Use cases

AI for modern portfolio management.

From single funds and wealth portfolios to multi-strategy platforms, AutoCIO adapts to the use case - with a consistent AI signal layer, optimiser, and reporting stack underneath.

Portfolio Managers

Enhance existing strategies with AI-driven signals and optimisation. AutoCIO identifies where performance, risk, and diversification can be improved without changing the investment thesis or mandate.

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Wealth Advisors

Deliver hyper-customised, institutional-grade portfolios to every client. Build tailored strategies across multiple mandates, risk profiles, and asset classes at scale, while reducing operational complexity and cost.

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Platforms

Integrate AutoCIO’s AI signals into fund-of-funds and multi-strategy portfolios. Connect via API or Python SDK for seamless integration into existing infrastructure, workflows, and portfolio decision-making processes.

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Use case 01

An AI overlay on your existing strategy.

AutoCIO adds a forward-looking AI signal layer to your existing investment process. It complements your fundamental view, identifies opportunities, and highlights where portfolios may need review.

  • Support investment decisions - AutoCIO brings forward-looking AI signals into your process, helping teams test conviction, challenge assumptions, and uncover opportunities across every holding.
  • Signal-driven rebalancing - 230,000+ daily signals across 50,000+ equities identify where conviction is strengthening or weakening, making rebalances evidence-led.
  • Risk & diversification checks - Monitor factor exposure, sector concentration, and tracking error, with mandate and risk parameters built into each rebalance.
  • Compliance-ready outputs - Apply mandate-aware constraints, retain a full audit trail on every AI recommendation, and generate one-click factsheets for client and compliance reporting.

Use case 02

Institutional-grade portfolios for every client.

Build tailored portfolios around each client mandate without starting from scratch. AutoCIO applies risk limits, values-based constraints, and custom tilts up front, so every portfolio reflects the client’s objectives.

  • Customisation at scale - Manage thousands of individually tailored mandates across clients, families, and portfolios. Each investor gets a strategy built around their bespoke objectives.
  • Reduced overheads - Deliver highly customised active equity strategies across clients and mandates without proportional growth in manual work, infrastructure, or headcount.
  • Client-ready reporting - Branded factsheets, attribution and plain-English commentary are generated quickly, ready for review meetings or quarterly reports.
  • Regulatory fit - MiFID II, SFDR and suitability documents are produced automatically, with a clear evidence trail behind each AI-supported decision.

Use case 03

Built to fit your infrastructure.

Plug AutoCIO into your investment infrastructure through API, Python SDK, or enterprise deployment. Pull signals, run optimisations, evaluate strategies, and generate reports inside existing workflows without disrupting surrounding systems.

  • API-first - Access signals, optimisation, analytics, and reporting through standard endpoints, so AutoCIO fits into existing pipelines without disrupting surrounding systems.
  • Python SDK - Test ideas, analyse portfolios, and move from research to live strategy in the tools your quant and investment teams already use.
  • Agent-ready connectivity - Connect AutoCIO through REST API, Python SDK, and MCP, embedding signals, optimisation, and reporting into existing tools and AI workflows.
  • Enterprise deployment - Run AutoCIO in a dedicated Google Cloud environment, with regional data hosting, SSO, user permissions, and encryption built in.