How to vet family office software vendors in the age of AI

Suddenly, every software vendor in the wealth space claims to be “AI-powered”. But as anyone who's sat through more than one sales demo in the past 18 months can tell you, AI has become a marketing crutch.

One platform uses autocomplete and calls it predictive intelligence. Another pipes in ChatGPT and declares a revolution.

Meanwhile, family offices are dealing with the real complexities of wealth: Intergenerational handovers. Multi-entity structures. Illiquid alternatives. Shifting regulations. And a rising next-gen who won’t tolerate outdated systems that need a PDF to explain a PDF.

So, to arm you with a checklist and guide to vet these high-promise vendors in the age of AI and separate the hype from the genuinely valuable, we’ve created this straight-talking list of what to look for (and what to run from).

1. Does the vendor have a working API?

This question is your strategic litmus test.

A public, well-documented API is like a sign saying: “We play well with others”. It tells you the vendor is serious about extensibility and interoperability. Without it, you're locked into whatever the vendor decides to build – and on their timeline. Worse, you’ll struggle to connect your own analytics tools, AI models, or third-party applications.

In the AI era, you’re going to move data in and out of systems frequently. Whether it’s piping fund data into your own LLMs, building custom dashboards, or triggering workflows with smart agents, fluid data exchange is non-negotiable.

So, if the vendor says, “We don’t offer an API yet, but we’re thinking about it”… it’s a red flag. They’re not building for modern infrastructure. They’re building for control.

2. Can they clearly explain their AI architecture and strategy?

Ask this, and watch what happens.

If you get a coherent explanation of when they use LLMs, when they rely on classic statistical models, and when they deliberately don’t use AI – good. You’re speaking to a team that understands its own product.

If, instead, they say things like “our platform leverages cognitive synergy for AI-driven workflows” – well, you’re in buzzword territory. Duck out. Fast.

Real platforms will tell you:

• “We use large language models for parsing capital calls and generating summaries.”

• “We detect outliers in performance data using time-series anomaly detection.”

• “We use logic rules – not machine learning – for tax treatment tagging because it’s more reliable.”

That shows they not only understand AI but also understand its limits.

3. What AI functionality is actually live – today?

Some platforms sell an AI story that sounds amazing… until you realize the only thing in production is predictive typing in the search bar.

Ask for a live demo of real, production-level AI features used by actual clients.

That means things like:

• Automated parsing of manager letters and fund documents.

• Natural language reporting on e.g. portfolio exposure.

• Summarization of GP updates.

• Detection of missing or inconsistent NAVs or cash flows.

• Entity-level tagging for distributions, commitments, or capital calls.

Bonus points if these features are used daily by family offices like yours – not just internal testing teams or beta clients from another vertical.

Bonus points if these features are actually being used – not just by internal testing teams or beta clients from another vertical, but by real family offices managing real capital.

4. How does the platform ingest, normalize, and structure your data?

This might sound dry, but it’s critical: AI is only as good as the data beneath it.

Because the devil isn’t just in the data, but in the details of how that data gets in.

Some platforms lean on third-party integrators or manual uploads. Others build their own ingestion pipelines to maximize fidelity and reduce error. But here’s the key: you want precision, not just “data in”.

If the platform is piping in “high-flying but crappy” data, guess what? You’ll get high-flying but crappy outputs.

This is the real challenge in consolidated reporting: not just getting any data in, but getting the right data in, structured and ready for AI to use.

So, dig deep here. Ask:

• How does your platform ingest PDFs, Excel sheets, bank feeds, and data from fund administrators?

• How does it reconcile capital calls, distributions, and commitments across entities and custodians?

• Does it use automated classification or does it rely on manual processing?

A strong platform should be able to demonstrate that your portfolio data is structured, contextualized, and immediately usable for querying, analysis, and automation.

This is where great platforms quietly outperform mediocre ones.

5. How does the vendor handle data security and AI model transparency?

Let’s be clear: family office data is sensitive. Security is mission-critical.

Your AI tools need to be both powerful and private.

So you want to see:

• Consent-based training: Your data should never be used to train shared models unless you explicitly say yes.

• Auditable outputs: Every AI-generated summary, alert, or insight should be traceable back to the data that produced it.

