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Documentation Index

Fetch the complete documentation index at: https://help.daylit.com/llms.txt

Use this file to discover all available pages before exploring further.

Daylit’s AI engine runs on a schedule and continuously generates insights for every customer, invoice, and your portfolio as a whole. You don’t trigger these manually — they’re produced automatically and stored so they’re always ready when you open a customer detail page, an invoice record, or the AI Insights tab. Each insight is grounded in your actual data: payment history, communication threads, aging metrics, and behavioral patterns observed over time.

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The 7 insight types

Signals detect risk conditions and behavioral patterns at the customer, invoice, and portfolio level. Each signal includes a severity rating, one to three tags from a fixed taxonomy, and metric-backed evidence explaining why the signal fired.Customer signalAnalyzes payment behavior across a customer’s full history to detect risk conditions such as:
  • Payment behavior worsening or improving versus the customer’s own baseline
  • Chronic late payment patterns (mild, moderate, or severe)
  • Accelerating deterioration month-over-month
  • A historically reliable payer who has recently missed expected timing
  • Ghosting — unresponsive to outreach despite an open overdue balance
  • Churn risk — balance declined sharply, customer gone quiet, remaining balance deeply aged
  • High portfolio impact — the customer’s overdue balance is a material share of your total AR
The signal also flags positive conditions, such as a customer who is consistently on time or improving their payment behavior.
Invoice signalEvaluates the status and risk of a single invoice. Example signals include:
  • Action required — needs human intervention now
  • Promise to pay active — customer committed to pay by a date; collection is paused
  • Auto-reminding — the AI is running a drip campaign; no human action needed yet
  • Disputed — flags pricing disputes, missing PO numbers, or delivery/quality issues
  • High risk of default — the AI predicts this invoice is unlikely to be paid
  • Payment imminent — customer has viewed the invoice, clicked a payment link, or stated it’s being processed
Portfolio signalScans your entire AR book for trends that affect the portfolio as a whole — concentration risk, aggregate aging deterioration, shifts in average days-to-pay across all customers, and other portfolio-wide patterns that don’t surface when you look at individual accounts in isolation.

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Customer strategy plan

The strategy plan is a recommended collection action for a specific customer, generated by the AI based on the customer’s current risk signals, conversation history, open invoice balances, and behavioral patterns. Each strategy plan includes:
  • Recommended action — whether to send an email, make a call, or create an internal follow-up task
  • Reasoning — why this action is recommended given the current account state
  • Urgency score and bucket — a 0–100 score and one of five categories: CRITICAL, TODAY, THIS_WEEK, UPCOMING, or INFO
  • Due date — when the action should be performed
  • Action details — depending on the recommended action type:
    • Email — a drafted subject line, body, tone (friendly, urgent, firm, etc.), and template stage
    • Call — a contact, call script with 3–7 talking points, anticipated objections, and success criteria
    • Internal follow-up — an assignee, task description, priority level, and context explaining why the task is needed

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Where to view insights

LocationWhat you’ll find
Customer detail pageCustomer conversation summary, customer signal, and customer strategy plan
Invoice detail pageInvoice conversation summary, invoice signal, and payment date prediction
AI Insights tabAll insights across your portfolio, filterable by type, customer, or invoice

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Giving feedback on an insight

You can rate any insight with a thumbs up or thumbs down directly from the insight card. Your feedback is saved and helps the Daylit team understand where the AI is performing well and where it needs improvement. You can also add a short comment to explain your rating. To remove your rating, click the same button again to toggle it off.

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How often insights are refreshed

Insights are generated automatically on a schedule — you don’t need to request them manually. When new data arrives (a payment recorded, an email received, an invoice updated), the relevant insights are queued to refresh so the information you see reflects the current state of your AR book.
If you’ve just received a significant payment or email and want to see updated insights, check back after a few minutes. The scheduled pipeline processes new data continuously throughout the day.

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Insight confidence and evidence

Every insight includes a confidence indicator. Higher confidence means the AI had strong supporting data — a long payment history, recent communication, or clear behavioral pattern. Lower confidence means the AI is working with limited data, such as a new customer account or a customer with few closed invoices. Where applicable, insights also include evidence — specific data points or communication excerpts that explain why a signal fired or why a prediction was made. You can use this evidence to verify the AI’s reasoning before acting on it.