Daylit Launches AI Agents for Automated Collections

Daylit has launched an AI-powered collections platform that deploys autonomous agents to manage the entire accounts receivable collection workflow — from initial payment reminders through escalation and payment plan negotiation. The system represents the next evolution beyond basic automation: AI agents that make contextual decisions about tone, timing, channel, and escalation based on each customer's unique payment behavior and relationship value.

For accounting firms and finance teams struggling with the persistent challenge of collections (the average mid-market company has 15-20% of receivables past 60 days), Daylit's approach offers a force multiplier that makes one human collector as effective as a team of ten.

How the AI Agents Work

Daylit's collection agents operate across four escalation stages:

Stage 1: Proactive reminders (Days 1-7 past due). The AI sends personalized payment reminders via the customer's preferred channel (email, SMS, or in-app notification). Messages reference the specific invoice, offer one-click payment links, and use language calibrated to the customer's payment history. First-time late payers receive gentle reminders; repeat offenders get firmer language from the start.

Stage 2: Active follow-up (Days 8-30). The agent increases contact frequency and begins multi-channel outreach. It analyzes the customer's response patterns (opens emails but doesn't pay? responds to SMS? only acts on phone calls?) and prioritizes the channel with highest historical conversion. The AI can schedule calls for human collectors at optimal times based on the customer's engagement data.

Stage 3: Negotiation (Days 31-60). For accounts entering the higher-risk zone, the AI autonomously offers payment plan options within parameters set by the finance team. It can propose installment schedules, offer small early-payment discounts (if authorized), and negotiate terms — all without human intervention for amounts below a configurable threshold.

Stage 4: Escalation (Days 60+). Accounts that don't respond to AI-driven collections escalate to human specialists with a complete history of all AI interactions, customer response patterns, and recommended strategies. The human collector starts with full context rather than cold-calling a delinquent account.

Performance Metrics

Daylit's beta customers (47 mid-market companies across manufacturing, professional services, and technology) report:

DSO improvement: Average 9-day reduction in days sales outstanding. For a $50M revenue company, 9 days of DSO improvement frees approximately $1.2M in working capital.

Contact volume: AI agents generate 340% more customer touchpoints than manual collectors — sending personalized communications at optimal times 24/7 rather than during business hours only.

Recovery rates: 15% improvement in recovery on 60-90 day balances. The AI's persistent, multi-channel approach converts accounts that human collectors deprioritize due to time constraints.

Collector productivity: Each human collector supported by Daylit's AI manages 4x the account portfolio (800 accounts vs. typical 200) by focusing exclusively on Stage 4 escalations that require judgment.

Customer satisfaction: Surprisingly, debtor satisfaction scores improved 12% versus manual collections. The AI's consistent, professional tone and instant response to payment questions reduces the adversarial dynamic that human collections often create.

The Technology Differentiator

What separates Daylit from basic AR automation (email templates on timers):

Behavioral modeling. The AI builds individual payment prediction models per customer. It knows that Customer A always pays on the 3rd reminder, Customer B only responds to phone calls, and Customer C pays immediately if offered a 1% discount. Collection strategy adapts per-customer rather than applying blanket workflows.

Natural language generation. Messages aren't templates — they're generated contextually. The AI references specific invoices, acknowledges partial payments, adjusts tone based on relationship history, and even matches the formality level of the customer's own communications.

Payment friction reduction. Every AI communication includes the lowest-friction payment mechanism available: one-click ACH authorization, saved card charging, instant bank transfer links. Reducing payment execution effort from "log into portal, find invoice, initiate payment" to "click this link" converts 22% more of the "willing but lazy" segment.

Intelligent timing. The AI identifies each customer's optimal contact window (the time of day and day of week when they historically open messages and take action) and schedules outreach accordingly — a level of timing optimization impossible for human collectors managing hundreds of accounts.

Why This Matters

For CFOs managing working capital: DSO improvement directly converts to free cash flow. A 9-day reduction across a $100M AR portfolio at 5% cost of capital saves $123,000 annually in financing costs — plus the strategic optionality of having $2.5M in additional available cash.

For accounting firms offering AR advisory: Daylit creates a referral and implementation opportunity. Firms that recommend and help implement AI collections for clients capture advisory fees while improving client cash flow — a measurable, attributable value proposition.

For controllers and AR managers: AI collections don't replace your team — they amplify it. Your human collectors become high-judgment specialists handling complex negotiations and dispute resolution, while the AI handles the volume work of chasing routine late payments.

For the collections industry broadly: The traditional outsourced collections model (send accounts to a third-party agency at 25-50% commission) faces disruption. If in-house AI achieves 15% better recovery rates at a fraction of agency commission costs, the outsourced collections industry loses its value proposition.

For technology evaluators: When comparing AI collections platforms, prioritize behavioral modeling depth (does it learn per-customer?), channel flexibility (email-only vs. multi-channel), negotiation capability (can it offer payment plans autonomously?), and ERP integration (does it sync with your accounting system in real-time?).

The key takeaway: Daylit's AI collection agents achieve 9-day DSO reduction and 15% higher recovery rates by personalizing every interaction to individual customer behavior — making one human collector as effective as ten and converting AR management from a labor-intensive cost center into an AI-optimized cash flow engine.