Also ask them about their approach to different model types:

• When do they use large-scale commercial LLMs like GPT?

• When do they rely on open-source models?

• When do they deploy private, client-specific models?

• And when do they deliberately avoid AI altogether because a rule-based engine is safer?

If a vendor can’t explain how their models work, where they’re hosted, and what guardrails they’ve built, you’re dealing with a black box. And black boxes don’t belong anywhere near fiduciary-grade decision-making.

6. Are they ready for the next frontier – agent-based AI?

Agent-based AI is coming fast. Picture smart agents that can log in, pull reports, rebalance portfolios, even flag capital call anomalies. This next generation of tools will rely on standards like the Model Context Protocol (MCP) to securely interact with financial systems.

A platform that’s truly future-ready will already be working toward MCP compatibility or at the very least, have a composable API and permissioning structure that allows for safe agent interaction.

If your vendor’s roadmap doesn’t mention MCP, intelligent agents, or any sort of automation beyond dashboards… they’re not building for what’s coming.

7. Can your team extend the platform or are you locked in?

The best platforms are composable. That means your CIO, CTO, or even a tech-savvy analyst should be able to build on top of them.

Ask:

• Can we access structured data from tools like Excel or Power BI? (And can Copilot or other assistants run on top of it?)

• Is there a tabular “data cube” or model that allows us to explore data flexibly, by account, entity, or asset class?

• Can we export data easily, without limitations?

• Do you provide SDKs or developer tools to build custom dashboards and automations?

• Can we push and pull data between your platform and others we use?

If every customization requires a statement of work, you’re not a partner, you’re a prisoner.

8. How will they price AI and what’s the real cost over time?

Right now, a lot of vendors are bundling AI features for free. But don’t assume that’ll last. Some are already plotting usage-based pricing or tiered access based on seats, tokens, or model calls.

Be clear up front:

• Will you own the AI-generated outputs?

• Will you be charged extra to access insights from your own data?

• What happens if you want to move your data and models elsewhere?

You deserve to know where the model sits, who owns the IP, and what’s behind the curtain on pricing – before you make a long-term commitment.

9. Who owns the company and what are their incentives?

Finally, zoom out.

A vendor’s funding and ownership structure tells you a lot. Are they founder-led with a long-term vision? Or are they owned by a PE fund looking to flip the company in 3-5 years?

Also ask:

• How much of their business comes from family offices and institutional wealth?

• How many features were built for your use case vs. repurposed from other sectors?

• Are they building for long-term alignment or short-term monetization?

Because if your vendor’s incentives aren’t aligned with yours, it’s only a matter of time before it shows up in pricing, support, or roadmap neglect.

Final thought: Choose a platform that helps you lead

You need a vendor who doesn’t just check the AI box but gives your team the foundation, tools, and flexibility to lead in the years ahead where AI will power everything from document workflows to investment governance to personalized reporting for principals.

Ask the hard questions. Dig into the details. Look under the hood.

And if a vendor can’t walk you through what’s real, what’s shipping, and what’s next… thank them for the coffee and move on.

How we think at Aleta

At Aleta, we aim to stay at the forefront of innovation without compromising on what matters most: trust, transparency, and data integrity.

We believe in building a great standard platform. One that works seamlessly out of the box, with a native app, intuitive UI, and a clean user experience that just makes sense.

But we also know that data is everything.

You can’t build intelligence on top of noise. That’s why we don’t just rely on third-party aggregators. Instead, we’ve built the most important integrations ourselves, in-house, to ensure precision and control. And where we do bring in external data sources, it’s through a carefully vetted, deliberate process.

We also believe your data shouldn’t be locked away behind a dashboard. You should be able to model it, explore it, build with it, and increasingly, ask AI to help you make sense of it. That’s why we’ve built a modern, open API (already preparing for MCP compatibility), and a structured data cube that makes reporting in Power BI, Excel, or even your favorite AI copilot seamless and powerful.

We’re building Aleta for the AI era. Not with hype, but with real capability under the hood and deliberate choices about where, when, and how we integrate AI into workflows.

We love talking about this space – the future of AI, data, and wealth tech. So, whether you're comparing platforms or just exploring what's next, reach out. Even if we're not your end destination, we’ll help you ask better questions along the way.