Industry Context

AI is reshaping investing.

The data that drives fundamental investing — filings, transcripts, news, alternative signals — was until recently too unstructured for machines to read. That barrier has fallen. Machines now read this material faster, more consistently, and at a scale no human team can match.

Scale and consistency

The platform processes more signals, faster and more consistently, than any human team. No herding, no anchoring, no style drift.

Continuously improving

Models improve continuously. The edge grows over time rather than eroding with market cycles.

New data, new signals

Alternative data, news, earnings call transcripts, satellite imagery. Signals humans cannot analyse at scale, now tractable.

Three core capabilities

Three technology capabilities, used together or independently.

One investment engine, three deployment patterns. Mix and match by mandate.

Manager overlay

Analytics across your existing managers.

  • Run analytics across the existing manager line-up
  • Look-through analysis surfaces hidden factor, sector and geographic concentration
  • Identifies style drift and manager overlap
  • Consolidated reporting across the full portfolio
  • Manager relationships unchanged
ETF construction

ETF basket construction

  • Systematic selection and weighting of ETFs across a curated universe
  • Look-through exposure analysis drives fund selection and risk budgeting
  • Risk-budget construction across the basket for stronger risk-adjusted returns
  • Exposure limited to established, regulated funds
  • Cost-efficient beta with a systematic overlay
Stock selection

Systematic stock selection.

  • Systematic strategies for individual stocks
  • Established factor models combined with machine learning
  • AI-unlocked data sources: filings, transcripts, news, satellite, sentiment
  • Transparent execution and full attribution
  • Rigorous back-testing prior to deployment
Configuration

The levers you control.

Whichever capability, every mandate is configured around these parameters. The investment engine respects them as hard constraints.

Active risk target
Tracking error vs. benchmark
Universe selection
Base index for strategy inclusion
Holding constraints
Min/max distinct positions
Annual turnover
Trading limit to manage tax drag
Sector exclusions
Hard GICS sector constraints
Risk profile
Volatility limits, stop-loss triggers
Process

How the platform builds a portfolio.

The same four-step process applies across all three capabilities. Client configuration, engine, bespoke portfolio. A team of specialist AI agents runs this process continuously, under your team's human supervision.

1
Universe screened

ETF and security universe filtered for liquidity, factor exposure, mandate eligibility.

2
Signals generated

Fair-value signals, investment theses, unified BUY / HOLD / SELL scores per security.

3
Portfolio constructed

Macro regime, mandate parameters and signals combined by the PM agent into the bespoke portfolio.

4
Monitored and rebalanced

Live risk and drift monitoring. Rebalancing triggers fire against configured tolerances and client policy.

Human oversight Investment committee · quarterly review · risk sign-off

Speaking to asset managers, family offices and institutional investors. Get in touch.