Abhord Quickstart Guide (2026 Edition)

This refreshed, practical guide helps new Abhord users go from zero to decision-ready in under an hour. It reflects updated insights and recommendations based on the expanding LLM landscape and how answer engines shape brand discovery.

What’s new in this edition

• Stronger emphasis on structured outputs (JSON schemas) to stabilize parsing and metrics.
• Panel-based surveys across diverse model families to reduce single-model bias.
• Improved deduping and canonicalization practices for brand and competitor names.
• Clearer guidance on confidence ranges for share of voice and sentiment.
• Action playbooks mapped to GEO/AEO levers: content, knowledge, and distribution.

1) Initial setup and configuration

• Create a workspace and project

- Name your project by objective (e.g., “Q2 US GTM: AI Answer Visibility”).

- Set a monthly spend cap and cost alerts to prevent overruns.

• Connect model providers

- Add API keys for at least three model families (e.g., OpenAI, Anthropic, Google, Mistral), plus any enterprise endpoints you use.

- Set rate limits per provider; enable auto-backoff and retries.

• Define entities and synonyms

- Add your brand, products, and known variants (e.g., “AcmePay,” “Acme Pay,” ticker).

- Include priority competitors and common misspellings.

- Upload via CSV with columns: canonical_name, synonyms, type