The Invariant Chronicleby MaSer Invariant · A Coruña, Spain

EIT AI Entrepreneurs Lab 2026

News that shows where every number comes from.

An autonomous AI newsroom for Spain: it groups every outlet's coverage of the same event, checks each figure against the official body that produces it, and publishes a synthesis in which every sentence links to its evidence. When the evidence isn't there, it says so.

Sergio López Rapado (CTO) & Marta Fernández López (product) · invariantchronicle.com

1 / 9

The problem

Reading five newspapers doesn't tell you which of the five figures is right.

Fake consensus

Ten outlets reprinting the same wire story look like ten independent confirmations. They are one.

Numbers that don't compare

Headlines built on different metrics, periods or territories look contradictory when they aren't — or agree when they shouldn't.

The source is hard to reach

Finding the INE series, the Eurostat table or the article of the Official Gazette behind a claim takes time and expertise most readers don't have.

AI summaries make it worse

Generic summarisers average narratives together and can manufacture an agreement that no evidence supports. Human fact-checkers can't cover the volume.

For whom: readers who want to know what is actually supported; and, as a B2B layer, newsrooms, fact-checkers, researchers and communication teams.

2 / 9

The solution

A method, not a newsroom.

  1. ReadDiscover the news and decide, per source, what may be read, analysed and published.
  2. GroupCluster coverage by event — not topic — and separate reprints from independent reporting.
  3. ExtractAtomic claims with figure, unit, period, territory and who says it.
  4. CheckAgents find the official series or document with the same scope; a deterministic gate decides.
  5. PublishA synthesis where every factual sentence is traceable, disclosed as AI, versioned on change.
SupportedSupported with caveatsContradictedNo sufficient evidenceMatches across outlets

Two editions a day. No human approves each piece; humans own the rules, the sources and the rights policy.

3 / 9

Why AI is central

AI does the reading at scale. Deterministic gates keep it honest.

Without AI it cannot exist

Thousands of articles a day, each with dozens of claims, matched to the right statistical series: no human team can do that for a whole country.

Agents with tools, not a chatbot

LangGraph agents search official catalogues (INE, Eurostat, Banco de España, BOE, EUR-Lex, OECD, World Bank…) and read the documents they find. Gemini extracts, reasons and writes.

Trustworthy by design

No verdict without retrieved evidence. No invented sources: every ID must come from a tool. External text can't change the rules (prompt-injection tests). Abstaining is a correct outcome.

Measured, not assumed

Gold sets per task, paired shadow runs before any model change, a cost cap per day, and every model call recorded with its tokens and price.

4 / 9

What we have built

A working pipeline, end to end, on Gemini.

3,820
articles read
358
stories clustered
6,592
claims extracted
415
pieces written
8,879
model calls in that day
≈ 18.6 $
for the whole day (was ≈ 45 $/day on self-hosted GPUs, doing less)
21 / 24
published “Supported” verdicts correct on manual review

One full pilot day, 1 October 2026; manual review 1–2 October 2026. Private pilot: built and run by the two of us, part-time, with no funding.

5 / 9

What we have learned

The bottleneck is verification — and we know where.

Few stories reach “key facts supported”

21 of 2,908 pilot stories. Most key facts are events (51%) and statements (13%), for which we have no investigator yet.

Which route yields verdicts

Reading the source a claim cites works best (≈ 3% useful verdicts); matching statistical series barely works (0.3%) and costs the most. So we measure by input, not by outcome.

Grouping works, comparing needs work

The “same fact” judge reaches 0.58 precision against a 0.95 bar. We test better models in paired runs before switching.

Rights are a product requirement

An RSS feed is not a licence. Public launch waits for licensed press content; official data (INE, Eurostat) is reusable today.

Measured 21 September – 2 October 2026 in our own pipeline.

6 / 9

If it works

The evidence layer for the news.

For readers

A free, ad-free publication where every figure opens the data point behind it.

For organisations

API and data on claims, provenance and evidence for newsrooms, fact-checkers, researchers and communication teams — and alerts on how a figure travels across the press.

Beyond Spain

Country packs are data, not code: a second EU country with strong official APIs, then cross-country and multilingual stories.

7 / 9

What we want from the Lab

Prove who needs this enough to pay for it.

8 / 9

The team

Marta and Sergio — Ma·Ser.

Sergio López Rapado · CTO

Cloud solutions architect in data and generative AI, 10+ years (Inditex, MAPFRE with Google Professional Services, EY). Designed and built the whole platform and runs it. M.Eng. Telecommunications Engineering.

Marta Fernández López · Product

Dental surgeon, Master's graduate. Tests every version from the reader's side so that anyone can tell what is known and what isn't. Volunteer with the Red Cross and Cáritas.

We have shipped before: MaSer ONDA, our free app against unwanted loneliness, live on Google Play since September 2026. Contact: [email protected]

9 / 9