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Jump to:
 * Introduction
 * Why Causal AI
 * Testimonials

28 January 2022 causaLens raises $45m Series A to scale human-centered AI that
understands cause and effect causaLens raises $45m Series A to scale
human-centered AI that understands cause and effect
 * Causal AI
   * Why Causal AI
     
     Overview of Causal AI and its benefits
   
   * Trustworthy AI
     
     Learn about why it is the only AI that is human-centered and can be trusted
   
   * Explainable AI
     
     Learn about next-generation human-compatible AI
   
   * Our Vision
     
     AI that humans can trust
 * Product
   * Causal Decision-Making Platform
   * causaLake
     
     Explore the world’s most valuable data
   
   * causaLab
     
     Autonomously build & deploy AI models that truly understand cause & effect
   
   * decisionOS
     
     Go from predictions to AI decisions
 * Solutions
   * Decision App Store
     * Portfolio Optimization
     * Real Estate Investment
     * Marketing Attribution
     * Retention Optimization
     * Credit Risk
   * By Industry
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     * Healthcare
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     * Marketing & Media
     * Transport & Logistics
     * E-Commerce & Retail
     * Telecommunications
 * Resources
   * Causal AI papers
     
     Browse papers explaining the power of Causal AI
   
   * Case-study reports
     
     Download reports on real-world Causal AI applications
   
   * Our Causal AI Research
     
     Cutting-edge research into Causal AI
   
   * Webinars
     
     Access upcoming or on-demand webinars
 * Company
   * About Us
     
     Learn about our team
   
   * Contact
     
     Message us with any enquiries
   
   * Events
     
     Join us for workshops, webinars and conferences
   
   * News
     
     Keep up-to-date with news articles featuring causaLens
 * Join Us

Search for:
Request a demo
Menu
 * Causal AI
   * Why Causal AI
     
     Overview of Causal AI and its benefits
   
   * Trustworthy AI
     
     Learn about why it is the only AI that is human-centered and can be trusted
   
   * Explainable AI
     
     Learn about next-generation human-compatible AI
   
   * Our Vision
     
     AI that humans can trust
 * Product
   * Causal Decision-Making Platform
   * causaLake
     
     Explore the world’s most valuable data
   
   * causaLab
     
     Autonomously build & deploy AI models that truly understand cause & effect
   
   * decisionOS
     
     Go from predictions to AI decisions
 * Solutions
   * Decision App Store
     * Portfolio Optimization
     * Real Estate Investment
     * Marketing Attribution
     * Retention Optimization
     * Credit Risk
   * By Industry
     * Asset Management
     * Banking
     * Capital Markets
     * Energy & Utilities
     * Insurance
     * Healthcare
     * Manufacturing & IoT
     * Marketing & Media
     * Transport & Logistics
     * E-Commerce & Retail
     * Telecommunications
 * Resources
   * Causal AI papers
     
     Browse papers explaining the power of Causal AI
   
   * Case-study reports
     
     Download reports on real-world Causal AI applications
   
   * Our Causal AI Research
     
     Cutting-edge research into Causal AI
   
   * Webinars
     
     Access upcoming or on-demand webinars
 * Company
   * About Us
     
     Learn about our team
   
   * Contact
     
     Message us with any enquiries
   
   * Events
     
     Join us for workshops, webinars and conferences
   
   * News
     
     Keep up-to-date with news articles featuring causaLens
 * Join Us

causaLens Solutions

Request a demo


CAUSAL AI:
AI
 * DECISION-MAKERS
 * ASSET MANAGERS
 * GOVERNMENTS
 * BANKS
 * MARKETERS
 * INVESTORS
 * INSURERS

CAN TRUST

causaLens develops human-centered decision-making AI that organizations trust.

Learn more

CAUSALENS IS THE PIONEER OF CAUSAL AI — A NEW CATEGORY OF INTELLIGENT MACHINES
THAT REASON ABOUT THE WORLD THE WAY HUMANS DO, THROUGH CAUSE-AND-EFFECT
RELATIONSHIPS AND WITH IMAGINATION.


