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FINANCIAL AI RESEARCH

Learning the
structure
of markets.

Neural state-space models for financial time series. We bring machine learning and data engineering to the study of complex market behavior.

Explore our research
RESEARCH FIELD / 01SEQUENTIAL INTELLIGENCE
OBSERVATION → REPRESENTATION → SIGNAL
Neural state-space modelsConceptual illustration
OUR FOCUS

State-space models

Financial data

Applied machine learning

01 — RESEARCH

Markets change.
Models must account for it.

Financial data is sequential, noisy, and constantly evolving. Our research focuses on neural networks that represent how information develops over time.

01 /

Neural state-space models

State-space architectures use an evolving internal state to process sequences. We work with these models for financial data, where context and time matter.

SEQUENCE MODELING
02 /

Financial data engineering

Useful models depend on useful data. Our work brings data preparation and machine learning together to study patterns in financial time series.

DATA & REPRESENTATION
03 /

Applied market intelligence

We connect neural-network research with practical financial-market problems. The focus is on understanding market dynamics and informing systematic decisions.

RESEARCH TO APPLICATION

02 — APPROACH

Built around
the hard questions.

A clear research question matters more than a complex model. These are the questions that guide our work.

Start a research conversation
01

What does the model remember?

How can a compact internal state represent the history that matters in a financial sequence?

02

What changes when markets change?

Which patterns persist across changing conditions, and which depend on a particular period?

03

What survives beyond the experiment?

How should data quality, computation, and practical constraints shape model development?

OUR AI WORKFLOW

Connecting market context
with quantitative signals.

We use Gemini to turn financial news and announcements into structured inputs for our research systems.

Our neural state-space models combine this context with financial time series to study market dynamics and inform systematic decisions.

  1. 01 / CONTEXT

    Financial news & announcements

  2. 02 / GEMINI

    Structured research inputs

  3. 03 / STATE-SPACE MODELS

    Context meets market time series

03 — COMPANY

At the intersection of
AI and financial markets.

Tesuji Labs is a technology company working on neural state-space models and financial data.

Our work combines AI research, data engineering, and market applications. We use Google Cloud as part of our computing infrastructure.

We are interested in thoughtful conversations with researchers, engineers, and potential collaborators who share this focus.

TESUJI LABS LLCCompany contact · James Pinkerton

04 — CAREERS

EXPRESSIONS OF INTEREST

Work on problems
worth thinking about.

Interested in the intersection of neural networks and financial markets? We welcome introductions from people who care deeply about their work.

01

Machine learning researchSequence models, neural architectures, and financial time series

02

Research engineeringTurning modeling ideas into clear, reliable research systems

03

Data & infrastructureFinancial datasets, data pipelines, and research computing

These are areas of interest, not a list of confirmed vacancies. Tell us about your background and share a project, paper, or piece of work you are proud of.

05 — CONTACT

Let’s talk
about what’s next.

For research, collaboration, and career inquiries.

Your message reaches the Tesuji Labs team directly.