Architecture

How Beacon's research system is structured.

Beacon's core differentiator is not a landing page. It is the workflow composition across context, memory, and harness layers.

Search docs, support, and public pages
search
Layers

Core execution model

Context

Plans queries, compresses search results, and guides synthesis for each run.

Memory

Loads what a topic already knows first, filters seen URLs, and saves updated state last.

Harness

Keeps step behavior idempotent, resilient, and durable across recurring runs.

Workflow

Research run flow

1. loadMemory
2. planQueries
3. runSerpQuery in parallel
4. synthesizeReport
5. saveMemory
6. optional recurring sleep and rerun
Model Rules

Approved model layer

Beacon uses scoutModel for tool use and planning and synthModel for writing, both sourced from @/lib/groq. Direct provider imports outside that abstraction are intentionally not part of the repo contract.