WHY CAUSAL AI

Causal AI goes beyond standard predictive analytics, directly augmenting human
decision-making. Its recommendations are intrinsically explainable, reliable in
real-world scenarios, and sensitive to business and governance constraints.

 

 


WE HAVE A VISION OF A SOCIETY POWERED BY CAUSAL AI

Learn more about our vision


 * Causal AI plays an ever more important role in our investment analysis. It
   empowers our strategists and portfolio managers to generate alpha by
   identifying new causal relationships in economic, financial and alternative
   data, with sophisticated, adaptive and explainable models that don’t suffer
   from overfitting.”
   
   Michael Grady – Head of Investment Strategy and Chief Economist, Aviva
   Investors
   
   

 * The causaLens platform has enabled us to discover additional value in our
   data. Their causal AI technology autonomously finds valuable signals in huge
   datasets and has helped us to understand relationships between our data and
   other datasets.”
   
   Keith Tippell – Global Head of product at CLS group
   
   

 * causaLens provides us with key causal insights that continuously unlock
   untapped value in our data.”
   
   Patrick Hable – Co-Founder and Managing Partner, 2IQ
   
   

 * Transparency and explainability of AI models requires an understanding of
   causality—an inherent advantage of the causaLens platform”
   
   Wendy Harrington – Chief Data and AI Officer, TIAA
   
   

 * The novel Causal AI techniques available on the causaLens Platform have
   facilitated our joint effort of discovering valuable profitable trading
   strategies”
   
   Darko Kirovski – Jump Trading
   
   

 * causaLens’ causality-based techniques & automation of quantitative workflows
   help us discover more orthogonal signals faster while discarding spurious
   correlations”
   
   Chris Udy – Chief Investment Officer, Tibra
   
   

 * Causal AI is a fundamental scientific breakthrough and causaLens’ vision for
   Causal AI extends far beyond enterprise decision making. causaLens has the
   potential to disrupt a vast range of sectors and industries and has already
   demonstrated the value of its Causal AI technology in biological applications
   such as the discovery of cancer biomarkers”
   
   Nicholas Chia, Ph.D. – Mayo Clinic*
   
   *This should be taken as a personal statement and not a statement or
   endorsement from Mayo Clinic.  Mayo Clinic does not support or endorse any
   commercial products or companies and never has.
   
   


ORGANIZATIONS ACROSS INDUSTRIES TRUST CAUSAL AI


ASSET MANAGEMENT

Read more...
Asset Management


BANKING

Read more...
Banking


INSURANCE

Read more...
Insurance


CAPITAL MARKETS

Read more...
Capital Markets


ENERGY & UTILITIES

Read more...
Energy & Utilities


HEALTHCARE

Read more...
Healthcare


MANUFACTURING & IOT

Read more...
Manufacturing & IoT


TELECOMMUNICATIONS

Read more...
Telecommunications


TRANSPORT & LOGISTICS

Read more...
Transport & Logistics


ENTERPRISE DECISION-MAKING AI LEVELS

AI maturity is a critical determinant of success in almost every industry. A
chasm is opening between early and late adopters. Leading organizations use
traditional AI to find solutions to business-critical problems, but their
challenges cannot be solved with standard correlation-based machine learning.
Forward-thinking organizations are turning to Causal AI.


Level 0 Level 1 Level 2 Level 3

Level 0


NO AI

The organization doesn’t use artificial intelligence to make decisions. Most
organizations are stuck at L0. AI is confined to data science experiments and
has no impact on real decision-making. The limitations of standard machine
learning technology are to blame.

 

Core problems include a lack of adaptability to real-world dynamics, and a lack
of explainability. Data scientists may attempt to implement “post hoc
explainability” methods, but these methods do not produce actionable insights. 

There are many other limitations of standard machine learning (see L1). However,
these two mean that business decision-makers do not trust AI systems
sufficiently to let them out of the lab. Read up on the shortfalls of current
state-of-the-art AI here. 

