search_actuarial_embeds
shallowai.serff/ca-rate-filings · Verify this server
Pure vector search over per-filing actuarial-memorandum embeddings (`extract_embeds` where `kind='actuarial_memo'`). Each hit is a filing whose memo is semantically closest to your query, with the matching excerpt and lite filing metadata. **Cost**: one query-embedding call + one indexed Postgres lookup. Bounded, cheap, fast. No LLM planning, no LLM composition. **This is the right tool any time the question is *actuarial-shape*.** Reach for it — not `search_summary_embeds` and not `search_filing_embeds` — when the user is asking about: - Rate adequacy: headline rate change, indicated vs selected, off-balance, capping. - Loss trends: severity trend, frequency trend, pure-premium trend, projected ultimates, LDFs, IBNR development. - Credibility / experience: experience period, weight assigned to own experience vs class-plan / bureau, credibility tables. - Expense / profit provisions: permissible loss ratio, target combined ratio, profit & contingency loading, expense ratio, investment-income offset. - Reason codes / drivers: reinsurance cost, weather/cat load, severity-driven rate need, mix shift, frequency reductions from telematics. - Anything where the answer would be a *number from the actuarial memo* rather than a description of what the filing does. The memo is where actuaries put the numerics; the extraction summary is where the pipeline puts the prose. If the question reaches for numbers, hit this surface first. **Wrong surface for**: - *Content* questions ("filings discussing wildfire scoring", "telematics programmes", "parametric triggers") — those discuss what the filing is *about*, not actuarial numerics. Use `search_summary_embeds` (broader coverage). - Concrete-filter questions ("Filings from carrier NAIC 12345 in 2024") — use `search_filings`. - Filings with no actuarial memo. Memos are typically attached to Rate filings; Form, Rule, and Withdrawal filings often have none. Coverage is narrower than `search_summary_embeds` for that reason — most of the 2026 corpus is covered, prior years are backfilling. **How to combine**: - "Personal auto filings in California whose indicated rate exceeds selected by 5+ points" → `search_filings` (state=CA, product_type="Personal Auto", filing_type="Rate") to scope a candidate set, then this tool over the candidates' memos. - "Carriers citing severity-driven rate need in 2025" → this tool first; `get_filing_summary` on the top hits to read in full. Returns top-K hits, each with `{serff, similarity, excerpt, meta}`. Default `topK=10`, max 50. Excerpt is the first 800 chars of the matching memo.
1 trials · measured 8 days ago
search_actuarial_embeds scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against ai.serff/ca-rate-filings, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.
Component breakdown
| Component | Weight | Value |
|---|---|---|
| Reliability | 35% | not applicable |
| Schema integrity | 25% | 100.0 |
| Failure behaviour | 15% | not applicable |
| Latency | 15% | not applicable |
| Concurrency | 10% | not applicable |
Tool details
- Transport
- remote
- Credential class
- self-provisionable
- Category
- Finance & compliance
- Input schema
- not declared
- Output schema
- not declared
- Side-effect classification
- unclassified
Score history
| Day | Score | Tier | Methodology |
|---|---|---|---|
| 2026-08-25 | 100.0 | shallow | v0.2.0 |
Probe evidence
| Probe | Outcomes |
|---|---|
| schema_integrity | pass: 1 |
Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.
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