Claims teardown · 2026
Grow your claims operation in the AI era
AI agents that run FNOL intake, triage and screening. Faster cycle times, without adding adjusters.
Built around your lines of business and your floor's rules — not a generic model.sudoboat.com · 01/17
The old way · 02/17
Handling claims used to mean headcount.
01
Keying loss details
a person's job
02
Chasing what's missing
a person's job
03
Sorting files by hand
a person's job
The problemFaster cycle times meant a bigger back office — only the largest carriers could afford it.
The shift · 03/17
Now the same team handles the surge.
Before
The floor does the mechanical front — re-keying · completeness chasing · routinghours to days
Judgment
With agents
Agents run the front of the funnelminutes
Judgment
Capacity for the surge
.
the floor's day, with agents
more claims, same headcount
The payoffYour adjusters spend their time on severity, coverage and reserves. Productivity is the growth lever now, not headcount.
The asymmetry · 04/17
The expensive resource never touches the front of the funnel
Mechanical, no judgment
Keying loss details, chasing completeness, hand-routing. Most of the FNOL-to-first-touch window goes here — and both the time-to-first-contact and cycle-time clocks run the whole time.
The adjuster
Severity · coverage · reserve. The judgment you actually hired for.
Why it mattersClaims handling is your largest workflow, and adjuster judgment is the scarce resource in it. Every hour in that gap is mechanical work standing between a reported loss and the person you hired to work it.
The premise · 05/17
From a manual FNOL desk to an AI-native one
Manual FNOL desk · today
- Skilled staff re-type loss details out of PDFs, ACORD forms and emails by hand
- Incomplete notices stall until a human notices and chases the claimant — days, not minutes
- Someone reads each file, judges severity and line of business, and assigns by hand
- Claims worked in arrival order — the file that should jump the line waits behind routine ones
- The phone intake channel runs on a separate, unmeasured track
AI-native FNOL desk · with agents
- An extraction agent reads the form and writes loss details straight into the claims system
- Completeness is checked at intake; the gap-chase fires itself and closes same-day
- A triage agent infers severity and LOB and routes on a rule set you own
- Priority follows the claim, not the queue — the urgent file surfaces first
- Phone and document intake land in one measured pipeline; adjusters touch only judgment
The premiseEvery job still happens. The only thing that changes is who does the mechanical front of the funnel — and where your adjusters spend their judgment.
Plain definition · 06/17
What we mean by an "agent"
Not a chatbot, not a rigid macro. It runs a loop on its own: reads what arrived, decides the move against your rules, acts, and gets sharper with every outcome.
① Perceive
An FNOL lands
PDF, ACORD form, email or phone-triage capture
→
② Reason
Reads the file
extracts loss details, checks completeness, infers severity & LOB
→
③ Act
Does the work
keys to the system, fires the gap-chase, routes to the right desk
→
④ Learn
Gets sharper
which extractions and routes hold up feeds the next
The difference from a ruleA fixed workflow follows one script and stops dead when a notice doesn't match it. An agent reads the case and handles the exception — which is most of real intake.
Control · 07/17
Agents key, validate and route. Your adjusters decide.
a
Human-in-the-loop by design
Low-confidence extractions and edge documents route to a review queue. The agent does the typing; your staff confirm the calls worth confirming.
b
Routing on rules you own
Severity and LOB assignment run on a rule set you control and can audit — not a vendor's black box you can't see into.
c
We name what stays manual
The coverage read, the reserve call, the genuinely ambiguous claim stay with your adjusters. We'll tell you where automation won't pay off.
The principleAutomation here doesn't mean handing over the coverage call. It means moving the keystrokes and the sorting off your floor so judgment lands where it's worth the most.
Why a tailored build · 08/17
Your lines of business are the reason off-the-shelf breaks
a
Built to your forms & LOBs
Extraction, completeness rules and routing — shaped to your ACORD variants, your lines and your authority levels, not a generic template.
b
Plugs into your stack
Reads your document and phone intake, writes into the claims system your floor already uses. No rip-and-replace.
c
Hardened, not just a POC
Production reliability is our craft — the agent holds up across real document volume and messy edge cases, where most pilots quietly fall over.
The problem with packagedA packaged "intake tool" is trained on someone else's forms and someone else's routing. It demos well, then mis-keys your ACORD variants. That fit is the difference between a demo and recovered cycle time.
The leak map · 09/17
Where a claim loses hours before an adjuster sees it
1Re-keying from PDFsskilled staff re-type loss details out of PDFs, ACORDs and emails — slow, error-prone
2Chasing what's missing — days idlea partial notice stalls until a human notices and chases; the reply comes back in days
3Sorting files by handskilled time on a sorting task — the misroute-bounce-requeue tax
4Priority by arrivalthe queue sets priority, not the claim — urgent files wait behind routine ones
5The phone channelcaptured by hand, re-entered, rarely measured
6Adjuster's deskhandled twice before worked once
mechanical leaks — hours to days
judgment
The problemThe five leaks compound into cycle time before adjudication begins — and STP rate is lowest right here, precisely because none of it requires judgment.