Organizations stuck at L0 are wasting resources on AI investment which has zero
impact.



Level 1


CORRELATION-BASED AI

AI is deployed in a narrow range of use cases across the organization and may
factor in some real decision-making. Fewer than one in ten organizations have
reached L1. They can begin to participate in some of the benefits of AI.
However, at L1 the organization is still frustrated with its AI systems, which
have minimal impact on significant decisions. 

Machine learning technology is again responsible. The core problems at L1
include:

Lack of adaptability and explainability. The key problems at L0 remain, but at
L1 organizations cope with these problems by deploying AI in low-stakes
contexts. 

Predictions only. Conventional machine learning models are only suitable for
making predictions. They can’t meaningfully help with decision-making, which
requires a model of how interventions impact an environment. 

Need for big data. Machine learning techniques and open-source software
developed by big tech are designed for data-intensive problems. They have little
transferable applicability to most industries which need to work with small
data. Enterprise AI platforms simply automate open-source software that is not
designed for the enterprise. 

Limited human-machine interaction. Users can direct machine learning algorithms
to focus on certain variables, but that’s where interaction begins and ends.
They can’t convey context to the AI or constrain its assumptions.

Fairness. Machine learning algorithms amplify human biases and perpetuate
historical injustices. This creates ethical, legal, and reputational
liabilities.  

These shortcomings of machine learning severely limit the range of applications
of AI. Decision-makers do not trust them to assist with important decisions. At
L1, AI has no impact on most stakeholders and their decisions.



Level 2


CAUSAL AI

The organization harnesses Causal AI, the only technology that learns and
reasons about the world as humans do. Causal AI has three key pillars: an
ability to learn cause-and-effect relationships; the capability to simulate
interventions; and a computer imagination that can reason beyond the constraints
of historical data. Causal AI is the only AI that decision-makers can trust. 

While L1 technology is essentially a form of “pattern-matching” or “curve
fitting”, L2 technology is genuinely intelligent. 

Causal AI provides:

Intrinsic explainability. Causal AI can explain why it took a decision in
human-friendly terms. The assumptions behind the model can be scrutinized,
constrained, and corrected by humans before the model is fully trained. This
reinforces trust that the model will perform as expected in production. Read
more here. 

Adaptability to regime shifts. Causal AI continuously discovers invariant
relationships that tend to hold over time, and so it can be relied on to make
sound decisions even as the world changes. Learn more here. 

Optimal decision-making. The AI can go beyond predictions and directly take
decisions and make recommendations. The most mature Causal AI systems are
capable of autonomously optimizing for abstract business goals and KPIs
(autoKPI™). View our product pages here. 

Human-machine interface. Causal AI keeps humans in the loop — users can
communicate business context to the AI, shaping the way the algorithm “thinks”
via a shared language of causality. Read up on how Causal AI empowers experts
here. 

Small data handling. Causal AI autonomously finds the critical information in
limited data and harnesses human knowledge, allowing it to make recommendations
with small datasets that are ubiquitous in business and government. Find out
more from our blog. 

Algorithmic fairness. Causal AI can envision futures that are decoupled from
historical data, enabling users to eliminate biases in input data. Causal AI
empowers humans to impose fairness constraints before models are deployed. Read
more in this article. 

These breakthrough capabilities enable Causal AI to make trustworthy decisions
in applied settings. This is what’s needed to take AI from the lab to the field
where it can make an impact and unlock enormous value.



Level 3


AGI

The enterprise is controlled by an Artificial General Intelligence (AGI) — a
general-purpose technology at least as intelligent as humans. Higher causal
reasoning is a defining feature of human cognition — equipping machines with
this ability is a necessary condition for reaching AGI. L3 is beyond the
technological horizon for now — we estimate it is some decades away.

If reached, we envision AGI having a dramatic impact on businesses.
Unconstrained by biological substrate, an AGI’s digital mind may innovate,
strategize, and execute on superhuman timescales. There may be a
“winner-takes-all” effect for companies that first reach L3. The current
economic development model may change beyond recognition.   

 




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