# Grais

> Communication science and AI-assisted conversation systems.

This file is a curated map for LLM retrieval and citation.

## Canonical
- [Homepage](https://grais.ai)
- [Research Index](https://grais.ai/research)
- [RSS Feed](https://grais.ai/rss.xml)
- [Sitemap](https://grais.ai/sitemap.xml)

## Communication Science Research
- [Decision-Criteria Elicitation Before Solutioning](https://grais.ai/research/decision-criteria-elicitation-before-solutioning): A communication protocol for defining what will count as a good decision before you present options, so conversations produce clearer commitments and fewer reversals.
- [First-Turn Intent Clarification Protocol](https://grais.ai/research/first-turn-intent-clarification-protocol): A practical framework for clarifying what people actually need in the first exchange, so recommendations land with less resistance and better follow-through.
- [Non-Brand Intent Bridge Protocol](https://grais.ai/research/non-brand-intent-bridge-protocol): A communication-science protocol for helping low-context readers classify fit quickly through clear framing, trust boundaries, and decision-ready language.
- [Brand-Query Leakage Trust-Floor Protocol](https://grais.ai/research/brand-query-leakage-trust-floor-protocol): A reader-first framework for converting branded search visibility into qualified intent by tightening communication clarity and trust boundaries.
- [Conversation Trust-Floor Framework](https://grais.ai/research/conversation-trust-floor-framework): A reader-first, lab-grade framework for improving high-stakes communication outcomes without creating hidden trust debt.
- [De-escalation Protocol for Heated Threads](https://grais.ai/research/de-escalation-protocol-for-heated-threads): A practical, evidence-aligned de-escalation protocol for lowering emotional intensity while preserving momentum and outcomes.
- [Objection Handling Without Pressure](https://grais.ai/research/objection-handling-without-pressure): Handle objections with diagnostic clarity and persuasive structure, without triggering defensiveness or trust loss.
- [Re-engagement After Silence Playbook](https://grais.ai/research/re-engagement-after-silence-playbook): Re-open stalled conversations with low-friction prompts that recover momentum without sounding desperate.
- [Tone Calibration Under Pressure](https://grais.ai/research/tone-calibration-under-pressure): A fast calibration method for matching tone to emotional context without losing clarity, authority, or pace.
- [High-Stakes Follow-up Sequence](https://grais.ai/research/high-stakes-follow-up-sequence): A structured follow-up sequence for critical conversations where timing, clarity, and commitment quality matter.
- [Empathy With Boundaries in Support Conversations](https://grais.ai/research/empathy-with-boundaries-support-conversations): Use empathy to reduce friction and preserve trust, while maintaining clear boundaries on scope, policy, and next actions.
- [Multi-Stakeholder Decision Clarity Framework](https://grais.ai/research/multi-stakeholder-decision-clarity-framework): Align multi-party conversations around explicit decision criteria, ownership, and timing to reduce drift and hidden disagreement.
- [Diagnostic Questioning for Unclear Conversations](https://grais.ai/research/diagnostic-questioning-for-unclear-conversations): Use diagnostic questions to remove ambiguity fast, improve response quality, and reduce costly misalignment.
- [Commitment-Close Framework](https://grais.ai/research/commitment-close-framework): Turn conversation quality into execution by closing with explicit commitments, ownership, and measurable next steps.

## Policy and Support
- [Terms of Service](https://grais.ai/p/tos)
- [Privacy Policy](https://grais.ai/p/privacypolicy)
- [Data Handling](https://grais.ai/p/data-handling)
- [Support Center](https://grais.ai/support)