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Advisor operating system

The operating system for retirement plan advisors.

Find plans in public filings. Benchmark fees against real peer data. Model what a better plan design is worth. Run quarterly committee prep. One record per plan — and every number on it traced back to where it came from.

Deterministic enginesProvenance on every fieldAppend-only audit trailHuman-approved AI

Advice you cannot source is advice you cannot defend.

Retirement plan advisors are asked to justify recommendations years after they make them — to a committee, to a plan sponsor, sometimes to a regulator. RetireForge is built so that the justification is a byproduct of the work rather than an archaeology project.

Deterministic by design

Regulated math — fees, allocations, nondiscrimination testing, benchmarks — runs in versioned engines, reproducible from its inputs, the engine version, and the IRS limit set. The language model never computes a number.

Provenance on every field

Each figure on a plan record carries where it came from, how fresh it is, and how confident we are. When two sources disagree, the conflict is recorded beside the winning value — never quietly resolved away.

An audit trail you can hand to a committee

Append-only events on every regulated action, visible in the interface rather than buried in a log file. Automation records what triggered it, which rule version ran, what it produced, and who approved it.

Four stages, one plan record

Each stage captures structured data the next one consumes. Nothing is re-keyed, and nothing is lost between the pitch and the annual review.

01

Find

Search the public Form 5500 universe for plans that fit your practice, and pull the ones you want onto your book.

02

Diagnose

Benchmark the incumbent's fees against peer filings and model what a better plan design would do for the owners.

03

Win

Turn the diagnosis into a branded proposal, run a structured RFP, and track the conversion to the day it goes live.

04

Serve

Run quarterly committee prep, keep the fiduciary file complete, and let automation propose the follow-through.

Fee benchmarking

What plans like this one actually pay

Every 401(k) and profit-sharing plan files its costs with the Department of Labor. Here is the real 2023 distribution. Drag the marker to any all-in fee and see where it falls against its peers.

Small plans — $1M to $10M in assets

1.35%135 bps
50thpercentileCompetitive

A plan this size paying 1.35% all-in costs more than 50% of the 247,295 comparable plans that filed in 2023.

EFASTU.S. Department of Labor Form 5500 filings, plan year 2023. All-in cost is disclosed Schedule C/H fees plus fund expense as a share of assets; plans reporting no fee data are excluded, and bars are clipped where most plans cluster at the size-band floor. Illustrative of peer ranges — not a quote or an actuarial certification.

Start from what the filings already say

Every qualified plan in the country files a Form 5500. RetireForge turns that public record into a prospecting surface and a diagnostic, so the first conversation starts with evidence instead of a questionnaire.

  • Prospecting

    Faceted search across public Form 5500 filings by plan size, assets, participants, and provider. The incumbent recordkeeper, the insurance carrier, and the pre-approved document sponsor resolve as three separate, confidence-tiered signals — a plan can carry all three, and they are never conflated. Adding a plan puts it on your book as a prospect and writes an audit event.

  • Plan diagnostic

    A branded benchmark report generated straight from a plan's own filings — fees, participation, and design, set against comparable plans. Deterministic: the same filing and the same engine version produce the same report, every time.

  • Fee benchmarking

    The incumbent against provider quotes, side by side, broken out per participant and in basis points across recordkeeping, third-party administration, investment expense, revenue sharing, advisory, and custody. Ten-year cost projection, fee leakage, revenue-share exposure, and peer-percentile placement mined from Schedule C and Schedule H filings.

Show the owner what a better plan is worth

Scenario modeling, proposal generation, and a structured RFP — sharing one census, one fee picture, and one record of what the committee actually saw when it decided.

  • Plan design illustrations

    Stack scenarios over a single census: safe harbor, then profit sharing, then cash balance. Coverage, ADP/ACP, top-heavy, gateway, and cross-testing all run in a versioned actuarial engine. Output is illustrative — offered for discussion, not as an actuarial certification.

  • Proposals

    Compose the prospect's facts, the fee comparison, and the illustration into one branded proposal document. White-label ready, and every figure in it passes through from the engine that computed it.

