Aelanaaelana.ai
About Aelana

The intelligence layer that sits atop renewal cycles and RFPs.

Aelana helps a benefits broker ingest messy renewal inputs, normalize them into a common analytical model, simulate plan and funding scenarios, and produce an employer-ready recommendation with a defensible audit trail. The job is renewal decisions that are more accurate, more explainable, and more defensible.

The problem

The renewal is a 40-hour grind, done in spreadsheets.

Every renewal arrives as fragmented inputs — carrier letters as PDFs, census files, claims experience, stop-loss terms, quote files — in a dozen formats. Brokers retype them into spreadsheets, hand-build the stay-vs-rebid-vs-level-funded comparison, and assemble an employer deck the plan fiduciary can stand behind.

The transaction systems brokers already own — the AMS, the benefits-admin platform, the quoting tools — don't help with the part that actually matters: turning all of that into a consistent, defensible recommendation. There's no system for the decision.

The positioning

System of record for transactions is someone else. System of record for decisions is us.

What Aelana is not
  • — Where benefits are administered
  • — Where quotes are merely collected
  • — Where employees ask benefits questions
  • — A carrier marketplace
What Aelana is
  • — Where a broker turns fragmented data into a recommendation
  • — Where cost drivers become legible
  • — Where scenarios are modeled consistently
  • — Where employer recommendations become defensible
The workflow

One repeatable workflow, from intake to closed loop.

Phase A

Intake & case setup

Pull employer context, current plan data, contribution history, claims summaries, stop-loss terms, and quote files into one place. A completeness score and missing-data alerts show what's still outstanding.

Phase B

Normalization & diagnosis

Convert PDFs, spreadsheets, SBCs, and census files into a canonical model — then surface the cost drivers: dependent mix, geography, Rx and specialty-drug trend, out-of-network usage, plan-design sensitivity.

Phase C

Market & scenario modeling

Compare renew-as-is, contribution changes, rebids, level-funded, and self-funded — modeled on employer cost, employee cost, expected total cost of care, risk transfer, and implementation friction. Not just quoted premiums.

Phase D

Internal account-team review

Track comments, record assumption changes, support approvals, and preserve a decision history the whole team can see.

Phase E

Employer presentation

Produce a recommendation package that explains what changed, why it's recommended, the alternatives considered, the assumptions, the uncertainties, and the implementation steps.

Phase F

Handoff & closed-loop learning

Push decision metadata back into the broker's workflow, create implementation tasks, and compare post-enrollment outcomes against the assumptions that were made.

See the workflow on a real case.

Walk through the guided product preview, or have us demo it on renewals like yours.