A few weeks ago, we hosted our first AI Finance Hackathon and invited 10 companies. They spent the day building AI for their own work: remittance matching, chasing late payments, treasury forecasting, intercompany reconciliation, flux analysis and more. Watch how the day went. 👇 Thank you to the teams in the room: 9altitudes, Aikido Security, Copus, Guardsquare, House of HR, In The Pocket, Lighthouse, Pluxee and Telenet group
Eagl
Software Development
Ghent, Flemish Region 1,466 followers
AI Agents for the month-end close
About us
Eagl builds AI agents that automate the month-end close for multi-entity, mid-market finance teams, pairing the automation of repetitive close work with a data-quality layer that catches and corrects errors the moment transactions post. The result is a faster, more reliable close, reporting teams can actually trust, and a finance function that stops losing good people to manual grind. Connect your ERP/ acounting systems in minutes - no setup. Our agents scan every transaction for anomalies, misallocations and duplicate entries. Get variance insights with root-cause explanations. Orchestrate closing tasks in real time - fully auditable and always up-to-date Visit us: www.geteagl.com
- Website
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https://geteagl.com/
External link for Eagl
- Industry
- Software Development
- Company size
- 2-10 employees
- Headquarters
- Ghent, Flemish Region
- Type
- Privately Held
- Founded
- 2025
Locations
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Primary
Get directions
kleindokkaai 9a, 9000 Gent
Ghent, Flemish Region 9000, BE
Employees at Eagl
Updates
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Upvest is a leading investment infrastructure provider in Europe, powering some of the largest banks and wealth platforms with their API-first trading technology. As they scaled, their finance team had to manage high transaction volumes and rigorous compliance requirements across multiple entities, getting everything cleanly and accurately into NetSuite. To scale efficiently, the underlying manual close tasks, like manually matching transactions, tracking manual VAT risks, and managing accruals, had to be run autonomously. That is why Upvest's VP of Accounting & Reporting, Toni Krüger, chose Eagl to go beyond static close tracking and embed AI accounting agents directly into their record-to-report workflows.
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We are super excited to officially announce our partnership with Payhawk! 🚀 Corporate spend management and the month-end close belong in the same workflow. Today, we’re making that a reality. For too long, multi-entity finance teams have dealt with the exact same friction: spend happens in one system, and the close is managed in another. That gap creates a natural lag at the end of the month. Together, Eagl and Payhawk are completely eliminating that gap.
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Accruals are one of the hardest things to automate in accounting. We just cracked it. Eagl now runs the full accrual lifecycle automatically: detect the month an expected invoice never posted, book the accrual, write it to your ERP, and reverse it on its own when the invoice arrives. Plus a full cutoff analysis every close. Rolling out now.
Accruals are one of the hardest things to automate in accounting. Today I'm proud to say we cracked it. It sounds simple: an invoice is expected, so you book the cost and reverse it when the invoice lands. In reality it's messy. Most teams run it in a spreadsheet, lean on the PO system, or just reverse everything monthly. The spreadsheet depends on one person remembering. The PO system only sees what got a PO. And reversing everything buries the real exceptions in noise. Miss a reversal and your P&L takes a double hit, usually caught weeks later. So we built a new way to run the full accrual lifecycle: → Detect: Eagl spots the month an expected invoice never posted → Post: it books the accrual and writes it straight to your ERP → Reverse: when the invoice arrives, it reverses the accrual on its own Eagl runs a full cutoff analysis every close and surfaces what to recognize across periods: → Prepayments & deferrals → Provisions → Depreciation & amortization
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Eagl reposted this
A lot of you asked to see the real product, so here it is. Starting a short series on how Eagl actually works. First up: the Financial Controlling Agents. This one's a quick overview of what the agents do and how finance teams work alongside them day-to-day. Next in the series: Knowledge, Accruals, and the Data Quality agents that catch and correct misclassified bookings, such as the wrong cost center, cost unit, GL account or project. As any self-respecting vlogger would say: like and follow for the rest.
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Most finance teams catch accounting errors by hunting for outliers in a reporting tool. Which means you only catch the ones big enough to stand out. Eagl works differently. Our financial controlling agent reviews every journal entry and document against every check your finance team typically runs. No sampling. It flags what needs your attention, explains why, and proposes the corrective action. Controlling finally becomes proactive.
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Eagl reposted this
Today, we’re launching Eagl. AI will change finance. That part feels inevitable. But AI is only as good as the data underneath it. That's why we built Eagl: AI agents that continuously review accounting data, detect mistakes, and help finance teams trust their numbers. Before finance can be automated, the data has to be right.
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Today, we’re launching Eagl. AI will change finance. That part feels inevitable. But AI is only as good as the data underneath it. That's why we built Eagl: AI agents that continuously review accounting data, detect mistakes, and help finance teams trust their numbers. Before finance can be automated, the data has to be right.
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We organised the AI Finance Hackathon at Wintercircus Ghent last week. Ten of Belgium's leading finance teams spent the day building on real problems from their own teams. What stood out was how much overlap there was in the room. Reconciliation that eats days. Intercompany differences that bounce between countries. Variance comments that need a finance partner to crosscheck one by one. Manual checks across dozens of entities. One reflection from the day: building a working prototype turned out to be the easy part. The harder questions sit on either side. Scoping the right problem upfront. Processing large volumes of data at a reasonable cost. Keeping data quality high enough for the model to be trusted in production. Congrats to Lighthouse for the win with a remittance matching agent that turns Salesforce and NetSuite cases into one-click approvals. Runners-up Pluxee (2nd) with their penalty invoicing system, and In The Pocket (3rd) with BUDGY, an AI-powered budget variance platform. And to the other finance teams that brought real problems and the energy to match: Telenet group, Copus, Mint Tandartsen, House of HR, Aikido Security, 9altitudes & Guardsquare Big thanks to Spott, McKinsey & Company, Finhouse and Smartfin for making this happen together.
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10 teams. 1 room. 1 day to ship something real. 26 May, we're hosting the AI Finance Hackathon. Bringing teams from Aikido Security, Pluxee, Lighthouse, Telenet group and six other leading Belgian companies together at Wintercircus Ghent for one full day of building. Each one walks in with a real problem from their finance division. Each one walks out with a working solution. The premise behind the day: finance teams are still closing books manually while the AI that could do it already exists. We're closing that gap. Live, on real data, in one sitting. Built together with our partners at Spott, Eagl, McKinsey & Company, Finhouse and Smartfin. Judged by: Jeremie Sneessens (Managing Director, McKinsey BeLux), Thomas Guenter (Managing Partner, Finhouse Fund), Sebastien Thiel (Partner/CFO, Smartfin) and Tycho De Saeytyd (Head of US, Spott). No theory. No demos. Just building.
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