Question 1

How does Palm's AI forecast differ from what my TMS already does?

Accepted Answer

Most TMS platforms rely on open AR/AP from your ERP plus manual inputs; no intelligence, no pattern recognition. Palm runs 25+ machine learning models, including foundation models trained on financial time series, to learn from your historical payment patterns. The AI fills the gaps where ERP data doesn't exist, while still using your booked AP/AR data as the foundation for short-term accuracy. You see exactly which source is driving each forecast line: ERP, ML, or manual.

Question 2

What data does Palm use to forecast cash?

Accepted Answer

Depending on your teams specific needs, Palm is able to leverage from multiple data sources. We typically start with historical activity from bank statements pulled directly from your banks, ERP, or existing TMS.

Question 3

How accurate is Palm's cash forecasting tool?

Accepted Answer

Every company has different objectives and KPIs for forecasting accuracy. Palm aims to improve accuracy from your baseline through machine learning and variance analysis.

Question 4

Can we still make manual adjustments to the AI forecast?

Accepted Answer

Absolutely. Palm gives you the AI baseline as a starting point, and your team can override, adjust, or add line items at any level. You can add one-off forecast items for payments the system doesn't know about, or batch upload entire category forecasts from Excel or CSV. Every source; ERP, ML, manual, is clearly labeled so you can measure whether human overrides improve or hurt accuracy over time.

Question 5

How long does it take to onboard with Palm?

Accepted Answer

We appreciate that every day spent implementing a solution is one day lost of deriving value from it. We leverage AI and modern connectivity practices to reduce implementation timelines from months to weeks or even days.

Question 6

How does cash forecast scenario planning work?

Accepted Answer

Scenario planning in Palm lets you apply percentage-based adjustments to any forecast category — like "-5% on collections" or "+10% for seasonal payroll" — and see the impact instantly across your cash position. Adjustments preserve your underlying weekly and daily patterns, so a 5% reduction distributes intelligently across your existing forecast shape rather than flattening the line. You can create named scenarios (base case, conservative, aggressive), compare them side by side, save them for board reporting, and track how assumptions change over time.

Question 7

Does Palm replace my TMS?

Accepted Answer

No. Palm sits on top of your existing TMS and ERP infrastructure as an intelligence layer. Your TMS continues to handle payments and bank connectivity while Palm adds AI-powered forecasting, variance tracking, and scenario planning on top of the data flowing through your existing systems. You don't need to migrate, rip-and-replace, or run complex integration projects. Palm uses a read-only architecture, and most teams are live in weeks.

Question 8

What ERP and data source integrations does Palm support for forecasting?

Accepted Answer

Palm integrates with major ERPs including NetSuite, SAP, and Microsoft Dynamics, plus banking platforms via API and accounting systems. Batch uploads from Excel and CSV are supported for any source without a direct integration — tax payment schedules, talent cost forecasts, and similar category-specific data. Your existing data infrastructure stays intact, and Palm's read-only architecture means no changes to your ERP or banking setup.

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