Data Infra › News & Sentiment

Data Infra · 05

News & Sentiment

Curated technology and AI market news with two timestamps on every item: when it was published, and when we saw it. Trending detection and per-ticker sentiment as honest, dated series.

Every row passes the Bargo Verification Layer

Accurate · Reliable · Source‑backed

Continuous
ingestion and updates
2
timestamps per item: published and seen
Per ticker
sentiment series over time
100%
of items trace to their article

What's inside

What broke, when it caught fire, and how it reads

Curated feed

AI and technology market news, ticker-tagged, noise filtered before it reaches you.

Trending detection

Which stories are accelerating in coverage, and exactly when they started to.

Ticker sentiment

Article-level and aggregate sentiment per ticker, as a dated series, not a mood.

Source links

Every item traces to its article. Nothing arrives as a paraphrase without a pointer.

The data, not a description of it

A row you can check yourself

Every item ships with its article link and both timestamps, so backtests know exactly what was knowable when.

■ news_item · illustrative format
tickerMU headline“Micron guides below consensus on HBM pricing discipline” source_urlthe publisher’s article, linked published_at2026-09-24 16:32 ET seen_at2026-09-24 16:41 ET sentiment-0.4 · labeled as a model estimate, with version trendingaccelerating · computed from coverage counts
Field names simplified for display. Full data dictionary ships with every evaluation snapshot.

Bargo Verification Layer · Accurate · Reliable · Source‑backed

Watch one headline survive the three gates

A story publishes. Here is what happens before it becomes a data point:

Gate 1 · The data

Dated strictly, or left blank

Timestamps are parsed strictly. When a source date cannot be read with confidence, the field stays empty, so the crawl time never impersonates the publish time.

✓ published_at parsed from the article · seen_at recorded separately
guessing the date from context · a blank means unknown, never a guess
Gate 2 · The method

Both clocks preserved

Published and seen are separate fields on every row, forever. Point-in-time honesty is structural, not a disclaimer.

✓ a backtest keys on seen_at: what was actually knowable
✗ collapsing the two clocks into one · the classic lookahead bug, made impossible
Gate 3 · The answer

Scores labeled as what they are

Sentiment is a model output, and it ships labeled as one, with the model version on the row. Trending scores are computed from counts.

✓ sentiment -0.4 · model and version recorded on the row
a score presented as ground truth · estimates never wear the costume of facts

Only then does the item ship: linked, double-dated, honestly labeled. News data you can put in a backtest without archaeology. See the full Verification Layer →

Why it compounds: the seen_at clock cannot be recreated. When a story actually entered coverage is only knowable if you were watching at the time, and we have been. That series grows every hour and cannot be purchased retroactively.

Access

The same feed, three ways

Ask it anything

Bargo Agent

News questions with receipts: what broke, what is accelerating, and how it reads.

> What is accelerating in AI news right now, and since when?
For AI agents & terminals

Bargo MCP / CLIs

Wire it into Claude, Cursor or your own agents, or pull straight into pandas.

$ bargo news trending --sector semis \ --format json
Programmatic

Bargo APIs

Feed, trending and sentiment series as clean endpoints, ticker-tagged throughout.

GET /v1/news?ticker=MU GET /v1/news/sentiment?ticker=MU

Who runs on it

Built for what is catching fire

Portfolio managers

Context before the open

What broke overnight on your names, ranked by acceleration, each item linked to its article.

Analysts

The narrative, dated

When a story started, how it spread, and how coverage tone shifted, with sources.

Quants

Backtest-safe by construction

Dual timestamps kill lookahead at the schema level. Sentiment ships versioned, ready to be a feature.

Coverage & delivery

The facts sheet

CoverageCurated AI and technology market news, ticker-tagged.
LatencyContinuous ingestion; items carry both published and seen timestamps.
HistoryDated series suitable for point-in-time work, keyed on what was knowable when.
FormatsJSON over API, CSV / Parquet snapshots, digest-stamped.
IdentifiersTickers on every item, for joins with the rest of the catalog.
VerificationEvery row carries its source and its checks. Corrections are versioned, snapshots digest-stamped. How the Verification Layer works →
We would rather show you the data than describe it.
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