Capability map / research to release

One practice, across the difficult middle.

DIANNT joins investigation, system design, product judgment, and hands-on engineering. The result is a working surface whose logic can still be inspected.

  1. agent / retrieval / eval

    AI product systems

    Productized AI that connects source data, model behavior, human review, and a usable operating surface.

    • RAG and citations
    • voice and local models
    • agent workflows
    • evaluation loops
  2. state / signal / play

    Games and neurotechnology

    Interactive systems where world state, behavioral signals, and embodied research shape the experience.

    • Unity production
    • persistent worlds
    • EEG pipelines
    • behavioral modeling
  3. corpus / course / conversation

    Knowledge and education

    Learning platforms that preserve source context from curriculum operations through conversational interfaces.

    • course operations
    • multilingual content
    • CRM workflows
    • source-grounded study
  4. match / settle / validate

    Fintech and market signals

    Transaction infrastructure and quantitative research built around inspectable state, controls, and validation.

    • order books
    • wallet operations
    • alpha research
    • out-of-sample testing
  5. extract / model / explain

    Research interfaces

    Evidence-rich products that turn complex graphs, metrics, and recommendation systems into legible decisions.

    • knowledge graphs
    • behavioral analytics
    • semantic search
    • explainable scoring

A useful starting point

Start with the system,not the deliverable.

Share the constraint, the evidence, and what still refuses to become clear. The right product shape follows from there.

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