CUSTOMER Q&A: Piere

Piere helps people align their money with the life they want to live. Its platform combines AI-powered insights and automation to make personal finance feel less like manual upkeep and more like a system that works in the background, helping users plan ahead, adapt in real time, and move money toward their goals with less effort.

But delivering that kind of experience depends on having financial data that is accurate, current, and structured enough to support personalization at scale. After running into issues with connectivity, outages, and incomplete account data from a previous provider, Piere turned to Plaid for stronger connections, consistently refreshed transactions and investments data, and the account details needed to support more agentic money movement. In this conversation with Yuval Shuminer, Founder and CEO at Piere, we talked about the importance of reliable data and how AI is transforming money management into a more intelligent, hands-off user experience.

Plaid: A big part of Piere’s mission is to make personal finance effortless. What does that mean in practice for your users?

Yuval: Traditional personal finance tools are mostly backward-looking. They show users where they’ve been, but not where they’re heading—and often with stale data. They also tend to require too much manual work to stay useful. We think that runs counter to how people want to engage with technology today.

For us, effortless means enabling what we think of as self-driving money: using personalized financial intelligence trained on a user’s actual money and habits to plan ahead, then automatically moving money between connected accounts to help them reach their goals. The aim is a hands-free experience that creates better lived moments by removing the hurdles to keeping them funded.

Plaid: How does AI show up in the Piere experience today?

Yuval: We use AI to personalize automations, create budgets based on a user’s spending and income patterns, identify opportunities for growth, and design tailored plans for things like boosting savings, maximizing interest-earning opportunities, or repaying debt. We also use it to automatically move funds between accounts when conditions are right.

As the underlying models have improved, with little to no hallucinations when presented with real data, we’ve been able to trust AI with more of the user experience. That means fewer required inputs, more adaptive guidance, and a product that can meet users at their level of financial understanding.

Plaid: What challenges were you running into before working with Plaid?

Yuval: We were using a data aggregator that struggled with dependable user account connections and had more frequent system outages. That’s a major problem when your product depends on current balances and transaction history to create budgets or propose liquidity plans.

It also lacked account details that now allow us to facilitate agentic money movement for our users. In an AI-powered personal finance experience, incomplete or delayed data breaks trust quickly. If a user asks a question and gets an inaccurate answer because the information is missing or stale, confidence in the AI erodes immediately.

Plaid: What made Plaid the right fit?

Yuval: We were looking for more uptime, fewer dropped connections, and access to institutions that were missing with our previous provider. Plaid stood out on all three. Plaid’s integration with Dwolla also became a major selling point for us, because it enabled a faster buildout of Moves, our agentic money movement product.

Plaid: Which Plaid capabilities are most critical to the Piere experience today?

Yuval: Real-time balance data, transaction enrichment, ACH account details, and the Dwolla integration are all critical. Together, they give us a more complete and normalized view of a user’s finances.

That structured data helps us write code faster, better predict and format the information we need, and create a more complete financial picture with fewer inputs from either our backend or our users. That’s what makes the promise of self-driving money feel real: less user input combined with accurate available data equates to a magical agentic experience for the end user.

Plaid: How has Plaid’s integration with partners like Dwolla shaped what you can offer customers?

Yuval: It’s been game changing. The integration lets us bypass more complex money movement implementations, which means we can build faster and test UX assumptions more quickly without dramatically increasing engineering capacity.

Plaid: What impact have you seen since implementing Plaid?

Yuval: The biggest measurable improvement is on connectivity. User complaints about account disconnections have been cut by more than half, and requests for missing institutions have also decreased by more than half.

More broadly, better data quality is foundational to the AI experience. If the data isn’t right—and right on time—the AI can’t operate in a way users will trust. Plaid helps give us the reliability we need to deliver that experience.

Plaid: Trust matters even more when AI is involved. How do you approach that with users?

Yuval: We focus heavily on transparency. We communicate explicitly how user data is used, and we stress that it is never sold. We reinforce that during onboarding, ahead of account connection and KYC verification, and even in our post-signup drip campaigns. What we’re seeing is that when we volunteer that transparency, trust starts high and stays high through additional data collection moments.

Plaid: What’s next for Piere, and how do you see Plaid supporting that roadmap?

Yuval: We’re continuing to expand the reach of our AI-generated financial plans in the app, including into liabilities like loans and credit cards. We’re also growing our B2B offering through digital onboarding and enterprise-to-consumer financial data products that help large institutions better understand consumer needs and connect them to the right solution faster. Plaid will continue to be a key part of that foundation.