saascode
customer support & success·run 155 · Jun 2026

Attriton

A workforce-change evidence workspace that links AI deployment, affected functions, employee decisions, notice requirements, retraining or redeployment offers, reviews, filings, receipts, and corrections by jurisdiction.

Genesis score6.38/10
Make Attriton real.0/500
500 more votes and Attriton is authorized for build.
0%500 to authorize
Backing is the vote. When an idea crosses 500, we pull it into the build pipeline and ship it for real — the votes decide what gets built next, not an editor.
The opportunity
1Confirmed enacted state trigger
0Confirmed direct competitors
The case

When a company deploys support automation and changes roles or staffing, legal and operational teams need evidence of what changed, why, who was affected, what alternatives were considered, and which notices or filings were required. Research found no purpose-built displacement-disclosure product, but corrected the invention's regulatory premise: Connecticut enacted an AI-related WARN disclosure effective October 1, 2026; New York has an active employer checkbox; California's order directs recommendations rather than imposing immediate employer duties; and the cited federal proposal is a discussion draft, not law. Attriton organizes evidence and drafts bounded packets for qualified review. It never decides displacement causality, selects employees, files autonomously, or certifies compliance.

Who pays — and why

The HR, employment legal, compliance, workforce strategy, customer operations, or risk leader overseeing AI-related organizational change.

Market signalValidate below $10K-$55K/yr enterprise referencesobserved market reference, not fixed product pricing
What it unlocks
A versioned change event connecting deployed capability, business function, work redesign, staffing proposal, evidence, decision authority, affected groups, and effective date.
A jurisdiction queue that distinguishes enacted requirement, active form field, executive direction, proposed bill, effective date, applicability candidate, and qualified finding.
Reviewed notice and filing packets with exact source facts, approvals, delivery, authority receipt, correction, and outcome.
How Genesis scored it
6.38across seven criteria
tension 8temporal 8blindspot 5buyer 5leverage 7convergence 5why-not 6
8
Productive tension

The product must document AI contribution without reducing complex workforce decisions to automated causal labels.

8
Temporal window

An October 2026 effective date, active checkbox, and visible pipeline create a strong timing window.

5
Convergence

Two cross-references and two inbound connections provide moderate convergence.

Why it scored well

The category gap is confirmed, live and future triggers are specific, and the evidence-plus-jurisdiction mechanism addresses a high-stakes workflow.

What's holding it back

The buyer and budget are underspecified, causality and applicability require professional review, two interfaces were unverified, regulatory status is mixed, and no structural incumbent barrier is evidenced.

Signals detected3 sources crossed
SignalRegulatory research

SignalRegulatory research

SignalLegislative research

Direction briefattriton.md
attriton.md
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Discussion

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