Home – Iris.ai - Your Science Assistant

The future of Science

We’ve built AI tools to take you from a problem to a precise reading list in less than two days.

Exploration of interdisciplinary research

Consistently outperforming old school search tools, Iris.ai builds an interdisciplinary research map based on a problem statement or research paper of your choice. Iris.ai does this by building a "fingerprint" using machine extracted keywords, contextual synonyms and hypernyms, then matches the fingerprint against more than 70M Open Access papers

Bypass keyword search
Bypass citations
Navigate papers visually

Bookmark papers
Download full text directly
Access full history

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Full research landscape mapping

Use the Exploration tool starting from your free text description of the problem and a result editor, to build a large corpus of documents related to the problem statement. Use the iterative Focus tool to narrow down to a precise reading list.

Incorporate other databases
Exploration from free text
Edit exploration results

Focus down a reading list
Export your reading list
Machine topic filtering

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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

LATEST NEWS

Ready to hear all about “The https://t.co/cEBzyAV1dt project – the Future of Science” with @twitnitnit, founder of @TheIrisAI! #DeloitteDigiLU

AI is taking hold in industries all over the world, and university libraries are no exception. How can university libraries prepare for the future of AI-enabled literature? https://t.co/agiSrofi9Y #ai #ArtificialIntelligence #HigherEducation #LibrarianProblems #librarytwitter

The last IrisAI workshop of the year is tomorrow and there's still time to register! Join us and learn to create your first exploration map, edit and refine your results, and prep it for the Focus Tool. https://t.co/QDzkzZDHay

Everyone needs a cheat sheet now and then. To all of our ML and AI friends out there, here are some killer resources from the very detailed, all the way to "Machine Learning in Emoji." #AI #ML #MachineLearning #DeveloperResources https://t.co/ybUqkmssHh

Insightful fireside chat with @MariaRitola, @HKetamo and Martin Siltberg of @sanalabs. If you are a teacher with 30 students, you have to know the needs of each of them. That's one of the examples where #AI can be a great helper in learning.
#XcitED18 #slush18

What's relevant in AI now & how will traditional industries change? Great panel discussion at #Slush2018 with our CEO & Founder @LuCrFr, @MariaRitola at @TheIrisAI & @asarrafi at @CombientFoundry. How do you believe traditional industries will be affected?

Good morning #OEB18 ✨🦄 Ready for this morning’s opening keynote!!

Heading towards a digital paradise with @MariaRitola, cofounder of @TheIrisAI: ”It’s all about collaborative intelligence rather than machines vs. humans” #nakedapproach

We're rounding out a year full of advancements in the world of AI. What can we expect in the 12 months ahead? #AI #Future #Technology #Predictions https://t.co/eQZGR1VI7D

Are you ready for our Disrupted or Disrupter conference on 12 December? Get the opportunity to discuss with our speakers about #digitalinnovation: @twitnitnit @TheIrisAI; David Duan, @AiDeepblue; @Krisverburgh @singularityu & @TomChatfield #DeloitteDigiLU https://t.co/yY6zsKYThO:

“…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