causaLens - a leading Causal AI software company | Enterprise AI

Web Name: causaLens - a leading Causal AI software company | Enterprise AI






News: causaLens partners with Mayo Clinic to discover biomarkers of cancer using Causal AI News: causaLens partners with Mayo Clinic to discover biomarkers of cancer using Causal AI Request a demo decisionApps Client Analytics for Wealth Management Marketing Mix Modelling Model Validation & Risk Management Customer Retention Pricing and Promotion Optimization Product Causal AI Platform decisionOS Go from predictions to AI decisions causaLab Autonomously build & deploy AI models that truly understand cause & effect causaLake Explore the world's most valuable data Industries Asset Management Banking Capital Markets Insurance Marketing & Media Supply Chain & Logistics Digital Agencies E-Commerce & Retail Healthcare Telecommunications Resources Knowledge Hub Causal AI White Papers Browse papers explaining the power of Causal AI Case Studies Download reports on real-world Causal AI applications Causal AI Research Cutting-edge research into Causal AI Community Events Webinars News Blog Causal AI Why Causal AI Explainable AI Trustworthy AI Our Vision Company About Us Our Team Careers Contact Us

Causal AI: AI Decision-MakersAsset ManagersGovernmentsBanksMarketersInvestorsInsurersAgencies Can Trust

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

Request a demo

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

Trusted leader in the industry

Understanding the causal drivers behind demand is critical. causaLens enhances our supply chain visibility and empowers our domain experts to run powerful what-if analyses”

Takashi Hiramatsu
Senior Manager, MLCC planning department – Murata

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 Kivorski
Jump Trading

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

Retail Banking

Read more... Retail Banking


Read more... Insurance

Capital Markets

Read more... Capital Markets

Energy & Utilities

Read more... Energy & Utilities


Read more... Healthcare

Manufacturing & IoT

Read more... Manufacturing & IoT


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


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


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.   

Augment your decision-making capabilities today

Request a demo
Contact Us

3rd Floor, Lyric House
149 Hammersmith Rd
London W14 0QL

causaLens © 2022


Book a demo to see how causaLens can help you optimize your business.

Consumer Products and Manufacturing

Consumer Products and Manufacturing

Digital Agencies

Digital Agencies

Data Driven Marketing

Data Driven Marketing



Asset Management

Asset Management

Transport & Logistics

Transport & Logistics

Energy & Utilities

Energy & Utilities





Retail Banking

Retail Banking

Retail & E-Commerce

Retail & E-Commerce

Capital Markets

Capital Markets



Manufacturing & IoT

Manufacturing & IoT

TAGS:Causal leading causaLens AI

<<< Thank you for your visit >>>

Websites to related :
Mirai web

  We're sorry but Mirai doesn't work properly without JavaScript enabled. Please enable it to continue. 404
Errors are unexpected opportunities.We ca

Asociación AdaSpain


Fairfield County Bank Insurance

  Skip to content Accessibility info 203-438-0404Client Login Toggle navigation HomeInsuranceClaims & ServiceCommunity AssociationsBanking Service

Yorkshire Wedding Photographers


kubaai - Kulturquartier Bocholte

  Skip to Content #header { } .isotope .image-post-overlay { display:none; }.isotope .post { height: 222px; margin: 1%; }@media only screen

Maison Médicale de Braine l'All

   MAISON MÉDICALENotre maison médicaleNos valeursLe forfaitNotre équipeNos partenairesACTIVITÉSActivitésVignettes santésLES SOINSNotre approch

Acasă - Citiți.Iubiți.Trăiț

  Skip to contentAcasăCărțiConcursuriCulturăInterviuriReduceri și RecomandăriRecenziiTop CărțiConsiliere OnlineDezvoltare personalăArticole de

Protecting Brands Online with AI

  Skip to Main ContentYonder has been acquired by Primer, a leading NLP company for risk and security applications.Learn More SolutionsRisk Intellige | Số điện thoại củ

  MENUCouponTin tứcLiên hệ/* Style the navigation menu */.topnav { overflow: hidden; background-color: #333; position: relative; display: none;

Make Music Hawaii

   0 Skip to Content


Hot Websites