Rafael Barreto Haddad

Analyze observed MCP and AI-agent tool telemetry to rank tools, expose reliability and cost risks, preserve task coverage, and generate an evidence-based routing policy.

Audit robots.txt policies for major AI crawlers and inspect llms.txt discovery files for public websites with structured machine-readable results.

Turn aviation schedule snapshots into route-level seat-capacity expansion, contraction and competitive supply intelligence.

Turn app-store privacy metadata snapshots into app-level data-collection, tracking and disclosure drift intelligence.

Extract public business emails, tel links, and major social profiles from company websites and likely contact/about pages. Returns one structured result per site with explicit issues and safe public-URL validation.

Detect competitor support-policy, FAQ, SLA and return-policy shifts from recurring website-content datasets.

Turn job-posting snapshots into company and role signals that suggest contractor demand is shifting toward permanent employment.

Build source-to-destination talent-flow intelligence between competing companies from recurring employee datasets.

Profile field completeness, cardinality, type distributions, and numeric ranges, then compare them with a baseline to flag data-shape anomalies.

Find duplicate groups in Apify datasets, quantify duplicate risk, and generate deterministic merge recommendations without mutating the source.

Compare two Apify datasets or inline snapshots and explain added, removed, and changed records plus field-level change frequencies.

Measure dataset recency against a timestamp field and enforce freshness, minimum-volume, and recent-item SLA thresholds for scheduled pipelines.

Scan Apify datasets for likely personal or sensitive data patterns and return masked, field-level exposure evidence for privacy and pipeline controls.

Validate any Apify dataset before downstream use with required-field, duplicate, null-rate and minimum-size checks, producing a structured pass/fail quality score for Actor-to-Actor workflows.

Detect top-level field additions, removals, and type changes in Apify datasets with deterministic schema fingerprints and optional pipeline stopping.

Detect newly observed domains that resemble protected brands and rank registration, WHOIS and DNS risk signals.

Turn recurring job datasets into employer concentration risk across roles, locations and hiring clusters.

Monitor openFDA FAERS report volume, serious/death shares, reaction composition and changes over time for drug watchlists, with persistent state and explicit non-causal safety interpretation.

Turn FDA recall datasets into recalling-firm concentration, Class I exposure, distribution breadth and supplier-risk signals.

Monitor Federal Register topics for new or updated regulatory documents, rank materiality, persist state between runs, and return decision-ready change intelligence rather than a raw document dump.

Turn SEC Form D snapshots into issuer-level fundraising velocity, new-offering and capital-formation momentum intelligence.

Scrape Google Maps businesses, enrich public contacts, rank commercial opportunities, compare snapshots, and produce agent-ready local market intelligence.

Map local competitors by query and location, quantify saturation, rank white-space opportunities and track market-entry changes from Google Maps data.

Analyze Google Maps review datasets to detect rating drift, negative-review acceleration, reputation risk and competitor review momentum.