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SLM-Works

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SLM-Works Doc Summarizer

Concise summaries of long-form business documents

Generates concise, role-specific summaries from dense documents while preserving high-signal facts, owners, and deadlines.

2B~90% fewer tokens per summary vs GPT-4

How it works

  1. Step 1

    Segment large document into semantically coherent sections.

  2. Step 2

    Extract decisions, actions, and risks from each section.

  3. Step 3

    Assemble output in selected format (brief, bullets, or JSON).

  4. Step 4

    Return final summary with references to source sections.

Example

Example input

60-page board pack with financial, legal, and operational updates.

Example output

{ executive_brief: '...', decisions: [...], actions: [{ owner: 'COO', due: '2026-04-10' }], risks: [...] }

Key features

  • Long-context summarization for enterprise docs
  • Action/decision extraction
  • Template-driven output formats
  • Terminology-preserving summaries for technical content

Rollout guidance

  • Use department-specific prompts for board, legal, and engineering documents.
  • Define acceptable omission criteria with business stakeholders.

Ideal for

Executive assistantsBoard secretariesAnalystsProject managers

FAQ

How do we avoid hallucinated actions?

Enable strict extraction mode and require citation snippets in pilot phases for verification.

Want this model in your stack?

We can scope a deployment blueprint, evaluation set, and integration plan for your data and infrastructure constraints.