Built for agents to read. And to act.
Most marketing sites expect a human to parse them. Behar is structured so an AI agent can retrieve, extract, and operate without scraping — through a REST API (read + write), a published OpenAPI spec, JSON-LD on every page, and llms-full.txt at the root.
If you're building an agent that needs brand-visibility signal, this page is the contract.
What an agent can do with Behar.
Read the state of a brand's AI visibility, detect gaps, trigger content generation, and verify re-measurement — all without a browser in the loop.
REST API (read + write)
Pull projects, prompts, competitors, gaps, runs, and content pieces — and POST to create projects or trigger writes. JSON over HTTPS, versioned endpoints, predictable pagination. Base URL: app.behar.ai/api/v1.
Structured LLM-readable content
Every page emits JSON-LD schema. /llms.txt summarizes the site. /llms-full.txt ships the full factual base in one request. No scraping required.
Bearer-token auth
Per-workspace API keys, issued from Settings > API Keys in the app. Encrypted with AES-256-GCM. Rotate any time. Send as Authorization: Bearer <api_key>.
Deterministic CSV export
Stable column schemas for prompts, runs, gaps, citations. Diffable across runs. Safe to treat as a tabular source in retrieval pipelines.
Strategic intelligence reads
Blind-spot detection, content playbook, and citation-network analysis — strategic outputs computed per project from 60+ days of monitoring data.
Distribution intelligence reads
Behar maps which platforms (Reddit, Quora, YouTube, G2, press) are feeding AI answers in your category, so an agent knows where to focus content investment. Platform-native content generation is on the roadmap — the read surface today exposes citation-source analysis only.
Which surface, which plan.
Everything public stays public. Everything scoped to a workspace requires a token. Everything that changes state requires write access.
Rate limits are per-token. Exact numbers published in the API reference at docs.behar.ai (alongside GA).
One request. Full factual base.
An agent that needs to answer “what is Behar, what does it cost, and how does it score visibility” can fetch /llms-full.txt once. No JavaScript execution. No DOM traversal.
The read surface, enumerated.
Base URL: https://app.behar.ai/api/v1. Every endpoint returns JSON and accepts Authorization: Bearer <api_key>. Full OpenAPI spec: app.behar.ai/openapi.json.
Core concepts: a prompt is a search query users ask LLMs. A run queries all active LLMs with all tracked prompts and scores the results. Scores (0–100) cover presence, rank, and voice. A gap is a prompt where competitors outrank the brand.
Why agents get reliable data out of Behar.
Agent-accessibility isn't an export feature. It's a writing discipline applied to every page.
Every page leads with a declarative fact. Pricing, formulas, limits, and methodology are stated in plain numbers, not marketing language. Agents extract the same answer humans do.
Behar Score math lives on /methodology. Glossary lives on /glossary. Comparisons live on /compare. When an agent retrieves, it lands on a canonical page — no content duplication across routes.
Blog posts, changelog entries, and legal pages all carry visible datePublished and dateModified. Agents can resolve freshness without guessing.
Comparison tables on /compare render as semantic <table>, not CSS grids of <div>. Downstream extraction preserves rows and columns.
Third-party stats cite their source (publication and date). Agents can propagate provenance without losing it.
Every page owns its canonical URL. No trailing-slash drift, no campaign parameters in sitemaps, no redirect chains. Bookmark-safe for agent memory.
Explicitly welcome.
robots.txt explicitly allows GPTBot, ChatGPT-User, Claude-Web, ClaudeBot, anthropic-ai, Google-Extended, Applebot-Extended, PerplexityBot, Perplexity-User, CCBot, and DiffBot.
The only disallowed paths are /api/ (scoped to authenticated use) and /trial/ (conversion funnel, not informational).
Wiring Behar into an agent? We want to hear what you're building.
We're running private beta access for agent integrations ahead of GA. If your project reads from Behar, tell us the shape — we'll prioritize endpoints accordingly.