EchoCheck is a controlled pilot-ready MVP and technical preview for DV/IPV-informed LLM safety evaluation. It runs the same scenario through five prompt configurations, compares model responses against a structured, multi-dimensional safety rubric, and produces reviewable outputs for research, training, procurement review, and buyer diligence. Public launch, licensing, or production use should be conditioned on fresh verification of deployment, billing, exports, privacy controls, accessibility, and live environment behavior.
Controlled pilot-ready LLM safety evaluation for DV/IPV and survivor-serving AI use cases
Actual EchoCheck app screenshot. Public-safe preview with no private evaluation data shown.Public-safe preview
Asset type
DV/IPV-informed LLM safety evaluation MVP
MVP for comparative LLM safety evaluation, DV/IPV-informed rubric scoring, exports, and controlled buyer review.
Demo posture
Demo-ready for controlled buyer
Demo-ready for controlled buyer review after environment verification. External diligence should re-run build, tests, data-access rules parity, environment checks, billing test flow, export verification, privacy controls, accessibility checks, and live behavior checks before public launch claims.
Best fit
AI governance platforms, trust and safety teams, nonprofit technology consultants, and responsible AI acquirers evaluating high-vulnerability AI deployments.
DV and advocacy organizations evaluating AI tools, Nonprofit technology officers
Public-safe indicators buyers can use before requesting deeper materials.
Working MVP with automated scoring workflow5-panel comparative evaluation workflowStructured DV/IPV-informed rubricGoverned backend scoring gatewayDefault-deny data-access posture
Product thesis
Why this asset exists
AI tools are being introduced into advocacy, hotline, case-management, legal, and survivor-support workflows before many organizations have the capacity to evaluate risk. In DV/IPV contexts, unsafe AI advice can increase danger through victim-blaming, poor privacy guidance, missed lethality indicators, or coercive-control blind spots. EchoCheck gives organizations a structured way to test AI behavior before adoption, procurement, or deployment.
01
Buyer need
Organizations are testing and adopting AI tools before they have a practical way to compare how those tools respond to DV/IPV and survivor-serving scenarios. Generic model benchmarks do not reliably show whether responses account for coercive control, lethality indicators, privacy risks, cultural responsiveness, or the risk that AI outputs could increase harm.
Organizations are adopting AI tools before they can evaluate survivor-safety risk
Generic benchmarks do not measure trauma-informed language, coercive control, lethality awareness, or privacy preservation
AI outputs can sound helpful while introducing escalation, victim-blaming, or digital-safety risk
Funders and boards need a repeatable way to compare AI safety across tools and versions
Procurement teams need evidence that AI tools have been tested against domain-specific high-risk scenarios
02
Product response
EchoCheck provides a structured evaluation workflow for comparing AI responses across five prompt configurations: baseline, basic safety, SME-informed, adversarial, and custom. It uses an automated scoring workflow and a structured DV/IPV-informed rubric to help reviewers identify response strengths, gaps, and potential risks. It should be presented as controlled pilot-ready and buyer-diligence ready, not as production-ready or safety-certified.
Runs five structured evaluation panels against AI outputs
Scores responses against a structured DV/IPV safety rubric
Routes scoring through a governed backend gateway with quota and model governance
Supports tiered access, Pro samples, billing checkout paths, and exportable reports
Includes optional basic redaction for common identifiers in export workflows
Provides a buyer handoff package with architecture, testing, deployment, privacy, security, and commercial materials
Capabilities
What buyers evaluate first
These are the product behaviors, workflows, and evidence points a buyer can scan before requesting deeper materials.
5-panel evaluation
Compare baseline, safety, SME-informed, adversarial, and custom responses.
1
12-dimensional rubric
Scores DV/IPV safety across DV/IPV-informed survivor-centered dimensions.
2
Governed scoring gateway
Model access runs through a governed backend gateway with quotas and abuse-protection paths requiring deployment verification.
3
Buyer handoff package
Audit, deployment, billing, privacy, security, and operations docs are present.
4
Use cases
Where this asset fits
AI procurement review
A nonprofit compares candidate AI tools against DV/IPV safety dimensions before adoption or renewal.
Model update regression check
A trust and safety team reruns evaluations after model, prompt, or product changes to identify safety drift.
Funder portfolio oversight
A foundation uses standardized evaluation reports to assess AI safety practices across grantees or funded tools.
Advocacy-sector research
Researchers test how different AI systems respond to survivor-centered, adversarial, and SME-informed scenarios.
Commercial safety add-on
An AI governance platform licenses or acquires the rubric, gateway pattern, and evaluation workflow for a vertical safety product.
Review package
What transfers, what stays gated, and what needs verification.
The public brief gives buyers a safe first pass. Deeper implementation and operational materials stay controlled by fit review.
Documentation
Public overview available. Detailed documentation is gated for controlled review.
Review by request
Testing / QA
QA evidence is available in controlled review and should be freshly verified before buyer reliance.
Controlled review
Transfer boundary
Transfer scope is reviewed privately during app-specific diligence.
This section shows only public-safe evidence language. Deeper technical, security, billing, operational, transfer, and implementation materials stay gated.
Public overview
Available
Public pages provide buyer-centered positioning, fit, use cases, and a controlled next step without implementation details.
Private walkthrough
By request
A private walkthrough can be requested for qualified review. No public demo access is implied.
QA evidence
Controlled review
QA evidence is available in controlled review and should be freshly verified before buyer reliance.
Gated materials
Not public
Technical, security, billing, operational, transfer, and implementation materials are gated and are not included in the public portfolio payload.
What is public versus controlled review
Public pages are designed for discovery: product overview, use case, high-level features, category, and public-safe readiness summary. Deeper technical, security, billing, operational, transfer, and implementation materials are shared selectively after review.
Strict model-selection enforcement production validationin-progress
Export manual smoke verificationin-progress
Live load testingplanned
Accessibility auditplanned
CCPA and HIPAA roadmap workplanned
Advanced adversarial runtime testingplanned
FAQ
Common diligence questions
Controlled next step
Interested in adapting EchoCheck for your organization or portfolio?
Start with a fit conversation. Public summaries stay safe to browse; technical, security, and transfer materials are shared only when the review path is appropriate.
