Research that shows how the conclusion was formed.
Company evidence, metrics, valuation context, and thesis synthesis stay connected instead of collapsing into an opaque answer.
AI-native investment research
Investment research that shows its work.
Pythia connects company evidence, valuation, macro context, portfolio review, and AI-assisted workflows in one visible analytical chain you can save, replay, and audit.
LIVE PRODUCTInvite-only workspace
VISIBLE CHAINSources through thesis
REUSABLE STATESaved and auditable
Current product
Enter Pythia
01 · The research loop
The workflow is the proof.
Pythia keeps the analytical chain visible from raw evidence to a decision you can revisit. Each surface has a clear job; together they form one reusable research system.
Analysis becomes reusable product state.
Research can be reopened, compared, replayed, and audited rather than disappearing into a one-off report.
Review decisions, not just returns.
Contribution, timing, thesis context, and what-if analysis create a disciplined feedback loop.
AI assists. The data layer stays authoritative.
Deterministic services remain separate from advisory model output, with explicit approvals and boundaries.
A product story people can inspect.
Current screenshots, public-safe case studies, architecture diagrams, and build notes make the work tangible.
Explore the public evidence02 · Inspectable evidence
Built for evidence,
not black boxes.
The public layer demonstrates the same discipline as the private workspace: clear provenance, current product surfaces, explicit boundaries, and claims you can trace.
Public case studyPortfolio 8 contribution and decision review
Source-aware by design
Evidence and analytical outputs stay connected so readers can inspect the chain behind a conclusion.
State that survives the session
Saved research and portfolio context become durable inputs to future decisions.
Explicit system boundaries
Private data remains authenticated while public artifacts are intentionally allow-listed.
Current product, not concept art
The public story uses real screens, real workflows, and redacted app-sourced evidence.
03 · Why Pythia exists
Better tools should improve judgment.
Investment research becomes more useful when the evidence, models, assumptions, and decisions remain visible to the person making the call.
AI should increase the quality of judgment—not hide the reasoning behind it.Pythia’s working principle
- Research
- Bring filings, metrics, peers, valuation, and narrative synthesis into one inspectable workspace.
- Memory
- Keep saved analyses and portfolio context available for comparison, review, and future runs.
- Discipline
- Separate deterministic data services from model guidance and preserve human approval at decision boundaries.
04 · Continue into the product
Put the full research chain in view.
Sign in to use the private workspace, or request access if you are exploring Pythia for the first time.