Agent 01 of 03 · the beachhead · 10/17
FNOL Intake & Triage
The problem
The front of the funnel is all keystrokes and sorting. Staff re-type loss details from PDFs, chase incomplete notices for days, then hand-sort each file by severity and LOB — mechanical work that stands between a reported loss and the adjuster you hired to work it.
The agent
Reads the ACORD form, PDF or emailed FNOL, writes loss details straight into the claims system, runs a completeness check at intake, fires the gap-chase itself, and routes by severity and LOB. Tuned to your forms, lines and authority levels; low-confidence extractions go to a human review queue.
The flow
① Trigger
FNOL lands
document or phone-triage capture
→
② Agent · extract
Keyed + checked
written to system, completeness validated
→
③ Agent · route
Triaged by claim
severity & LOB, on rules you own
→
④ Human, if needed
Edge review
low-confidence cases confirmed
→
⑤ Output
Right desk, ready
adjuster opens a clean file
The payoffRe-key gone — not moved to a cheaper desk · By claim, not arrival — the multi-day chase becomes same-day · Adjuster opens clean — TTFC and STP both move
Agent 02 of 03 · consistent reads · 11/17
Adjudication Assist
The problem
Before an adjuster can call coverage, they assemble the picture by hand — pulling policy language, prior claims and the loss facts, then reconciling them. It's slow, and two adjusters can read the same file two ways.
The agent
For each claim, surfaces the policy provisions in force, the relevant prior-claim history, and a drafted coverage position with the facts that support and contradict it — for the adjuster's review. Tuned to your policy forms and authority levels; the decision stays the adjuster's.
The flow
① Trigger
File ready to work
intake complete, routed
→
② Agent · assemble
Policy + history
provisions in force, prior claims
→
③ Agent · draft
Coverage position
support and contradiction surfaced
→
④ Human
Adjuster decides
the call stays yours
The payoffPre-read — time spent deciding, not gathering · Consistent — every file framed the same way · Judgment stays human — coverage and reserve remain the adjuster's call
Agent 03 of 03 · before payout · 12/17
Fraud Screening
The problem
Fraud screening is uneven and late. Suspicious claims slip through when the floor is busy, SIU referral runs on gut feel, and by the time anyone looks closely the payout is often already out the door.
The agent
Scores every claim against fraud indicators and cross-claim patterns at intake, and flags the risky ones for SIU before payout — clearing the clean ones so they don't wait. Tuned to your fraud signals and lines; SIU works the flagged queue.
The flow
① Trigger
Claim at intake
before it moves to pay
→
② Agent · score
Indicators + patterns
cross-claim signals checked
→
③ Condition
Risk gate
clear, flag, or hold
→
④ Output
SIU or clear
flagged before payout
The payoffBefore payout — caught at intake, not after the money left · Every claim screened — not only when the floor has time · SIU works the queue — flagged files, not hunting
The honest read · 13/17
Re-keying, completeness checks, routing, fraud scoring, file assembly — that's the mechanical majority, and where these agents earn their keep. The coverage read, the severity and reserve calls, the genuinely ambiguous claim, and the SIU investigation itself stay with your people.
The leaks aren't where your adjusters are weak; they're where the workflow makes skilled people do unskilled work before any judgment is applied.
Worth pressure-testingWhich parts are mechanical enough to automate now versus what stays with your adjusters — that's the exact thing worth testing against your real intake mix.
What "good" looks like · 14/17
The three numbers your floor already watches
Not invented percentages — the KPIs claims leaders measure.
↑
straight-through-processing rate
0
new adjusters hired to get there
The payoffClosing the front-of-funnel leaks moves all three in the same direction, on your own claim mix.
Size your own drag · 15/17
The no-judgment hours, in three of your own numbers
A FNOLs / mo × B mechanical minutes per claim before first adjuster touch × C fully-loaded cost / minute = spend on work that needs no judgment
Worked example: 4,000 FNOLs/mo × 18 mechanical min each ≈ 1,200 staff-hours/mo on keying, chasing and routing — before an adjuster opens a single file. That's the pile the agents take first; your adjusters keep the judgment.
Rule of thumbIf A × B × C is larger than the fully-loaded cost of the people doing that keying and routing by hand, the manual front-of-funnel is already the more expensive option.
Who we are · 16/17
The credibility rides on the mechanics
The Sudoboat team has shipped and hardened production AI systems for HCLTech, PayPal, IKEA, Qoruz and others. On claims we act as an extended, AI-native domain team that builds the system doing this work — intake, completeness validation, routing and screening — around your forms and lines, and runs it at production reliability. We don't have a claims case study to wave at you, and we won't invent one.
How we'd startOn a call we'll walk your actual intake flow, leak by leak, and tell you what's mechanical enough to automate now and what stays with your adjusters.
The next step · 17/17
Watch an agent key and route a real FNOL in 20 minutes
Reply to the email this came from and we'll show you a working FNOL Intake agent run on a real, de-identified first notice — extract the loss details, validate completeness, route it — then map which intake leak is worth closing first for your lines of business. No deck of outcomes, no obligation.
Reply to book the 20 minutes →
Keep this teardown either way — it's yours whether or not we ever talk.sudoboat.com
