Endpoint: POST /screener/person/search
Date: 2026-04-21
Reproducible: yes, every call
We pass post_processing.strict_title_and_company_match: true expecting your API to return only profiles where a role at the target company also matches the title filter. Instead, the API returns profiles where:
Project: Learco Personal, Project 1409 (Graphisoft CEO search)
Date: 2026-04-04
Candidates: 359 with full LinkedIn profiles
Scoring factors: 6, all on 0-5 scale (total max: 30)
Runs per experiment: 5
Concurrency: 32 parallel requests (10 for Anthropic due to latency)
Prompt: Identical across all experiments (exported via experiment:export-prompts using production CandidateScoringPromptService)
Dealroom enrichment: Skipped (to eliminate external API nondeterminism)
We ran a candidate sourcing project targeting VP/Head/Director of Sales, Revenue, and Commercial roles across 735 SaaS companies in Sweden and Finland.
We ran the same search through two pipelines:
/screener/persondb/search)
Model:
grok-4-1-fast-reasoning(xAI) for both scoring and tiering.
Date: 2026-03-30
Context: Follow-up to earlier bug report. CrustData team recommended using linkedin_profile_url (URN format, immutable) instead of flagship_profile_url (slug format, can change). We switched to URN and re-tested.
Topliner is a multi-tenant platform where users belong to Spaces (teams). Data from one team must never be accessible to users outside that team. This document evaluates four approaches to data isolation and explains why we chose application-level checks.
Current stack: Laravel (PHP), Azure Managed MySQL 8.0, Redis, 100+ PM2 queue workers.
Data model constraints:
Date: 2026-03-20 Context: This analysis builds on the COMPANY_DATA_PROVIDERS_COMPARISON.md (2026-03-14) with empirical data from 1,346 Dealroom and 318 CrustData company records in our production
company_identifierstable.
No. CrustData cannot replace Dealroom for company intelligence in our scoring pipeline. The two services are complementary, not interchangeable. Dealroom provides financial data (revenue, EBITDA, funding rounds with investors, growth stage) that CrustData simply does not have. CrustData provides headcount analytics (role/region/skill breakdowns, weekly timeseries) that Dealroom does not have.