One engineer. Zero staff.
This entire platform runs itself.

Everything on this site — the deep dives, the frameworks, the graded scorecard, the weekly letters — is produced by an autonomous AI research system designed, built, and operated by one person. This page explains how, because the system itself is the demonstration.

The pipeline

1. Ingest — every morning, unattended

   A scheduled job wakes at 5:15am, checks 105 shows and expert channels, pulls new transcripts, and falls back to local GPU speech-to-text when captions aren't available. Company fundamentals, prices, filings, and macro series flow in from market-data pipelines the same way. Nobody presses a button.

2. Distill — from talk to testable claims

   Frontier language models read each transcript and extract every falsifiable claim — who said it, about what, with what conviction, on what horizon. The result is a knowledge base of 54,764 structured claims, every one carrying its source, date, and speaker, so any conclusion can be traced back to who actually said what, when.

3. Analyze — where humans and models meet

   Custom scoring models weigh each voice by track record and each claim by age and type. Quantitative screens rank companies on forward growth and acceleration, not hindsight. The two streams fuse into conviction scores, expert frameworks, and the 619 company pages across the site.

4. Publish — the system writes, charts, and ships

   Weekly letters draft themselves from the week's new claims, build their own data-backed charts, pass editorial gates that verify every quote against its transcript, and deploy to this site on a git push — served from a global edge network with no servers to maintain and hosting costs near zero.

5. Grade — in public, against its own record

   Predictions get resolution dates. When they come due, the system grades them — hit or miss, on the record — and the 606 scored verdicts stay published either way. Discipline isn't a promise here; it's a table anyone can read.

What it took to build

• LLM extraction pipelines with provenance on every record — claims that cite their source, not a black box
• A local GPU for embeddings and speech-to-text — fast, private, and free at the margin
• A vector database for semantic retrieval across everything ever ingested
• Custom scoring and screening models over market and fundamentals data
• Automated chart generation where every datapoint traces to a dated, attributed claim
• Editorial gate systems that verify quotes verbatim before anything publishes
• Static edge hosting with push-to-deploy — no servers, no maintenance window, no monthly platform bill

Why this matters if you run a business

Swap the nouns. Instead of podcasts, your industry's trade publications and filings. Instead of stock research, your competitive landscape, your compliance monitoring, your client reporting. The architecture — ingest, distill, analyze, publish, all unattended — applies to any operation that turns information into decisions and documents. That's what a complete AI workflow means, and this site is the working proof.

Synthos Research publishes educational analysis, not investment advice.