Tim Zinin

Scrape current public LinkedIn job search cards with job IDs, titles, companies, locations, posted dates, and source links without login.

Rank recent commercial permit and license records from five fixed US city datasets, with source evidence, recency, confidence, enrichment gaps, and next actions.

Compare aggregate commercial-vessel pressure across two fixed Panama Canal approach zones. Get side imbalance, movement, observed dwell, baseline change, freshness, confidence, gaps, and a human review action without exposing raw vessel identities or claiming official Canal queues.

Analyze submitted restaurant websites for evidence-backed reservation and contact gaps, booking providers, confidence, audit angles, and manual qualification actions.

Compare official monthly Singapore bunker demand, tanker arrivals, fuel mix, and vessel calls in one evidence report. Add optional bounded BYOK tanker pressure, with publication lag, freshness, confidence, null reasons, provenance, gaps, and human review.

Compare aggregate commercial-tanker observations across three fixed Strait of Hormuz zones with seven- and thirty-observation baselines. Get deterministic recovery labels, freshness, confidence, gaps, and a human-review action without exposing raw identities or positions.

Review up to 100 token contracts or bounded ticker searches using current DexScreener observations. Get pair identity, liquidity, volume, age, heuristic score, risk flags, evidence, confidence, gaps, and billing. Ticker matches remain unverified; no-match rows are free. Not financial advice.

Normalize authorized or licensed trademark evidence records into provenance-linked review rows with stable identity, freshness, visible gaps, human actions, and current-run settlement. Zero external source requests or automated business decisions.

Turn 1–100 buyer-supplied brand evidence rows into one deterministic citation-table report with preserved fields and HTTPS URLs, bounded Markdown, source and host counts, verification gaps, and SHA-256 digests. Sources are never fetched or verified; run start is separate.

Compare two buyer-supplied evidence snapshots in one deterministic report. Separate added, removed, changed, and unchanged records with stable digests, evidence gaps, human review actions, and current-run billing truth. No source fetching.

Get one bounded, official USAspending prime-contract snapshot for an exact recipient ID and date window. Preserve verified recipient identity, source as-of, first-page coverage limits, evidence gaps, human review action, and current-run billing truth.

Normalize buyer-supplied offer evidence into review-required delivery candidates. Check submitted-field consistency, preserve terms and attribution metadata, and expose evidence gaps without fetching a source or claiming external verification.

Group buyer-supplied signal rows by brand, event type, severity, or analysis status. Get one deterministic grouping report with complete counts, stable digests, evidence gaps, and a human review action. It does not create separate Datasets.

Summarize buyer-supplied signal rows by brand in one deterministic report. Preserve event, severity, status, and recorded-source counts with stable digests, evidence gaps, and a human review action. No source fetching or external verification.

Turn 1–50 buyer-supplied signal rows into one deterministic severity brief. Get complete CRITICAL/HIGH/MEDIUM/LOW sections, ordered projections, stable digests, explicit evidence gaps, and a human review action without source fetching or external verification.

Apply explicit buyer-owned accept and review thresholds to normalized signal scores. Get one deterministic report with accepted, review, and rejected queues, stable digests, evidence gaps, human review action, and current-run billing truth.

Count which opaque signals appear together across buyer-supplied groups. Get one deterministic report with support, Jaccard overlap, stable digests, evidence gaps, and a review action. No source fetching, identity inference, or causality claim.

Turn buyer-supplied signal rows into one deterministic CRM mapping template for review. Compare versioned HubSpot or Salesforce field proposals, conflicts, omissions, and evidence without logging in to or writing to either CRM.

Build one complete cross-tab from buyer-supplied row and column dimensions. Get every observed combination, including zero cells, with exact counts, row/column/overall denominators, stable digests, evidence gaps, and a review action.

Compare two buyer-supplied signal sets in one deterministic union report. Preserve left-only, right-only, exact duplicate, and field-conflict evidence without selecting a winner or fetching recorded source URLs.

Aggregate buyer-supplied signal rows into one deterministic metrics report. Get complete closed-enum counts, source totals, integer confidence basis points, review warnings, evidence gaps, and a human action without fetching external sources.

Compare up to 20 explicit buyer-owned threshold policies over normalized signal scores. Get complete outcomes, pairwise changes, sensitive signals, stable digests, evidence gaps, human review action, and current-run billing truth without selecting a winner.

Turn buyer-supplied normalized signals and ordered rules into one deterministic routing plan. Preserve matched routes, unmatched signals, warnings, stable digests, evidence gaps, human review action, and current-run billing truth without contacting destinations.

Count adjacent directed transitions across buyer-supplied opaque sequences. Get one deterministic report with exact sequence and transition counts, stable digests, explicit evidence gaps, and a human review action. No identity, timing, or causality claim.