This Is How We Are Creating An Autonomous AI Investment Research Analyst...

July 2026 Development Update: Come along for the ride as we create Inferent Analyst.

Jul 06, 2026

Here’s a fairly typical daily situation for an active equity investor.

You wake up and market’s have shifted overnight. A bellwether company reported and changed views on a key thematic underpinning recent stock moves.
There was a central bank development affecting global interest rates and some President somewhere made 15 all caps tweets that have sent stocks in all directions.
A portfolio company launches an equity raising - complete with investor call and presentation to be poured through and understood.
A stock you are not invested in received news reports of a major product launch that now makes it compete with one of your portfolio companies - what’s the implication?
A hedge fund or influential investor released a report attacking the earnings quality and valuation of another portfolio holding with some cleverly constructed claims.
This all needs detailed analysis and consideration as to how it may affect your portfolio and what, if any, decisions need to be made…

For many investors, there is simply no way they can dedicate the time and consideration to making well-informed judgements about all these intertwined scenarios. For most, its information overload colliding with time limitations. It takes a team.

That is where Inferent Analyst comes in…

Pre-register me for Inferent Analyst

Inferent Analyst is being designed as a wholly agentic system with multiple levels of monitoring across events, contextual information and data. The system will be monitoring around 40 news, data and information feeds, detecting changes and synthesizing implications to report these insights to you, the investor, and assist your decision making and idea generation.

Here’s an example of an integrated workflow. This represents a simplified depiction of how the system will monitor information feeds and create outputs that build upon a contextual knowledge of each stock:

This systematic monitoring and analysis process then enables highly value added feature creation built around specific investor activities:

Traditionally, this level of agentic capability has been the preserve of the world’s largest quant funds. To my knowledge, there is currently no unified system that is doing all these integrated, agentic and analytical workflows that are being built natively into Inferent Analyst - and we’re targeting price point tiers that start in reach of active retail investors with escalating allowances and features that take it all the way up to the requirements of boutique managers.

Here’s a depiction of the information feeds that Inferent will be analyzing on a live basis:

In each case, if data or events change, the system makes a materiality and impact assessment, discarding noise and prioritizing signal. It then calls upon specialist analysis workflows to analyze the particular event. The system draws upon contextual information to build depth into insights - recent news flow for current context, prior Inferent analytical reports for deeper insight, connecting the event with an evolutionary view of market expectations and knowledge - stock prices are built on a view of the future. When that view changes, stocks prices must follow.

At the same time, investor’s need to be able to see the data that insights are created from. Traditionally this has been the domain of data terminals like Bloomberg, Factset and Koyfin. However, we are building all the functionality right into the system. All the data will be there as investors have come to expect however, right alongside it will be bullet point synthesized insights on the key implications.

No more walls of numbers. Data being presented with implications attached,

So this is what Inferent Analyst will deliver. It is designed as an Analyst experience where data supports every insight and can be transparently tracked through. Agents process events and changes for you and present the reports along with context and implications without you having to ask.

But if you want to perform your own bespoke research or run regular recurring routines to synthesize insights in your own particular way from news data and events, then this functionally will be possible too with Inferent’s Task Engine. Investors will even be able to task chain to run highly sophisticated 8 step investment processes that allow you to be truly creative and determinitive as to how you look at stocks.

There is more work to do as we being this vision to life and I intend on publishing monthly updates to preview features, demonstrate data structures and mechanics and even discuss architectural and tech specific hurdles.