Is policyholder and claims data confidential?

Claims and underwriting content is never used to train any AI model. A pseudonymization layer replaces policyholder and personal identifiers with reversible tokens before the models see them, restoring them only in your result — automated detection reduces what reaches a provider, though it cannot guarantee elimination. Each deliberation leaves a timestamped record you can retrieve by ID. Retention periods and Zero Data Retention mode are set out in our Privacy Policy.

Does it replace the underwriter or the claims handler?

No. It argues the exposure from five directions and keeps the reading that says the risk is mispriced or the claim is covered, so the decision-maker has seen the counter-case. Pilot5.ai does not provide legal or actuarial advice.

What does it cost on a single risk or claim?

The estimate is shown before the deliberation runs, reserved at launch, settled on completion, with any excess refunded. Current rates are on the pricing page.

Who it's for / Insurers & Reinsurance Teams

Pilot5.ai for Who?

Insurers & Reinsurance Teams

Every policy you write is a position on the future.
Five independent AI models argue the risk before you price it.

For the underwriter reading the submission. For the pricing actuary who has to defend the number. For the reinsurance team carrying the accumulation long after the quote went out.

Risk assessments grounded in regulatory authority and verifiable data. Decisions that survive the underwriting committee and the regulator. Absolute confidentiality on insured data. Speed at quote pace that does not compromise the file, and a record of how each conclusion was reached, ready for the audit.

A single AI gives one confident answer, in the same tone whether it is grounded or invented — and a model trained to agree with you validates your risk assessment instead of testing it. On a risk that sits on your book for years, that is not a research assistant. That is a risk of its own.

Step 1

The companion builds the brief with you.

The submission and the exposure it brings. The accumulation it adds to the book. The wording and where it will be tested. Your appetite, your treaty, and the committee that has to sign the terms.

Step 2

Research and retrieval fire in parallel.

NAIC — US insurance regulation and model conduct standards
SEC — carrier and counterparty filings and disclosure
Federal Register · eCFR — US regulatory text
EIOPA — EU insurance supervision, solvency and conduct standards
EUR-Lex — EU insurance legislation for cross-border programs

Every claim carries a provenance tag. [SOURCED] means traced to a verified reference. [INFERRED] means analytical inference — flagged automatically. Claims that cannot be traced are labelled as inference, never presented as fact.

Step 3

Five frontier AI perspectives deliberate, each through a calibrated mandate.

The Architect maps the risk as written — exposure, accumulation, retention, and where the wording actually carries the loss.
The Strategist reads the market, the cycle and the reinsurance capacity the account will meet at renewal.
The Engineer works the pricing assumptions, the loss data and the sensitivity of the base case.
The Counsel surfaces coverage disputes, jurisdiction and what a regulator would question in the file.
The Contrarian sole mandate: argue this account produces the loss, and name the correlation this book is not pricing.

Five complete analyses. Five distinct angles. Not five versions of the same answer. Then they challenge each other, anonymously. Then they converge — and when one perspective refuses to, that dissent is preserved rather than averaged away.

Output:GO / PIVOT / NO GO / INSUFFICIENT BASIS · Confidence score · Decision matrix · Minority Report · Testable predictions.

Questions Pilot5.ai helps with

What does this submission expose us to that the broker's summary does not show?
Where does this account stack onto accumulation we already carry?
Which words in this wording will be fought over when the claim comes in?
What would the underwriting committee push back on first, and how do we answer it?
What is the strongest argument against binding these terms at this price?

Common questions

Is policyholder and claims data confidential?: Claims and underwriting content is never used to train any AI model. A pseudonymization layer replaces policyholder and personal identifiers with reversible tokens before the models see them, restoring them only in your result — automated detection reduces what reaches a provider, though it cannot guarantee elimination. Each deliberation leaves a timestamped record you can retrieve by ID. Retention periods and Zero Data Retention mode are set out in our Privacy Policy.
Does it replace the underwriter or the claims handler?: No. It argues the exposure from five directions and keeps the reading that says the risk is mispriced or the claim is covered, so the decision-maker has seen the counter-case. Pilot5.ai does not provide legal or actuarial advice.
What does it cost on a single risk or claim?: The estimate is shown before the deliberation runs, reserved at launch, settled on completion, with any excess refunded. Current rates are on the pricing page.

Do not take our word for it. Run your own deliberation on a question you know well.

Read how five independent models handle it, then decide what it is worth.

Pilot5 delivers analysis. You deliver judgment.

Disagree to decide.

Start an Underwriting Deliberation

Read: AI decisions need an audit trail →·Read: the verified sources library →·Read: run it from your own AI →

Pilot5.ai produces AI-assisted analysis and is not a substitute for professional actuarial, legal, or regulatory advice. Outputs are research and decision-support only, and must be reviewed by a qualified professional before any underwriting, pricing or claims decision.