Your documents already hold the answers. Now you can ask.

Every organization sits on a pile of documents too big for any one person to read — research papers, specifications, contracts, archives that grow faster than anyone can keep up. Blackfrog turns that pile into meaningful answers. Ask a question in plain English; get a direct synthesis where every single claim carries a citation to a specific source, so your expert can check the work instead of redoing it. The machine does the reading. Your expert stays the validator.

01 / RESEARCH LITERATURE

A corpus no human can read. Answers a researcher can stand behind.

For a scientific research organization, we built a platform that turns roughly 16,500 research abstracts into direct, cited answers. Keyword search returns lists; generic chatbots answer fluently and cite nothing — disqualifying for scientific work. This does neither. Ask a focused question and the system retrieves the relevant abstracts, then writes a synthesis under an enforced integrity rulebook: every claim carries an inline citation to a specific source, and when the literature doesn’t cover something, the answer says so explicitly — “the sources don’t address this” — instead of guessing. Five query modes cover the real shapes of research work: cited Q&A, comparison, summary, diagram, and long-form report. The researcher owns the conclusions; the citations exist so they can check every step.

Ask in plain English

Inline citation on every claim

5 query modes

~16,500

scientific abstracts in the
indexed corpus

~30 sec

to a fully cited answer
on a focused question

blackfrog / literature synthesis — cited answer

[ PRODUCT SHOT —
cited answer ]

blackfrog / document intelligence — your corpus

[ PRODUCT SHOT —
your corpus ]

02 / ANY PILE OF DOCUMENTS

One expert. An unreadable pile. The same discipline.

The pattern isn’t about science — it’s about any firm where one expert holds the judgment and the evidence sits in a pile nobody can read end to end. Specifications. Contracts. Regulations. Product catalogs. Decades of project archives. The shape of the problem is identical, and so is the answer: retrieval over your corpus, plus the same enforced citation rules, with your expert as the validator. Your senior person stops skimming for the needle and starts doing what they’re actually paid for — judging the answer, with the sources one click away. That’s what amplifying an expert looks like when the raw material is documents instead of drawings.

Specs, contracts, regulations, archives

Same enforced citation rules

Your expert validates

Cited

every claim traces to a specific source in your corpus —
the same rule the research platform enforces in production

Yours

your documents, your corpus, your expert
making the final call on every conclusion

/ THE DISCIPLINE

Anti-hallucination as architecture, not a promise.

Cite everything, invent nothing.

Every claim in every answer carries an inline citation to a specific source document. Not a bibliography at the bottom — a citation on the claim itself, so checking the work takes seconds, not an afternoon.

Numbers verbatim.

Figures from the sources are reproduced exactly — no rounding, no “approximately” the source didn’t say. When an answer connects numbers across sources, that inference is flagged as synthesis, so you always know what was read versus what was reasoned.

Missing evidence says so.

When the corpus doesn’t cover a question, the answer is “the sources don’t address this” — not a fluent guess. That honesty is what makes the tool an analyst your expert can trust and build on. No staff displaced: the machine does the reading, your expert owns the conclusions.

See how we work →

This isn’t a roadmap — the platform runs in production for a scientific research organization, with a citation architecture hardened to withstand third-party expert scrutiny and a corpus the client’s own non-technical staff manage themselves. No staff displaced. Read the build →

Stop searching your documents. Start asking them.

Bring the pile — a folder of specifications, a contract archive, a research corpus — and one question your expert wishes they could answer without a week of reading. We’ll show you what a cited answer from your own documents looks like.