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iankar8/README.md

Ian Kar

I build AI-native products and operating systems for fintech, regulated workflows, and long-running agents.

My work usually starts with a messy operational problem and ends with something testable: a working product, a deterministic receipt, or an observable handoff. AI accelerates the research and implementation; evidence, controls, and human ownership stay visible.

Website · Arcana Research · X

Start Here

Operational systems

  • Event Manager OS — An end-to-end conference operations system that moves one persisted record from proposal through public schedule, with cross-role handoffs and audit history. Live demo.
  • Scam Discovery Platform — A public-data pipeline for finding emerging consumer-fraud patterns before they become established categories.
  • FileReady — A synthetic mortgage-processing prototype for evidence-linked document review, borrower follow-up, and processor-controlled underwriting handoff.

Evidence and agent infrastructure

  • Evidence Workbench — A deterministic CLI that turns claims and supporting material into auditable decision receipts.
  • rrule-kit — Timezone-correct recurring scheduling primitives for long-running agents and automations.
  • agent-reminders — Lightweight reminder and follow-up infrastructure for AI agents.
  • Researcher — A zero-dependency CLI and Raycast extension that turns URLs, files, and YouTube videos into clean Markdown dossiers.

How I Build

  • Working systems over slideware.
  • Human approval at consequential boundaries.
  • Source-linked evidence instead of confident black boxes.
  • Tests at the observable boundary: persisted records, API responses, receipts, and rendered interfaces.
  • Honest labels for observed, synthetic, modeled, and unavailable data.

Now

I run Arcana Research, where I study how large organizations adopt, operate, and pay for AI. I also build local agent systems and small products that make persistent AI workflows easier to inspect and control.

Some work stays private on purpose: customer data, outreach workflows, Arcana's research platform, and the core of my personal command center. Public repositories use public or synthetic data and state their boundaries explicitly.

Pinned Loading

  1. agent-reminders agent-reminders Public

    Lightweight ephemeral to-dos and reminders for AI agents.

    Swift

  2. event-manager-os event-manager-os Public

    Open-source conference program operations: proposals, review, speakers, scheduling, publishing, API, and observable handoffs.

    TypeScript

  3. evidence-workbench evidence-workbench Public

    Claim → decision receipt. Zero-dependency CLI that scores claims on a 7-dimension rubric and emits auditable decision receipts.

    JavaScript

  4. researcher researcher Public

    URL / file / YouTube → clean markdown dossier. Zero-dependency CLI + Raycast extension.

    Python

  5. rrule-kit rrule-kit Public

    Timezone-correct RRULE scheduling for AI agents. Drop-in rrule replacement + agent scheduling primitives.

    TypeScript

  6. scam-discovery-platform scam-discovery-platform Public

    Early-warning system for emerging consumer scams — clusters public CFPB/FTC complaint data to surface novel fraud patterns before they hit banks' books.

    Python