Products / insigz Research

Turn the world's research into a queryable evidence base.

insigz Research reads scientific literature and reports, extracts structured facts, and maps them — every claim traced back to its source sentence, confidence-scored, and labelled as AI-extracted. It runs on the same canonical model as the rest of insigz.

R.1 / THE PROBLEM

Millions of papers. None of them queryable as data.

The data exists. The layer between the documents and the people who have to act is what's missing.

Evidence lives in unstructured prose — abstracts, full-text articles, regulatory filings, field reports. Finding it means keyword search and manual triage; trusting it means reading every source by hand.

insigz Research ingests a corpus, uses grounded LLM extraction to pull out structured, source-anchored facts, canonicalizes them against standard ontologies, and serves them through search, filters, and a map. Every fact links to the exact sentence it came from.

Provenance over assertion. The platform never presents a fact as ground truth — it presents "this source says X, here is the exact sentence, here is the extraction confidence." That is what makes the output defensible, auditable, and commercially trustworthy.

R.4 / HOW IT WORKS

Four stages, one canonical chain.

The same Source → Observation → Entity → Event → Case → Report model that powers the rest of insigz.

/01

Ingest

Pull literature and documents from licensed and open sources. The per-document license travels with every fact.

/02

Extract

Grounded LLM extraction returns typed assertions with the verbatim source span. Any claim whose span can't be matched back is rejected.

/03

Canonicalize

Resolve every entity to a stable id (MeSH, ICD, RxNorm, UMLS, GeoNames). Locations get lat/long for the map.

/04

Search, map & export

Faceted search, the evidence map, per-assertion provenance, and license-gated export. A review queue promotes machine output to gold.

R.5 / WHO USES IT

Where auditability is the buying requirement.

Life sciences is the lead case; the pipeline generalizes to any literature or report corpus.

/01

Pharma & life sciences

Pipeline and competitive intelligence, epidemiology and market sizing, pharmacovigilance signal scouting — every signal traceable to source. A "reviewed-only" view for regulated environments.

/02

Public health & policy

Map where conditions are reported and studied; spot under-studied regions; combine with surveillance feeds — always separating attention from incidence.

/03

Research, due diligence & NGOs

Accelerate systematic reviews, quantify the evidence behind a target or thesis, and build cited evidence maps suitable for public accountability.

R.6 / CAPABILITIES

What's in the product.

EXPLORE

Search, facets & the evidence map

  • Full-text + semantic search over assertions
  • Facets: entity, location, evidence class, confidence, source tier, review status, license
  • Interactive map; findings vs mentions kept distinct
TRUST

Provenance & review

  • Per-assertion source sentence, PMID/DOI, model + confidence
  • Unmissable AI-extracted badge throughout
  • Human review queue: confirm / edit / reject
ANALYZE

Entities & scenarios

  • Entity pages: linked assertions, top locations, evidence over time
  • Scenario layer: observed vs projected, reproducible
  • Connects to the wargame extension for tabletop runs
SEE IT

Explore a sample evidence map, or talk to us about your corpus.

Request a demo →