Iris.ai - Your Research Assistant – Leading AI for your research challenge

Research discovery with artificial intelligence

Use Natural Language Processing to review massive collections of research papers or patents: find the right documents, extract all their key data or identify the most precise pieces of knowledge.

For academia

For Corporate R&D

Try the free tool

Natural Language Understanding

Iris.ai uses a combination of keyword extraction, word embeddings, neural topic modeling, word importance based similarity of document metrics and hierarchical topic modeling. The approach is mainly unsupervised but we utilize an evaluated annotation set from our community of AI Trainers for benchmarking and improving our tools.

Key information extraction
Key terms identification. Marking of possible contextually disambiguating information. Forming basis for a document fingerprint.

Neural Topic Modelling
Clustering of semantically similar documents. Cluster labeling. Document fingerprint update.

WISDM
Fingerprints are matched using the WISDM document similarity metric.
Basis for document fingerprint indexing.

HOURS SAVED

PER YEAR

WITH A TEAM OF

RESEARCHERS

Saved time and increased radical discovery

Industrial researchers use on average 3 weeks to build a reading list, with a self-reported 70% confidence. Using the systematic academic approach, we save you time and resources – while increasing the chances of groundbreaking interdisciplinary discovery.

Up to 90% time reduction
85% precision
Increase interdisciplinary inspiration
Organize your internal R&D documents

“…tools such as Iris.ai…can accelerate researchers’ entry into new fields.”

Andy Extance

“[Iris.ai] might just revolutionize scientific research”

Phil Barker

“Computers can’t yet replace humans, but they can do a great job handling the mundane clutter of our lives.”

Fast Company’s Most Innovative Companies 2017

“One wonders just what she’ll be capable of when she’s all grown up.”

Andrew Wade

“Iris.ai drastically expedites research.”

Haje Jan Kamps

“Access to reliable knowledge – the academic literature – is becoming a fundamental bottleneck for humanity.”

Owen Gaffney and Denise Young

“humans need increasingly smarter, machine-assisted ways to navigate the ever-growing mountain of scientific knowledge”

Natasha Lomas

“…especially useful when you don’t know the exact keywords for the type of research you are looking for”

Bahar Golipur

“As AIs take on more responsibility in managing the discovery process, the science community may free up significant portions of the time they currently devote to scanning for trends.”

Aaron Frank

“This type of assistant is a huge asset to academics and scientists.”

Sam Cohen

“artificial intelligence (AI) that enhance or even replace the role of humans each step of the way”

John Bohannonur

“…built with smart, savvy tech leaders”

Ed Sappin

“found to have the most potential to positively impact one billion people”

Vanessa Bates Ramirez

“Iris.ai is on its way to transform from Science Assistant to fully-fledged, curious Scientist – and we can’t wait to see the impact Iris.ai will have on the scientific community”

Elsa Snellman