Maya Patel·
Synthesized three weeks of messy research notes into a proper intelligence brief with confidence ratings. My analyst brain finally has a template.
Turns unstructured research notes into a structured intelligence brief with key judgments, evidence, and confidence levels.
Messy Notes to Intelligence Brief
You are a senior intelligence analyst. I will paste raw, unstructured research notes below. They may contain duplicates, half-finished thoughts, quotes, links, and contradictory claims. Your job is to synthesize them into a decision-ready intelligence brief.
Structure the brief exactly like this:
1. **Bottom Line Up Front (BLUF)** — 2-3 sentences answering: {{core_question}}
2. **Key Judgments** — 3-5 numbered judgments. Each judgment gets a confidence rating (High / Moderate / Low) with one sentence explaining why that rating.
3. **Supporting Evidence** — for each judgment, list the specific notes that support it. Quote or paraphrase, and mark each source as primary, secondary, or unverified.
4. **Contradictions & Gaps** — where do my notes disagree with each other? What critical information is missing? Be explicit; do not paper over conflicts.
5. **Indicators to Watch** — 3-4 observable signals that would strengthen or weaken the key judgments over the next {{time_horizon}}.
6. **Collection Requests** — what should I research next, in priority order?
Rules: Never invent facts that are not in my notes. If a judgment rests on a single unverified source, cap its confidence at Low. Use analytic language ("likely", "unlikely", "we assess") rather than absolutes. Keep the whole brief under 700 words.
My notes:
{{raw_notes}}
Ergebnisse
## Intelligence Brief: EU AI-Compliance Tooling Market
**BLUF:** The market for EU AI Act compliance tooling is consolidating faster than expected. We assess it is likely (Moderate confidence) that 2-3 platform players will absorb most point solutions within 18 months, making a narrow-wedge entry viable only with a clear acquisition or integration story.
### Key Judgments
1. **Consolidation is accelerating.** — Confidence: **Moderate**. Three acquisitions in eight weeks is a strong signal, but the sample is small.
2. **Buyers want audit-trail features over dashboards.** — Confidence: **High**. Consistent across all six customer interviews and two independent surveys in the notes.
3. **Pricing is settling at €2-4k/month mid-market.** — Confidence: **Low**. Based on a single unverified forum post and one sales call; treat as anecdote.
4. **Legal teams, not engineering, hold the budget.** — Confidence: **Moderate**. Four of six interviews support this; two contradict it.
### Supporting Evidence
- J1: TechCrunch note on Holistic AI deal (secondary); two founder conversations (primary).
- J2: Interview notes #2, #4, #5, #9 (primary); Gartner excerpt (secondary).
- J3: Forum screenshot (unverified).
- J4: Interviews #2, #3, #6, #8 (primary).
### Contradictions & Gaps
- Interview #7 claims engineering owns the budget at companies >1,000 FTE — directly contradicts J4. Possible segmentation effect by company size.
- No data at all on public-sector demand. This is a material gap.
### Indicators to Watch (next 2 quarters)
1. A fourth acquisition announcement → strengthens J1.
2. Job postings for "AI compliance lead" in legal vs. engineering orgs → resolves J4.
3. Published pricing pages from two named vendors → resolves J3.
4. First enforcement fine under the AI Act → likely demand shock.
### Collection Requests
1. Five interviews at companies >1,000 FTE to resolve the J4 contradiction.
2. Pricing verification via two demo calls.
3. Public-sector procurement scan (TED database).
Modell: o3
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2 Kommentare
Anna Hofmann·
The confidence caps on single-source claims are the best part. Stealing that rule for my decision memos.
Hannah Meier·
Ran my keyword research notes through this and the Contradictions section alone was worth it.