Transform Market Intelligence into a Decisive Advantage

Sosna brings data, analysis, research and intelligent automation into one structured environment, allowing users to understand markets, companies, sectors, risks and capital flows through a single operating layer.

The platform is built for teams who need context, not noise. It is designed to connect information across public markets, private markets, credit, transactions, ownership and macroeconomic signals.

Instead of forcing users to manually search through filings, reports, transcripts, news, presentations and market commentary, Sosna is designed to help surface the information that matters faster.

AI-assisted search, document intelligence and natural language querying can help users extract insights from large volumes of text, tables and structured data.

Users can query documents, summarise research, detect themes, identify sentiment, compare companies and generate clearer views of market developments without losing sight of the underlying source material.

Sosna is designed to support a broad view of public and private markets, bringing together company data, market data, ownership information, funding activity, fixed income data, macroeconomic indicators, transaction history and sector-specific research.

Rather than treating datasets as isolated silos, Sosna is structured around context. Public company analysis, private company intelligence, transaction activity, credit signals and macroeconomic developments are designed to sit within the same analytical environment.

This makes it easier to understand not only what is happening, but why it matters.

Private markets require more than surface-level company data. Sosna is being shaped to support deeper analysis across private equity, private credit, venture capital, real assets and investor activity.

The aim is to give users a clearer view of fundraising, investor commitments, fund performance, private company growth, sector exposure and market positioning.

By connecting private markets data with broader company, sector and macroeconomic intelligence, Sosna can help users follow the full investment journey from capital formation to deployment, performance and exit activity.

Credit risk is not static. It moves with markets, balance sheets, sector conditions, liquidity, refinancing pressure and investor sentiment.

Sosna is designed to support disciplined credit monitoring by bringing ratings, issuer developments, research, market data and early warning indicators into a more consistent workflow.

Users should be able to track issuers, sectors, counterparties and portfolios with a clearer view of changing credit conditions.

Peer analysis helps users compare financial performance, leverage, liquidity, debt maturity profiles, margins, valuation trends, rating movements, ownership structures and sector exposure.

This makes it easier to distinguish between company-specific risk and broader market movement.

During periods of volatility, this comparative view becomes especially important. Users can identify outliers, monitor relative deterioration, spot stronger performers and prioritise follow-up analysis based on the signals that matter most.

Sosna is designed to support sector-specific intelligence across financial services, insurance, real estate, energy, utilities, metals and mining, technology, media, telecommunications, commodities and related industries.

Sector coverage gives users a more practical understanding of the forces shaping markets, from regulatory change and capital flows to supply chains, commodity pricing, geopolitical risk and technological disruption.

Sosna is being built around practical workflow. The platform should support users who need to move quickly between research, analysis, modelling, reporting and presentation.

This includes the ability to export data, support Excel-based analysis, refresh models, create reports, share findings and maintain consistent internal processes.

For investment teams, credit analysts, executives and advisers, workflow efficiency matters. Reducing manual steps, avoiding duplicated work and improving the reliability of outputs can make the difference between being informed and being late.