Predictive market intelligence, trained from scratch.
Maphoros develops proprietary financial foundation models that transform petabyte-scale multi-dimensional data and emit machine-readable signals for live markets.
What we do
Models trained on our own corpora — not third-party API wrappers.
Our models are trained from scratch on our own corpora: billions of tick-level market events, decades of regulatory filings, real-time news wires, and alternative datasets.
Our architectures span multi-billion-parameter time-series transformers, sequence models trained directly on limit order book messages, and deep reinforcement learning agents for execution and pricing.
Every research cycle — from synthetic data generation to distributed pretraining to live inference — runs on cloud-native GPU clusters that we scale dynamically across regions.
Operational scale
Built for continuous, large-scale research.
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Multi-billion parameter
Foundation models pretrained in-house on financial time-series and unstructured global text.
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100+ GPUs
Orchestrated in scalable, clustered environments for training, experiments, and continuous inference.
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1,000+ simulations / week
Across our proprietary backtesting and synthetic-market generation environments.
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100% LLM-native
Every researcher and engineer ships against an internal agentic stack.
The platform
A single, vertically integrated AI platform.
Maphoros operates one stack — not a collection of disconnected scripts. Our internal stack is the product.
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Data Plane
Petabyte-scale ingestion, normalization, and feature pipelines for structured market data and unstructured global signals — filings, news, earnings call transcripts, supply chain logs, geospatial imagery.
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Model Foundry
Distributed pretraining and fine-tuning infrastructure for proprietary financial foundation models: multi-billion-parameter time-series transformers, microstructure sequence models, and multi-dimensional encoders.
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Simulation Engine
GPU-accelerated backtesting and synthetic-market generation that stress-tests strategies across decades of historical regimes and counterfactual scenarios.
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Inference Runtime
Ultra-low-latency model serving for live signal generation and execution, with continuous out-of-sample evaluation and model-drift detection.
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Agentic Research Layer
An internal fleet of AI agents that automate hypothesis generation, feature engineering, code authoring, and operational tasks — compressing the research cycle from months to days.
Inquiries
For partnerships, press, and capital — write to [email protected].
For roles, see Join Us.