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Yati CRM · AI & LLMs

AI for debt settlement: LLMs on every call, letter and task.

Your Openers and Closers talk; the AI does the paperwork. LLMs listen to every call with a business owner, read funder letters and answer from your own playbooks. Nothing changes until a person approves it, and every approval is audited.

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AI changes approved by a person
100%
Records the AI edits alone
0
Where models run
Your cloud
  1. 01

    Listens and reads

    Live call transcripts, funder letters, your policies and scripts.

  2. 02

    Proposes

    A summary, a callback, a new balance, a recap email, an answer with its source.

  3. 03

    A person decides

    Approve, edit first or reject. Nothing changes until someone does.

  4. 04

    The usual rules apply

    Approved changes pass the same permissions, compliance gate and audit log as anyone's.

What the AI drafts

The paperwork of a settlement program, drafted for approval

Call notes and results

The LLM reads the whole transcript and drafts the summary and the call's result.

Callbacks and promises

Callbacks at the time the person asked for, in their time zone. Promises to pay with a check-in task.

Recap emails and texts

Drafted from the call and sent through the gate. A banned phrase stops the draft.

Letter data entry

Funder letters and notices read by OCR and the LLM, turned into new balances, contacts and deadlines.

Disclosure QA

Every recorded call checked for your required disclosures. Misses go to a manager's queue.

Policy answers

Agents ask in plain English and get answers from your own playbooks, with the source cited.

Live call assist

Help while the caller is still on the line

Each sentence appears a second or two after it's spoken, and the LLM reads it as the call goes.

  • Live transcripts of every Opener and Closer call
  • Rebuttal suggestions picked only from your approved library
  • The caller's mood, sentence by sentence
  • Alerts on banned statements, attorneys, lawsuits and judgments
  • Live English translation when the caller speaks another language
  • A live board for managers: every call, its mood and its alerts

After-call wrap-up

The wrap-up writes itself, and waits for a yes

When the call ends, the LLM reads the whole transcript once and proposes everything that should happen next.

  • A summary saved as the call's notes, and the call's result
  • Callbacks, promises to pay, handoffs and recap emails, ready to approve
  • Document requests, agreements to sign and settlement letters
  • Safe by default: after "don't call me", nothing that reaches out is proposed

Document intelligence

Funder letters and notices, read the moment they arrive

OCR and the LLM classify each letter from an MCA funder as a balance statement, default notice, settlement offer or summons, and turn it into one-click changes on the deal. A summons raises an urgent alert; letters the AI isn't sure about wait for a person.

Knowledge base

Answers from your playbook, with the page they came from

Upload your policies, scripts and playbooks. Agents ask in plain English and get a cited answer. Search runs in your own database, so your documents never leave your environment.

Guardrails

What the AI never does

AI in a regulated business has to be predictable. These limits are part of the design, not settings someone can forget. Everything the AI proposes still passes the compliance gate.

  • Your call center

    Opener and Closer calls the AI listens to

  • OCR

    Scanned funder letters read on arrival

  • Your environment

    Where the language models run

  • Change a record without a person approving it
  • Invent rebuttals or wording outside your approved lists
  • Send anything that skips the compliance gate
  • Propose outreach after someone says "don't call me"
  • Keep card, Social Security or account numbers in transcripts
  • Send your documents outside your own environment

AI governance

AI you can explain to a regulator

Every AI feature is built so you can say what it did, why, and who approved it.

Runs in your environment

Models run inside your own environment. The model is a setting your admins choose, not a hard-coded vendor.

Picks from lists you approve

Rebuttals and alert topics come from libraries your managers write. The AI chooses among them; it doesn't invent wording.

Keeps working without AI

If the AI is off or slow, phrase matching still raises alerts and suggests rebuttals, and calls go on as normal.

Measured, not assumed

Document reading accuracy reported per field, per model and prompt version, from what agents approve, edit and reject.

Sensitive numbers stripped

Card, Social Security and account numbers are removed from transcripts before they are stored.

Every output audited

Suggestions, alerts, summaries and answers are recorded, with who approved what and when.

AI features can be turned off for the whole company in Settings.

FAQ

Questions about AI in Yati CRM

How does Yati CRM use AI in MCA debt settlement?

Large language models listen to Opener and Closer calls, read funder letters and answer questions from your playbooks. They draft call summaries, follow-ups, letter data entry and cited answers, and flag mood, lawsuits and banned statements while the call is live.

Does the AI change records on its own?

No. The AI proposes and a person approves, edits or rejects. Approved changes go through the same permissions, compliance gate and audit log as any change made by your staff.

Which LLM does Yati CRM use?

Models run inside your own environment. The model is a setting your admins choose, not a hard-coded vendor.

Is our client data used outside our environment?

Models run in your own environment, knowledge base search runs in your own database, and sensitive numbers are stripped from transcripts before they are stored.

What happens if the AI is off or slow?

Calls go on as normal. Phrase matching still raises alerts and suggests rebuttals, and every task can be done by hand. AI features can be turned off for the whole company in Settings.

How accurate is the document reading?

Accuracy is measured, not assumed: it is reported per field, per model and prompt version, from what agents approve, edit and reject. Letters the AI is unsure about wait for a person.

Hear the AI on a live call

A walkthrough on demo data: live transcript and alerts, the AI wrap-up waiting for approval, and a funder letter read on arrival.

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