Build financial intelligence. Keep the evidence.
Research, backtest, and deploy quantitative models on one platform. Every strategy carries a traceable record of its data, experiments, and paper trading. That shared foundation is how we are building toward a market for financial intelligence.
Live today: Research, backtesting, model registry, and monitored paper trading. Access by cohort.Building next: Capital access and portfolio construction. Real-money execution is not available.
Research and evaluation are live. Capital access is planned.
Illustrative evaluation record. Example identifiers; paper trading uses simulated fills.
The starting customer
More research. Less infrastructure to assemble.
Independent researchers and small quantitative teams need a reliable path from an idea to a model they can observe in a live market. Today that work spans data pipelines, notebooks, experiment trackers, backtest engines, and deployment scripts.
Promethean connects that workflow, with the evidence preserved at every step.
Build and test in one place.
Develop features, train models, and run backtests against point-in-time data. Trace a result to the code, data, and environment that produced it.
Observe the model after research.
Move a registered model into a monitored paper session on real market data. Inspect its behaviour, compare versions, pause it, and iterate.
Make the work reviewable.
Keep experiments, backtests, and model versions connected. A colleague can follow the work from a result back to the run that produced it.
Publish when you choose.
Marketplace listings connect a strategy to its evaluation record. Discovery is available; capital access and builder payouts are still being developed.
Start with your own research. The platform is useful before a strategy is listed or any capital enters the ecosystem.
From research platform to financial ecosystem
A useful product today. A larger market ahead.
The entry point is a complete research workflow for independent researchers and small quantitative teams. The same evaluation record that helps a team improve a model can help someone else assess it. Each stage builds on that foundation.
Development platform
liveA scientific ML environment for quantitative finance. Data, features, models, agents, backtests, deployment, monitoring: one system, one provenance chain.
Marketplace
discovery liveListings and evaluation records support discovery today. Capital access and builder economics are being developed.
Intelligent capital layer
directionWith many specialized systems in one ecosystem, a new question appears: how should capital be composed across them? This layer is infrastructure for portfolio construction over an ecosystem of intelligence.
Research creates strategies with evidence attached. Discovery makes that evidence useful to others. Over time, comparable observations could support portfolios built from many independent strategies.
The network
A market where evidence is the listing.
A strategy listing connects to the model version and evaluation record behind it. The aim is to give researchers a path to distribution and allocators a consistent starting point for diligence. Listings and discovery exist today; access for capital is the next stage.
For developers: a way to make research discoverable. For capital: a way to inspect how a strategy was tested before considering it.
The marketplace must earn trust through the quality of its evidence and the usefulness of its discovery.
Access for capital will be introduced in stages, beginning with structures suited to professional and institutional allocators, with each stage delivered through the appropriate regulated entity or partner. Access models may include subscriptions, flat fees, or performance-linked structures, subject to the appropriate regulatory framework. Promethean does not provide investment advice, manage assets, or act as a broker or adviser.
The larger problem
From individual strategies to portfolios.
As the ecosystem grows, evaluating strategies together becomes a distinct problem.
Which strategies work together, under which conditions, and within which constraints?
Portfolio construction requires evidence about how strategies behave together. A common evaluation environment could make those relationships easier to study.
Our long-term direction is infrastructure for selecting, combining, and monitoring strategies against portfolio objectives. Portfolio construction is in design; it is not available as a product today.
Promethean builds the infrastructure. Any product built on it for investors would be offered through the appropriate regulated entity. Nothing here is investment advice or an offer of any product.
Compounding
How the platform could become more valuable.
The first opportunity is distribution: useful research tools attract builders; credible strategies could attract allocators; access to capital could attract more builders. This is the network we aim to establish.
The second opportunity is learning from comparable evidence about how intelligence behaves across market conditions and in combination. With sufficient participation, observation history, and permission to use that evidence, the platform could improve how strategies are evaluated together.
These are advantages to earn as the ecosystem grows. The foundation today is an integrated research workflow and its record of evidence.
Technical depth
The evidence starts in the infrastructure.
One Python SDK connects data, experiments, backtests, and monitored paper deployment over a Rust core. The architecture preserves the context needed to inspect and reproduce a result.
Point-in-time correctness by construction.
Data is served as it was known at the moment a decision would have been made. Look-ahead is prevented in the read path.
Reproducible identity.
Every experiment is anchored to the exact code, data versions, environment, and seeds that produced it. Two runs can be diffed; any run can be replayed.
Backtests against the book.
Full-depth order-book simulation. Fills, slippage, and costs come from the state of the book.
Rust throughout.
Business logic lives in a Rust core; the Python you write is a declaration. Correctness under concurrent, multi-tenant load is a design property.
What comes next
Build adoption. Establish trust. Expand access.
Early access
Where do you enter?
Build on it.
You research, build, and deploy quantitative strategies, models, or agents. The platform is live; access is by cohort.
Request builder accessAllocate through it.
You represent capital (a family office, an emerging manager, an allocator, or, eventually, an individual investor) and want early visibility into how validated intelligence will be accessed.
Talk to usThis is a conversation. No product is offered.Partner with us.
Data providers, venues, research groups, and others who want to work with the platform.
Contact the founderPromethean is a technology platform. It is not a fund or an adviser.