Arcev finds opportunities and shifts forming in the world’s public data.
It reads 191 kinds of public data around the clock: news, social media, official filings, government sources, capital markets and more.
It connects scattered signals that are secretly the same story: connections no single person would ever spot alone.
It tells you plainly what’s forming: an opportunity, a market shift, a coming rule. Every claim comes with its source.
A market intelligence engine that reads the world between the lines, every second.
It exists because the world announces what is coming, constantly, in public. Governments publish what they will regulate. Companies publish what they raise, build and hire for. Researchers publish what is about to work. The signals are all there, in plain sight.
What has been missing is a reader: something that can take it all in, notice what belongs together, and say out loud what it means. That is the whole reason Arcev exists. Not another feed, not another dashboard. A reader with a verdict.
Watch it spot a real opportunity,
step by step.
A true story, replayed in sixty seconds: autumn 2024, the whole world is staring at AI while quantum computing quietly compounds in the public record. Watch Arcev catch the turn before Google’s Willow chip ignites the sector, and flag the hype before the 40% day.
Every clue in the film was public, months early: the standards, the preprint, the funding, the hiring. Arcev reads them the day they appear, across every industry at once. The next turn is already leaving clues.
The work of a hundred analysts.
Done in hours, without the blind spots.
A team reads fragments and meets on Mondays. Arcev reads everything, holds it in one memory, and connects dots that sit oceans apart. That connection is the product.
Under the hood: one engine that
reads, connects, and scores everything.
Everything above is produced by one system. At the base, 191 categories of public sources stream in around the clock. In the middle, one living graph · every document read, resolved to the companies and places it is actually about, and clustered with everything that belongs to the same story. At the top, what your team receives: scored markets, tried verdicts, typed reports. No black box: the same citation travels intact from the raw document to the sentence you read.
Four model passes turn a raw item from any of 191 source categories into a typed, scored, cross-source object on the graph. Each runs continuously, on everything.
Dozens of sources reporting the same thing collapse into one story · entities resolved, duplicates merged, the cross-source signal made visible.
Every cluster is read and labelled · market shift, event, regime change, leading indicator, science or hype wave · with no human tagging.
Not just what happened, but how fast and what it leads. Acceleration and lead-lag against the markets a signal touches.
Pain, novelty, market readiness, regulatory tailwind, timing and capital · combined into one 0–100 score and a clear tier.
Four modules. Every feature, explained.
Your first look every morning: what moved overnight, what died in testing, and what deserves your next hour.
41 sectors and roughly 700 markets, discovered and named from the data itself. No consultant taxonomy, and it re-draws as the world moves.
A quality-weighted index per market. Sort by acceleration and you are watching momentum build before the headlines arrive.
The same landscape from three angles: a novelty-by-capital scatter, a 90-day signal river, and per-market trendlines.
Every underlying signal, readable and sourced. The receipts are always one click deep.
Everything ranked from Tier 1 to noise. Each entry carries its verdict, its evidence mix, and its full history.
The structure underneath: which domains move first, which follow, and which formations rhyme with past winners.
Every candidate interrogated like an investment committee would: who buys, why now, what is the wedge, what would kill it.
“Build this. Sell study-automation to transmission owners first. The window is 18–30 months.”
A red team attacks every top candidate, with sources. You read the full fight, and what died along the way.
“Incumbents bundle this into existing contracts. There is no wedge.”
“Penalties bind before their release cycles can respond. The wedge is speed.”
Dated, falsifiable calls with confidence attached, graded publicly against what actually happened.
Typed, dated, cited documents, from Investment Thesis to Hype Alert. Each one built to end a different argument.
A chat that answers with footnotes. Every claim in every answer links to the document that backs it.
Speed. Penalties bind before incumbent release cycles respondc1c10. Sell study-automation to transmission owners first.
Pin the conversation to any market, signal or report. The answer knows exactly what you are looking at.
Named in the evidence: 6 investor-owned utilities, 41 postingsc3. List follows.
Follow what matters to you. Tier changes, momentum spikes and fresh evidence reach you first.
Every verdict carries a tripwire, watched automatically. And Monday at 07:02 the Dispatch sums up your week, fully cited.
Arcev reads everything the world publishes, watches what companies and governments actually do, not just what they say, and finds the few signals that are a real opportunity forming. Every claim cited to its source.
How is this different from Bloomberg, PitchBook or CB Insights?
They index what already happened: deals closed, rounds announced, markets named. Arcev works one step earlier. It reads the primary record and surfaces opportunities while they are still a handful of quiet signals, before they have a category name, with a dated verdict and the citations to check it.
Why should I trust a machine’s verdict?
You shouldn’t. You should check it. Every claim carries a citation to a public document. Every Tier 1 survived a red-team trial you can read. And every call is scored later against what actually happened; the ledger of hits and misses stays on the page.
What does it actually read?
191 categories of public sources across 12 domains: news and social discussion, official and regulatory filings, government records, legal dockets, research and grants, hiring activity, and capital flows of every kind.
How current is the data?
Sources stream in around the clock; clusters re-form and scores recalibrate continuously as new evidence confirms or contradicts. The Dispatch summarises weekly. The machine does not wait for a news cycle.
How is Arcev priced?
Per seat, sold to teams. Companies get a walkthrough and a demo tailored to their markets. Bring your sector and we’ll show you its trail.
Can it read our internal data, in our environment?
Yes. Enterprise deployments connect private sources alongside the public ones and run in your cloud, or fully separated. Your data never informs anyone else’s view.
Is this investment advice?
No. Arcev is research infrastructure: evidence, scoring, and argued verdicts with sources. The decision, and the responsibility, stays with you.
When can I use it?
Arcev launches in 2026. The demo is live now, and the build is public. Follow along on LinkedIn.
Sixteen opportunities were stress-tested last week. One survived.
The demo shows you which one, and why the other fifteen died. Somewhere in today’s filings, tenders, dockets and job posts, the next one is already forming. The only question is who reads it first.
| PROJECT | ARCEV · SIGNAL & OPPORTUNITY ENGINE |
| STATUS | LAUNCHING 2026 |
| REV | A |
| CHECKED BY | THE RED TEAM |