Building now · Miami, FL

Research that shows its work. By design.

I'm Kristian Ortega — a finance-trained product builder at OKO Group by day, building Pythia Analytics by night: an AI-native investment research workspace where sources, reasoning, valuation, and portfolio review live in one visible analytical chain.

LIVE PRODUCTInvite-only workspace
PUBLIC EVIDENCECase study + build notes
VISIBLE SYSTEMArchitecture + data boundaries
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01 /

The project is the proof.

Most research disappears into static reports. Pythia turns it into a visible, reusable workflow — every conclusion traceable back through the chain that produced it. Watch the signal move:

Sources

Filings, data, and evidence — attached, not asserted.

Metrics

The numbers that matter, connected to where they came from.

Valuation

Context and comparables that frame what a number is worth.

Thesis

A conclusion a reader can inspect, replay, and challenge.

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Built on five working principles.

Visible chain

Research that shows its work

Sources, metrics, valuation context, and thesis stay connected — so anyone can inspect how a conclusion was formed.

SourcesMetricsValuationThesis
Saved state

Analysis becomes product state

Research can be reopened, compared, replayed, and audited — instead of vanishing inside a one-off static report.

SavedLinkedReplayable
Portfolio loop

Review decisions, not just returns

Contribution, timing, saved thesis context, and what-if analysis create a disciplined feedback loop.

ContributionTimingWhat-if
AI boundary

AI assists. The data layer stays authoritative.

Deterministic services are cleanly separated from advisory model output — approvals and boundaries stay explicit, so judgment improves without the reasoning being hidden.

Deterministic coreAdvisory layer
Public proof

A product story people can inspect

Current screenshots, a public-safe portfolio case study, technical diagrams, and build writing — showing both product judgment and implementation depth.

ScreenshotsDiagramsBuild notes
03 /

Finance underneath. Product on top.

04 /

A finance mind that learned to ship.

AI should improve the quality of judgment — not hide the reasoning behind it.

Working principle · Kristian Ortega

I studied finance to understand how companies, markets, and capital compound over time. Building Pythia became the practical application — research, modeling, automation, product decisions, and constant iteration inside one system I actually use. I work where capital meets concrete — and increasingly, where finance meets software.

Why I built Pythia →

Focus

Financial analysis, real estate finance, AI-native product development, research workflows.

Currently

OKO Group by day. Building and documenting Pythia Analytics outside the day job.

Approach

Source-aware. Skeptical. Iterative. Focused on making complicated analysis easier to inspect.

05 /

The lab. Markets, rendered.

A growing series of real-time financial visualizations — live market data driving GPU physics. Built to explore the same idea behind Pythia: analysis you can see into.

06 / Follow the build

See what Kristian
is building.

Explore the product, inspect the public case study, or connect directly.