AI Driven Company Analytics

We use advanced machine learning techniques to support unbiased, high-quality equity research for investors and fund managers.

Asset Management is Changing

Regulatory and technological changes mean there has never been a greater need for high quality equity research at an affordable price.

Shift to passive investment

Increased costs due to MiFID II

Tech-savvy Millenials

Fintech and robo-advisor disruption

By enhancing your research base and providing trusted models to support your investment decisions, is here to empower the innate abilities of your business.

Our unique approach

Machine + Man

produces machine-driven forecasts without opinion that are unique to each company. On top of this you can add your own knowledge and insights.

Service and Performance

collects and analyses more data than is humanly possible, creating a more complete financial model with a more accurate assessment of the risk inherent within it.

Unrivalled Coverage

is size agnostic. It can give insight into any company, whether listed or not, creating unbiased, high quality, relevant and timely information on any company that you wish to investigate.

Conventional Research

Analysis by The Economist showed strong bias with 49% ‘buys’ to 6% ‘sells’ [2].
Tells you 'what the numbers say', giving you unbiased forecasts and insights.
Huge volumes and lack of trust means only 2%-5% is actually read [1].
A uniquely fact-based and scientific approach that mitigates and quantifies risk.
Static and infrequently updated.
Continually updated, always learning.
Huge volumes of data that is time consuming to assimilate.
Highly focused research insights that can be customised to your needs.
Focused on larger firms, with highly partial coverage of small firms.
Broader coverage, including small cap and unlisted firms.
MiFID II has made research a cost that is hard to pass on, eroding margin.
Inexpensive and helps to eliminate poor quality providers, restoring margin.
Keeps you busy, limiting time available to focus on your business.
Surfaces the knowledge you need so you have more time to maximise your returns.

Securing your business.
Empowering your abilities.
Protecting your margin.

Our analytical engine

creates individual and unique financial models for each company.

Our analytical engine identifies a complete web of interconnections across a company's set of financial statements, making it difficult to hide unwanted disclosures and determining how the company connects to the external world - whether that is the economy, world markets or the company's competitors.

The resulting financial model can be used immediately for your investment analysis and risk assessment, or it can be used to give new insights into the make-up of an investment portfolio. You can even modify the model with your own assumptions to incorporate your own insights and knowledge.

Flexible to meet your needs

Investment Managers

Have better faith in your buy and sell decisions by using data-driven financial forecasts and models that are unbiased and up to date. Test multiple hypothesis and assumptions. Quantify the risk in your portfolio strategies.

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Have a unique lens in your analytical approach to financial assessment. Examine sector trends ('is this company unusual?'), improve your asset valuation, test goodwill, impairment and remuneration structures, and get a better apportion Going Concern.

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Company Valuations

Screen and value target companies quickly and easily. Identity alternative companies from within a sector or across other sectors that have a similar financial profile. Identify your most suitable acquisition targets and test them against the external world.

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Vincent Julier


Vince has over 30 years of global experience in finance. After a 23-year distinguished career at BP plc, he was a founder of two successful private equity and financial advisory firms. In addition, Vince was Assistant Keeper of the Privy Purse in Her Majesty The Queen’s Royal Household and is a Non-Executive Director for Enbridge Rampion UK.

James Hood-Smith


James has a PhD in Computer Science, 20 years experience as a full stack software developer, data scientist and consultant and an overlapping 12 years as a university teaching fellow then school teacher. He has been an 'Agile Consultant' and led development on a number of projects involving distributed systems and Big Data.