# Search-box.ai

Don't search the web. Search the answer space.

Search-box.ai is a multi-step, agentic web research engine. Given a hard question it autonomously forms hypotheses, decomposes uncertainty, runs purposeful searches, opens sources, extracts verbatim evidence, surfaces contradictions, updates beliefs — and streams a fully sourced answer while you watch every step live.

Built on the Anthropic Claude API (reasoning & orchestration) and Firecrawl (web infrastructure). PostgreSQL holds the durable research state; every UI update corresponds to a real backend event.

# Screenshots

A completed research session — the question blooms into objectives and claims, every node driven by a real backend event:

Home — ask a question that deserves real research

Mobile-first, one-handed

# Validated on a real research problem

Benchmark question: "Can transformer KV cache be compressed by an order of magnitude without seriously harming model quality?" — one autonomous session, no human steering:

The engine assigned differentiated confidence per claim (40% / 85% / 90%), and caught a genuine contradiction: a vendor blog presenting 8× compression as "comparable" quality for a method whose peer-reviewed paper only claims lossless behavior up to 4×.

# How it works

question → understand objective → form hypotheses → decompose uncertainty
→ decide next action → use web tools → inspect evidence → update beliefs
→ identify gaps/contradictions → repeat → synthesize evidence-backed answer

• No fixed pipeline — Claude decides research strategy through tool use; the app enforces safety: hard budgets, zod-validated tool contracts, SSRF guard, prompt-injection defense on all scraped content.
• Claims & evidence are first-class objects — verbatim quotes tied to falsifiable claims with stances (supports / contradicts / context) and probabilistic confidence.
• Contradictions are a research success, not an error state.
• Provenance is never lost — every answer sentence traces mechanically: sentence → [n] marker → citation index → source → evidence → claim.
• Event-sourced UI — the client replays the persisted event stream (SSE with Last-Event-ID recovery); nothing on screen is a fake progress animation.

# Quick start

pnpm install
cp .env.example .env        # ANTHROPIC_API_KEY, FIRECRAWL_API_KEY, DATABASE_URL
pnpm migrate                # apply PostgreSQL schema
pnpm dev                    # web app on http://localhost:3000

Run a session from the terminal:

pnpm research "Your hard question here"

# Repository structure

apps/web            Next.js app (UI + API routes + SSE)
packages/agent      orchestrator loop, prompts, tools, session runner
packages/research   ResearchState service (claims, evidence, sources, contradictions)
packages/firecrawl  Firecrawl v2 adapter (search, scrape) + SSRF guard
packages/anthropic  Anthropic Messages API adapter (streaming)
packages/events     typed research event protocol
packages/db         PostgreSQL schema, migrations, repositories
packages/shared     shared types, zod schemas, budgets, ids
deploy/             ngrok config + start script (node m3u96a)
docs/               architecture, agent loop, research state, event protocol

Full design notes in docs/architecture.md.

# Deployment

Production runs on node m3u96a behind an ngrok tunnel: https://www.search-box.ai — see deploy/.

# Author

Simon-Pierre Boucher 📫 contact@spboucher.ai

© 2026 Simon-Pierre Boucher. All rights reserved.