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Technology · Research

Evidence first. Engine second. Player always.

Research tools help us find and test possibilities. The useful output is a position and plan a human player can recognize under tournament conditions.

Capabilities

The research toolkit.

Established workflow01

Chess databases

Organize game evidence and opening history around the actual preparation question.

Established workflow02

Engine-assisted analysis

Test candidate positions and tactical details, with human interpretation of practical choices.

Available by scope03

Multi-engine research

Compare analytical perspectives where the position and scope warrant it.

Established workflow04

Statistical game analysis

Look for tendencies in available game samples while respecting sample-size limits.

Research-stage05

Human-centered AI research

Explore move-choice hypotheses as an experimental aid to chess analysis.

Research-stage06

Player-specific behavioral modeling

Investigate whether available games support a useful player-specific model.

Established workflow07

Preparation decision support

Translate evidence into a concise set of options for the player and coach.

Evidence & confidence

Predictions need context.

We distinguish a repeated choice from a weak signal. Recent games, sample size, time control, and changes in repertoire affect how much confidence to place in an opponent forecast.

  1. 01Record the games behind a likely line.
  2. 02Check whether the opponent has recently changed course.
  3. 03Separate observed behavior from analyst interpretation.
  4. 04State uncertainty next to the recommendation.
AI player modeling

Research-stage, by design.

Player-specific modeling may help investigate move-choice patterns when enough suitable games exist. It cannot be presented as a reliable simulation of a future opponent without task-specific validation against unseen games and expert review.

A modeling engagement begins with feasibility: what data exists, which decision is being studied, and how uncertainty will be measured.
Explore player-modeling research
Move-choice hypothesis
  • Bxc3+
    74%
  • Be7
    18%
  • Ba5
    8%
Held-out check pending · research stageIllustrative · no client data
Your move

Every preparation begins with a question.

Tell us the match, the timeline, and what you need to decide.

Discuss your preparation
Technology & Research | Farzin Prep