Float Launches Float Intelligence, Finance AI Purpose-Built for the Canadian Business Efficiency Squeeze

Trained exclusively on real Canadian transactions, Float’s first AI agent outperforms general-purpose LLMs by 28 percentage points, giving businesses back hours they can’t afford to lose in the current economic climate.

TORONTO--(BUSINESS WIRE)--Float today launched Float Intelligence, an AI and automation layer embedded across the finance platform where more than 7,000 Canadian businesses manage payments, optimize cash flow and close their books. Its first capability, a transaction coding agent, automatically assigns GL codes and Canadian tax codes—HST, GST and PST—to corporate card transactions, turning what used to require hours of line-by-line coding into a process that takes minutes.

"We didn't set out to build an AI product. We set out to remove the everyday friction caused by Canadian businesses being handed infrastructure that was never designed for them,” said Rob Khazzam, Co-Founder and CEO at Float. "We spent six years fixing that foundation. Float Intelligence is what becomes possible once it's right.”

The launch comes as Canadian businesses face a deepening efficiency squeeze. A recent Float report found that while revenue grew 5% last year, profits declined, cash reserves dropped nearly 5% and debt stayed flat. Businesses are burning reserves to stay operational, not borrowing to grow. In a country where half of SMBs spend up to 40 hours a month on payments and reconciliation alone, Float Intelligence is designed to give these businesses the advantage they need now, not by adding capital, but by giving finance teams back the operational capacity to deploy it more strategically.

Float Intelligence first tackles transaction coding

The first Float Intelligence capability is a transaction coding agent, which automatically assigns GL codes and a range of tax codes to card transactions. Designed specifically for the Canadian context, Float’s agent handles the complexity of provincial tax structures, the variance in how Canadian businesses categorize spend and the accuracy threshold finance teams require before trusting a system to act on their behalf.

• Confidence-gated coding: The system only auto-codes when confidence meets Float's 90% accuracy threshold. When it's not sure, it routes the transaction for human review rather than guessing.
• Self-improving and hyper-personalized: Instead of a one-size-fits-all approach, the model powering the agent is calibrated to each business’s specific chart of accounts and coding history, and learns from every correction or modification made by the user.
• Built for privacy: Float runs all inference in its own secure AWS instance, not through third-party LLM providers. No transaction data or coding decisions are shared between businesses. Each customer's model is calibrated on their data alone.

Why general-purpose AI falls short

On a benchmark of 5,000 real Canadian transactions, Float's transaction coding agent achieved 90% precision. A leading general-purpose LLM, tested on the same dataset, scored 62%.

The gap comes down to specificity. General-purpose models don't understand how Canadian businesses actually code their spend. Float's architecture pairs a large language model with a proprietary per-business calibration layer trained on years of Canadian transaction data. It learns each customer's chart of accounts, vendor relationships and tax assignment patterns. It knows when to act and when to abstain.

"Accuracy and trust are non-negotiable for finance teams," said Ruslan Nikolaev, Co-Founder and Head of Product at Float. "Because Float already sits at the centre of how these businesses manage their spend, the model learns from how each customer actually works. If it isn't confident, it stays out of the way."

Early results

During beta testing across 350+ Canadian businesses, Float's transaction coding agent achieved 95% measured precision on eligible auto-coded transactions. Finance teams using the system are shifting from line-by-line coding to a quick review-and-approve workflow.

"Month-end close used to mean four hours of manual GL coding. Now Float's transaction coding agent handles the first pass and it's right over 90% of the time. I review what actually needs my attention and move on," said Wilford Lam, finance lead at Layerzero. "We're getting three hours back every single month, time we can use to drive strategic impact across the company. It's one of those features that makes you wonder how you managed without it."

What comes next

The transaction coding agent is the first Float Intelligence capability. Over the coming months, Float will extend the same approach—purpose-built for Canada, personalized by default—across more of the platform. The goal is to give Canadian businesses hours back every month, moving finance teams from manual busywork to work that actually moves the business.

The transaction coding agent is available now to all Float Professional plan customers. It activates automatically and begins learning each team's coding patterns from day one.

About Float

Float is Canada's complete business finance platform, combining modern financial services and software to help businesses spend, save and grow. Trusted by more than 7,000 Canadian companies, Float provides high-limit corporate cards, automated expense management, next-day bill payments, high-yield accounts and fast, friendly support—all built in Canada, for Canada.

floatfinancial.com