LAAGAM's AI operating system.

What it needs to know.

Customer conversations, payment promises and the history linking advances to invoices.

The job for the agent.

Use the conversation to explain the balance, check the bank evidence and prepare a follow-up for human review.

Where it checks the facts.

Compare the reviewed balance with documents and bank evidence. A conversation alone cannot confirm payment.

What comes out.

Reviewed balances, unresolved payments and a shared collection history across the team's views.

Unclear payments stay unassigned. Promises are not treated as cash. The team reviews follow-up text and sends it manually.

What it needs to know.

The conversation, the company's reviewed policy, writing guidance and the order linked to this case.

The job for the agent.

Read the permitted conversation, matched order and policy, then prepare a private reply with missing evidence flagged.

Where it checks the facts.

Check the conversation and policy versions again before presenting the draft. The support team reviews and sends.

What comes out.

A private reply draft with source checks and a review queue.

The support team reviews and sends. A draft cannot authorise a refund, promise delivery or resolve the case on its own.

What it needs to know.

The job and application, reviewed offer, document checks and each person's onboarding responsibilities.

The job for the agent.

Bring the application, offer and document reviews together, then show which approved onboarding tasks still need an owner or evidence.

Where it checks the facts.

Check the actual document review, activation approval, task records and first access. A signed offer alone is not completed onboarding.

What comes out.

A hiring history and an onboarding checklist with owners, evidence and access checks.

People select, review signed documents and approve activation. This is not an automatic hiring decision, signature service or payroll setup.

What it needs to know.

What counts as available cash, which entries are manual and when balances were recorded.

The job for the agent.

Bring the balances together, separate recoverable amounts and flag entries that need a person to check them.

Where it checks the facts.

Check account source status and the dates of saved positions before comparing them.

What comes out.

A dated cash position, account-level source status and changes between recorded days.

Missing sources stay visible. People review manual entries and unusual changes; the tool does not transfer money or forecast cash flow.

What it needs to know.

Launch dates, time allowed for returns and the difference between return requests and confirmed refunds.

The job for the agent.

Compare products, refunds and return reasons, showing how long each group of orders has had to be returned.

Where it checks the facts.

Check shipped items, confirmed refunds, missing reasons and time since launch. Do not predict the final return rate.

What comes out.

Product and cohort comparisons, linked return reasons and visible coverage gaps.

A return request is not a refund. The analysis does not change purchases, issue refunds or predict a final return rate.