  • RFP and conversion

    Structured scoring criteria, an invite-only portal where providers respond, and a side-by-side comparison. Deciding freezes an immutable snapshot of exactly what the committee compared. Conversion milestones — from file to blackout to live — flag slippage before it becomes a problem.

The quarterly meeting, prepared in advance

Committee prep is the workflow the year turns on. RetireForge organizes the platform around it, so the file is complete before anyone asks to see it.

  • Committee and meetings

    Roster, agenda, minutes, action items, and acknowledgments as one cycle. A single view assembles what the next meeting needs: who is on the committee, what was decided last time, and which action items are overdue. Minutes export for the file.

  • Fiduciary vault

    Versioned documents, each with a content hash. A new version is a new record — nothing is ever overwritten. Share externally with a PIN and an expiry, and every access, allowed or denied, is logged.

  • Playbooks

    Declarative automation: when this event fires and these conditions hold, propose these actions. Draft the notice, flag the fund, open the task. Every action lands as a proposal a human approves — nothing executes on its own.

  • Data reconciliation

    See which fields you actually hold on a plan, which source each came from, and how stale it is. Feeds that drift from their expected layout are quarantined whole rather than half-parsed, and disagreements between sources surface as conflicts to resolve.

For broker-dealers and aggregators

Oversight across every firm in the network

A parent organization sees its whole subtree without leaving the platform, and without a spreadsheet arriving by email every quarter.

  • Plans by lifecycle stage, sponsors, and advisors by role — rolled up across every child firm and drillable down to one.
  • Recent scenario and proposal activity per firm, so you can see which practices are actually working the tools.
  • Subtree visibility is enforced by row-level security in the database itself, not by a filter in application code that someone can forget to apply.

For pooled plan providers

Run a PEP without losing control of the disclosure

Three distribution models, one fee engine, and a hard rule that a fee can never drift out of sync with what has been disclosed to the plan sponsor.

  • Open PEPs use a provider-maintained template that locks completely once a plan adopts it.
  • Firm-exclusive PEPs let the advisor fee change within a ceiling the broker-dealer sets — but the change routes through your approval queue rather than applying itself.
  • Advisor-owned PEPs cap the advisor fee at the plan owner's limit and apply changes directly, with a switchable fee-disclosure presentation.
  • Sponsor identity stays masked to the provider until the plan is won.

The model drafts. The engines decide. You approve.

Language models are good at prose and bad at arithmetic, and a retirement plan is arithmetic. RetireForge puts a wall between the two, and enforces it in code rather than in policy.

  • Numbers are verified, not trusted

    Every regulated number comes from a deterministic engine. Before an AI-written draft is saved, each figure in its prose is verified against the structured data the model was handed. A number that cannot be traced back fails closed — the draft is rejected, not flagged.

  • Citations are verified, not generated

    References to ERISA and the Internal Revenue Code are checked against a real corpus of statute and regulation before a draft is persisted. A citation the model invented never reaches your file.

  • Every write is a proposal

    Narrating a prospect, drafting a meeting agenda, explaining a conflict between two data sources — each lands as a proposal, with the grounded data attached for you to inspect. Nothing is written to your book until a person approves it.

  • Ask in plain language

    Press ⌘K and ask for what you need. Natural language routes to the right surface against a fixed catalog of destinations, so the assistant can navigate the product but cannot invent a place to send you.

Built for the file, not the demo

You are a fiduciary, and the platform you keep the evidence in is part of that responsibility.

  • Multi-tenant isolation enforced in Postgres with row-level security, with an isolation test on every tenant-scoped table that runs on every build.
  • Sensitive census fields — Social Security number, date of birth, compensation — encrypted at the field level, separately from the database at rest.
  • Append-only audit events on every regulated action, surfaced as a product screen rather than an internal log.
  • Every external dependency — custodian, payroll, filing engine, data feed — sits behind an adapter. Replacing a partner is configuration, not re-architecture.
  • Built against the SOC 2 criteria from the first commit, with controls that emit their own evidence automatically. The independent audit is not yet complete, and we will not claim otherwise.

See it against your own book

We will walk through prospecting, a fee benchmark, and a cash balance illustration on plans you actually care about.

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