Voter engagement infra for orgs that don't pick sides.

501(c)(3), 501(c)(4), chambers, unions, civic mobilization. The same platform candidates use, with compliance guardrails built in.

The AI reads every send before your members do. Your audit log is exportable to CSV any time your board, your counsel, or the IRS asks for it.

→ Join the front line

10% nonprofit discount applied automatically on c3 / c4 / union / chamber tenants

§02 · USE_CASES

Four org types. One platform. Four rule sets.

▸c3

League of Women Voters, NAACP, voter registration drives

Voter education, registration outreach, GOTV — without candidate endorsement language. Our AI auto-blocks any message that tips into endorsement territory before it ever reaches a member.

▸c4

Emgage, Working Families Party, AFL-CIO state federations

Full issue advocacy and ballot-measure campaigns. Same platform as the c3 tenants, different compliance rules — switched on by a single tenant_type field.

▸chambers

Hispanic Chamber, Black Chamber, Realtor associations

Civic mobilization on policy issues without political endorsement. Use the public voter file to reach member households at home, not just the inbox.

▸unions

SEIU locals, Teamsters, building trades

Member contact plus endorsed-candidate GOTV. Bilingual EN/ES turf packets are standard. Member roster geocodes and dedupes against the public voter file on upload.

§03 · COMPLIANCE

We block what you can't send.

On c3 tenants, every outbound mail piece, text, and email is AI-scanned for candidate-endorsement language before send. If the copy crosses the line, we block it and surface the exact sentence that tripped the filter.

c4 tenants get a softer posture — warnings on express advocacy with the lobbying-percentage implication logged. Chambers and unions get their own gates. Same product, different rules per tenant_type.

The audit log records every flag, every override, every send, and the reasoning. Retention defaults to 7 years.

“Vote for Smith for mayor”

“Elect Maria!”

“Sign up for our voter ed event Saturday at the library.”

Above: examples of what the c3 compliance check blocks, allows.

§04 · PRICING

Two tiers. 10% off, always.

Discount applied automatically once your 501(c) determination letter is on file. 14-day free trial, no credit card up front.

Starter

Small chapters, single-county chambers, local unions.

$89/ mo

List $99 · 10% nonprofit discount applied

▸1 staff seat · 25 volunteers
▸10 active turfs · up to 5,000 contacts
▸Compliance check on every send
▸Audit log + CSV export
▸Email support (48h)

→ Start 14-day trial

Most chosen

Pro

State affiliates, larger locals, mid-size advocacy orgs.

$224/ mo

List $249 · 10% nonprofit discount applied

▸5 staff seats · 100 volunteers
▸50 active turfs · up to 50,000 contacts
▸Everything in Starter
▸Membership file integration
▸Slack support channel

→ Start 14-day trial

National federation? Multi-state roll-up? Email us for custom seat + chapter pricing.

§05 · QUESTIONS

Common questions.

Will using FrontlineHQ jeopardize our c3 status?

No — nonpartisan voter education, registration, and GOTV are explicitly permitted activities for 501(c)(3) organizations under IRS rules. We give you tools to run those programs while the AI compliance layer screens every send for candidate-endorsement language. Your audit log is exportable to CSV any time your board, your counsel, or the IRS asks for it.

What about the Johnson Amendment?

The Johnson Amendment bars 501(c)(3)s from intervening in any political campaign on behalf of (or in opposition to) any candidate. The AI compliance layer is calibrated against that line. If your copy names a candidate in a way that reads as support or opposition, we block the send and surface the line that tripped the filter. You see the flag before your members do.

Can we add multiple chapters or locals?

Yes. Each chapter or local gets its own tenant with its own roster, its own staff seats, and its own audit log. A national parent can roll up reporting across all child tenants. SEIU and AFT state councils already run this way on the platform.

How does the AI know what's endorsement?

Two layers. First, a fast classifier trained on IRS guidance, FEC advisory opinions, and a manually-reviewed corpus of c3 messaging — pass/block in under 100ms. Second, an LLM verifier on edge cases that walks through the reasoning and logs it to the audit trail. Overrides are allowed with a justification; we tune the model on overrides every month.