ContextForge

Forge lean LLM contexts. Keep every fact.

30%

Raw context —

Forged context —

How it works

ContextForge workflow: raw context in, compression engine, faithfulness verification, forged context out

1 · Score

The extractive engine splits your context into sentences and scores each by information density, with primacy/recency weighting — because models forget the middle (Lost in the Middle, TACL 2023).

2 · Forge

Top sentences fill your token budget in original order. First and last sentences are always kept. Numbers, dates and URLs get extra protection.

3 · Verify

Every checkable fact in the original is matched against the output. Anything missing is flagged by severity before you ship the prompt.