Most intake teams don't need more people. They need a different way to do the first pass.

Today, every submission gets opened by a person who checks what came in, finds what's missing, and writes an email. Then the file waits for an answer. Hiring another person adds capacity, but the work stays the same.

Intake engineering changes the work itself.

What intake engineering is

Intake engineering means turning your intake checklist into requirements an AI intake agent can run on every submission.

An intake engineer decides:

• what a file needs before anyone reviews it;
• which facts matter, and which document each one should come from;
• which facts have to match each other or your systems;
• what to ask the applicant when something is missing.

The agent then does the first pass on every file while the applicant is still in the form. The intake engineer's job is to write and maintain the requirements, not to read every file.

Your underwriters and credit analysts still make the decision. Intake engineering changes what reaches them.

Why this is possible now

Two things changed.

1. AI agents can read the documents people actually send. Scans, phone photos, forwarded broker emails, a schedule pasted into a spreadsheet. Older rules engines needed every field in a structured form. An AI agent can read the messy version, extract the facts, and show the quote and page each one came from.

2. Follow-ups can happen during the submission. Most of the time in intake goes into the round trip: email, wait, reply, reopen, find the next gap. An agent can ask while the applicant has their documents open, and read the answer as soon as it arrives.

Together, that means the first pass no longer needs a person. Deciding what the first pass should check still does.

What an intake engineer builds

There are three layers. In Klarefi they're called Form, Fact, and Verify.

1. Requirements (Form). What a complete file needs for one product, written as an actual list. For example: a signed proposal form, a schedule of sums insured, and a loss history covering the years your guidelines require.

2. Facts (Fact). The values your team decides on, and where each one should come from. For example, the sum insured comes from the schedule rather than the broker's covering email, and the account holder comes from the bank statement rather than the application form.

3. Checks (Verify). What has to match. For example, the sum insured on the proposal against the schedule, the account holder against the company registry, or the salary on the payslip against the employer statement.

When a requirement is missing or a check fails, the agent asks the applicant. When the answer comes back, it reads it and updates the case file. Anything still open stays visible for your reviewer.

Examples by market

MGAs. Requirement: a loss history covering the years your guidelines ask for. Fact: claims per year, cited to the page. Check: the risk address on the proposal matches the schedule. Follow-up: "The loss history you sent covers two years. Can you upload the third?"

Factoring. Requirement: bank statements for the months your onboarding policy lists. Fact: the account holder and closing balances. Check: the account holder matches the company in the registry. Follow-up: "We're missing the statement for June. Can you add it?"

Mortgages. Requirement: payslips from the months your lending criteria set. Fact: gross monthly salary. Check: the salary matches the employer statement. Follow-up: "This payslip is from March. Do you have the one from August?"

The work is the same in all three markets. Only the checklist changes.

Who does it

You probably already have someone who could do this job. Right now they spend their day doing the first pass by hand.

There are three common setups:

1. The underwriting or credit lead who already owns the checklist writes the requirements for their product.
2. An operations analyst owns intake across products and works with each lead to write their requirements.
3. Operations and IT together, when checks need to reach core systems such as a policy administration system or a company registry through connectors.

You don't need a software engineer. You need someone who can explain why your last ten files were sent back.

How to find the right person

Give them three tasks:

1. Review a returned file. Hand them a file your team sent back last month and ask what was missing and how you could have known on the day it arrived.
2. Write one page. Ask them to write the requirements for one product on a single page: the documents, the facts, and the checks.
3. Build and test it. Have them set it up and run five real files through it, including one with a deliberate problem.

Pay attention to how they handle the file with the problem. That's most of the job.

How to start

Pick the product that generates the most follow-up emails. Write its checklist, run a few real files through it, and look at what the agent asked for.

Our guides cover writing facts and verify rules and going from sign-up to your first live intake. To see how the agent handles a submission from start to finish, read how the AI intake agent works.

FAQ

What is AI intake automation? An AI agent does the first pass on an application, insurance submission, or onboarding file. It collects the answers and documents, reads them, checks them against your requirements, and asks for anything missing. Your team reviews the result and makes the decision.

Is intake engineering a new job title? It's a new name for work operations teams already do, mostly from memory. Writing it down is what lets an agent run it.

Does an intake engineer need to code? No. Requirements are written in plain language. Connecting to your own systems may need help from IT once.

Does the agent make the decision? No. The agent prepares the case file. Your underwriters and credit analysts approve, decline, or send it back.