Bandeau Previsio AI

A research infrastructure for markets that change regime

Previsio is an editor of adaptive market models. We produce market intelligence, not capital management: our models, signals and scenarios are exposed via API to professional or regulated partners, who remain the sole decision-makers for their use.

Research built on competition, not on a single model

We do not seek a model capable of predicting everything with certainty. Our infrastructure permanently maintains several tens of thousands of algorithmic hypotheses, confronts them with real market data, and continuously identifies the most robust behaviors in the face of changing market regimes (bullish, bearish, indecisive).

Question the obvious

We start from no market conviction a priori. Every algorithmic hypothesis is tested, measured, and continuously challenged based on its observed results.

Permanent competition

Several tens of thousands of algorithmic behaviors are simulated in parallel. A selection mechanism regularly identifies models whose behavior has best adapted to recent market conditions.

Continuous improvement

Models are continuously retrained from new market data and their own observed behavioral gaps.

Models, signals, scenarios

Previsio continuously builds adaptive market models. Each model has its own history, risk level, theoretical buy, sell or hold signals, and its own statistical characteristics. These models are exposed via API as a library: the professional or regulated partner selects, combines, filters or ignores models according to its own governance and risk rules.

Previsio produces. The partner decides. The partner executes.

A multi-market infrastructure

Our research work currently covers several analysis universes, at different stages of maturity.

Validated universes

  • · Crypto-assets
  • · French equities (CAC 40)

Research universes being integrated

  • · European equities — 72 securities
  • · American equities — 516 securities
  • · Index ETFs and thematic models — 23 ETFs (semiconductors, defense, space, Europe, environment, Asia, Africa)

Experimental observations, not promises

Over the last twelve months, certain sequential simulations performed on historical data showed differentiated behaviors compared to reference indices, both on the CAC 40 universe and on the crypto-asset universe.

These results are experimental observations on historical data. They do not prejudge future performance and do not constitute an offer to the public, a solicitation to invest, or a performance guarantee.

An infrastructure designed for professional or regulated partners

Previsio serves asset management companies, family offices, regulated digital asset service providers (PSAN/CASP) and other professional or regulated operators wishing to integrate into their own governance adaptive models, signals or scenarios from our quantitative research.

Member of acceleration programs

Previsio is recognized and supported by global tech leaders.

NVIDIA Inception Program

Member of NVIDIA Inception Program

The NVIDIA Inception program supports startups revolutionizing their industry through AI and Deep Learning.

AWS Activate for Startups

AWS Activate for Startup

AWS Activate provides startups with resources, technical support and cloud credits to accelerate their growth.

Our news

What a quantitative research infrastructure in production concretely represents

→ 700 active ML models simultaneously
→ 840,000 model portfolios simulated in continuous competition
→ 376 million theoretical orders generated
→ 146 million predictions calculated
→ An automated hourly pipeline, 24/7, across 12 asset universes (crypto, FR/US/EU stocks, ETFs)
→ Nearly 16,000 "champion" alpha strategies re-backtested each day
→ Over 140 constrained strategies \(maximum daily loss and drawdown)
→ And yes it's sure… lots of "secret sauce"!

Classical quantitative approaches share a structural flaw: they seek the best strategy. Our R&D lab on financial markets challenges this.

Usually, a market hypothesis, a calibrated model, optimized parameters. Then we deploy.
The problem is that markets don't stay in the regime for which the model was trained.
07/03/2026

We are pleased to announce that Previsio joins the NVIDIA Inception program and the AWS Activate for Startups program!

We are developing an adaptive AI capable of predicting and simulating complex systems linked to human behaviors.
05/07/2026

Can machine learning differentiate its behavior from market indices?

Our quantitative research is based on continuous competition between tens of thousands of algorithmic hypotheses. On CAC 40 and crypto-asset universes, our infrastructure currently features approximately 51 distinct models per market, tested against more than 234,556 virtual portfolios simulated on historical data.

These works are experimental observations on historical data: they do not prejudge future performance and do not constitute an offer to the public or a solicitation to invest.
03/13/2026

What if forecasting also meant understanding?

We are promised increasingly powerful predictive models: more data, more algorithms, more correlations. But predicting is not fortune telling! And certainly not understanding.
05/20/2025

On Thursday, April 24th we were at the recruitment fair of @DataScientest.com school to meet…

On Thursday, April 24th, we were at the recruitment fair of @DataScientest.com school to meet Data Scientist, Data Engineer and Machine Learning Engineer profiles who could join the Previsio adventure.

24 interviews with great profiles in speed dating mode, congratulations on the organization @Estelle MOLTO and @Kahina!

You were used to mediocrity, discover the excellence brought to group behavior prediction by Machine Learning

Let's focus on health through this article from the scientific journal Nature: published in 2023, this report illustrates the ability of ML to predict complex human behaviors by leveraging heterogeneous data and using advanced mathematical models.

Work hybridization is settling in: anticipating crowds in shops, restaurants and public services is becoming problematic

In light of the release this week of AREMIS Group's annual study on work hybridization, we wanted to examine its facts from the angle of consequences in the local economic fabric.

Meeting tomorrow's talent: Previsio at the DataScientest recruitment fair

On April 24th, Previsio participated in the recruitment fair of DataScientest school, meeting 24 candidates with diverse profiles in data science and machine learning. An opportunity to strengthen our team and share our vision of intelligent flow prediction.

Understanding human behavior through machine learning

A study published in Nature demonstrates the ability of machine learning to predict complex behaviors, such as barrier gestures during the pandemic, by integrating sociodemographic, psychological and political data. Previsio applies these advances to model attendance dynamics, offering reliable forecasts even in uncertain contexts.

Anticipating the unpredictable: AI for hybrid flows

As remote work redefines presence rhythms, traditional models struggle to predict actual office occupancy. Previsio relies on artificial intelligence and heterogeneous data to provide unprecedented visibility into flows, enabling facility managers and local businesses to optimize their resources and improve user experience.

Explore our model library

Are you an asset management company, a family office or a regulated operator and want to explore our model library? Contact the Previsio team.