access policies, cost structure, and performance requirements without being locked into a single provider. If required, we can advise which model would best fit your needs.
Memory. Over time, FinAilyse builds a library of previously executed analyses. When a new request resembles something the system has already prepared — the same type of calculations, a similar risk metric — it proposes reusing that prior work rather than starting from scratch — no need for users to remember report names or restart analysis from scratch. This is, in practice, one of the most important benefits: it provides the accuracy and consistency of a human analyst working in excel, combined with the speed and flexibility of AI.
Persistent guidelines. Users can define custom instructions in pure natural language — preferred output formats, specific metric definitions, chart styles, or domain constraints that they want to apply consistently across every analysis that the system produces. No need to repeat context with each new request. No need to call IT to tailor the layout of reports.
Who this is for
FinAilyse is for practitioners who need reliable quantitative answers from market data without the overhead of building and maintaining analytical tooling themselves. Equity analysts running portfolio simulations, risk managers performing stress tests, or treasury teams monitoring interest rate exposures — the common thread is a recurring need for structured, accurate financial analysis delivered quickly and at a low cost.
The goal is not to replace financial judgement. It is to remove the preparation work that sits between a question and the data needed to answer it. The judgement remains yours.
As of now, FinAilyse is available in beta version for tests for selected entities. If you’re interested in learning more, please reach out to *skaminski@aibreaker.eu.*