The Engine Behind Value-Driven Portfolios
Rvalor builds the quantitative engines behind fundamental analysis, multi-asset scoring and portfolio construction, then integrates them, and the agentic AI pipelines around them, into the workflows of investment funds, banks and wealth managers.
What We Do
Four services that put Rvalor's quantitative research and engineering to work inside your organization, from licensed valuation engines to agentic AI pipelines running in your own workflows.
Algorithms for investment funds
License our fundamental scoring, DCF valuation and multi-asset ranking engines, the same models that analyze over 2000 stocks, sovereign bonds and equity ETFs, delivered as data feeds or signals that plug into your investment process.
Tailor-made solutions for banks and wealth managers
Bespoke analytics, screeners and diversified-portfolio construction built around your mandates, asset universe and risk framework, integrated directly into your existing tools and workflows.
Agentic pipelines inside your workflows
We design, build and run agentic AI where it earns its place in an investment process: research and screening for funds, credit and onboarding documents for banks, client reporting for wealth managers. The pipeline plans the task, calls your data and valuation tools, verifies its own output and hands the result back, with every step traceable and reviewable.
Database management
We design, build and operate the data layer underneath all of it: ingestion from market, filing and macro sources, validation and normalization, and one governed store your analytics, APIs and reports read from.
Agentic Pipelines in Practice
What we build for each kind of client. Every pipeline runs on your data, calls your tools and leaves a trace someone can review.
Investment funds
- Research pipelines that read filings, transcripts and macro releases, then draft the first version of a note.
- Screening runs that combine our valuation engines with your own mandate constraints.
- Position monitoring that flags when the thesis behind a holding stops holding.
Banks
- Credit and investment memos assembled from internal data and public filings, with every figure sourced.
- Onboarding and KYC document pipelines that extract, validate and escalate the exceptions.
- Suitability and compliance checks run before a recommendation reaches a client.
Wealth managers
- Client reporting and portfolio commentary drafted per account, in your house voice.
- Proposal and rebalancing packs generated from our portfolio engine and your risk tiers.
- Meeting briefs pulled together from holdings, past notes and current market context.
How We Work
Four steps from a first conversation to a pipeline running in production, each one ending in a decision you make with real output in front of you.
- 1
Discovery
We map the workflow, the data behind it and the decisions it feeds, then agree on what success looks like and how it will be measured.
- 2
Pilot
A scoped pipeline on your data, in weeks rather than quarters. You judge it on real cases before committing to an integration.
- 3
Integration
We wire it into your stack: your data sources, your tools, your identity and access rules, your review and approval process.
- 4
Run and improve
We monitor accuracy, cost and latency, re-tune as your data and markets change, and hand over the documentation and training your team needs.
Built to Be Reviewed
Institutions do not adopt what they cannot audit, so every system we ship is designed for scrutiny from the start.
Traceable runs
Every step, prompt, tool call and source is logged, so any output can be reconstructed and explained after the fact.
Human in the loop
Checkpoints where a person approves, edits or rejects, with automatic escalation when the pipeline is not confident.
Your data stays yours
Deployment inside your perimeter or a region you choose, and no training of public models on your data.
Explainable models
Scores and valuations an investment committee can follow line by line, not black boxes.
An Example of What We Build
Our own platform, running live: daily fundamental analysis of over 2000 stocks, sovereign bonds and ETFs on the engines, pipelines and data layer described above. This is the work we then do inside client firms.
What We Can Do
Short recordings of capabilities already running on our platform. Each one can be rebuilt around your data, your asset universe and your brand.
Method Overview
What is taken into account for the analysis?
How is the Investment Score calculated?
The valuation potential is coupled with quality scores (earnings, debt, profitability and growth) into one Investment Score.
The Multi-Asset Portfolio Engine
Value stocks, sovereign bonds and inflation hedges: three sleeves, each scored with the same value discipline, combined so that no single economic regime sinks the portfolio. The same engine we tailor to institutional mandates.
Value Stocks & Equity ETFs
The growth engine. Stocks pass the same fundamental value screens as our comparators, and top-scoring equity ETFs fill the markets your picks don't cover.
Sovereign Bonds
The stability sleeve. Governments are ranked by our risk-reward model, based on the real yield they pay versus their fiscal, macroeconomic and institutional risk. Only quality issuers pass the gate.
Inflation Hedges
The protection sleeve. Commodity-producer theme ETFs diversified across precious metals, industrial metals, energy, materials and agriculture.
Built for Every Economic Regime
Each sleeve responds to a different combination of growth and inflation, so part of the portfolio is always working.
Growth Rises
Stocks and equity ETFs lead the portfolio.
Growth Falls
Sovereign bonds cushion the drawdown.
Inflation Rises
Commodity hedges protect purchasing power.
Inflation Falls
Bonds and stocks both benefit.
Conservative, moderate or aggressive: pick a risk tier and an investment amount, and the builder does the rest.
Build Your Diversified PortfolioThe Methodology Behind Our Algorithms
Value Discipline
Every model is grounded in a value discipline: an asset is worth the cash flows it can generate, and price should be measured against intrinsic value. This principle drives the scoring across stocks, bonds and ETFs and makes the output explainable to an investment committee.
Fundamental Analysis
Our fundamental engine integrates historical financial reports (income statement, balance sheet, cash flow), sector-specific factors, future growth, and macroeconomic trends to determine an asset's intrinsic value at scale, systematically and daily.
Intrinsic Value and Potential
Target prices are calculated from advanced discounted cash flow techniques and reflect intrinsic value. The ratio between target price and market price is the appreciation or depreciation potential, a transparent, comparable signal across an entire universe.
Sector Adaptation
Assets are analyzed within their specific sectors, accounting for unique characteristics, market dynamics, and cyclicality. A bank requires a different model than a tech company or a cyclical commodity producer, and our algorithms adapt accordingly.
Risk Control
Rigorous quantitative analysis of financials, exposure only to assets with sufficient margin of safety, and disciplined exit rules keep the tradeoff between risk and reward under control, an approach institutions can audit and rely on.
Multi-Asset Diversification
Value discipline doesn't stop at stocks. We score sovereign bonds on the real yield they pay versus their fiscal, macroeconomic and institutional risk, and equity ETFs on the fundamentals of their constituents. Stocks, bonds and inflation hedges then combine into one diversified portfolio built so that no single economic regime sinks it.
An investment process does not need more opinions. It needs the same discipline applied to more of the universe, more often.
Put our engines and AI pipelines to work in your firm
Whether you run a fund, a bank or a wealth-management practice, let's discuss which parts of your investment process are ready to be modelled, automated or rebuilt.