> ## Documentation Index
> Fetch the complete documentation index at: https://deepline.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Crustdata API Guide for GTM Workflows

> Start with free autocomplete and default to fuzzy contains operators `(.)` for higher recall. Includes inputs, outputs, costs, and Deepline CLI examples.

## Playbook

Use CrustData for structured discovery and enrichment with recall-first filtering.

* Start with free autocomplete (`companydb_autocomplete`, `persondb_autocomplete`) to discover canonical values.
* Default to fuzzy contains operator `(.)`; use strict `[.]` only when explicitly requested.
* Use `crustdata_companydb_search` as the resolver step; for `crustdata_enrich_company`, prefer domain-based inputs instead of name-only payloads.
* For job data, use `crustdata_v2_job_search` for indexed listings or `crustdata_v2_live_job_search` when freshness is required for a known CrustData company id. Legacy job-listing compatibility actions are hidden from discovery and should not be selected for new workflows.
* In changed-company email recovery, use Crust as the second step after LeadMagic and before PDL.
* Keep filters composable and inspect a small sample before adding expensive enrichments.
* If Crust misses in the first 10 rows for a batch, move it later for the rest of that batch.

### Filter format

`filters` accepts an array of condition objects (AND-combined automatically). Each condition: `{"filter_type":"<field>","type":"<operator>","value":"<val>"}` or `{"filter_name":"<field>","type":"<operator>","value":"<val>"}`. `filter_name` is syntactic sugar for `filter_type`; human-friendly aliases (e.g. `company_investors` → `crunchbase_investors`, `company_funding_stage` → `last_funding_round_type`) are auto-mapped. A single condition object (not in array) also works.

**Company filter\_type values:** `company_name`, `company_website_domain`, `linkedin_industries`, `hq_country`, `hq_location`, `region`, `year_founded`, `employee_metrics.latest_count`, `employee_count_range`, `employee_metrics.growth_6m_percent`, `employee_metrics.growth_12m_percent`, `employee_metrics.growth_12m`, `follower_metrics.latest_count`, `follower_metrics.growth_6m_percent`, `crunchbase_investors`, `tracxn_investors`, `crunchbase_categories`, `crunchbase_total_investment_usd`, `last_funding_date`, `last_funding_round_type`, `estimated_revenue_lower_bound_usd`, `estimated_revenue_higher_bound_usd`, `linkedin_id`, `linkedin_profile_url`, `company_type`, `acquisition_status`, `ipo_date`, `largest_headcount_country`, `markets`, `competitor_ids`, `competitor_websites`.

**Person filter\_type values:** `current_employers.company_website_domain`, `current_employers.title`, `current_employers.seniority_level`, `headline`, `region`, `num_of_connections`, `years_of_experience_raw`.

**Operators:** `(.)` = fuzzy contains (default), `[.]` = substring, `=`, `!=`, `in`, `not_in`, `>`, `<`, `=>`, `=<`. Person search also supports `geo_distance` for `region`.

**Range filtering:** There is NO range operator like `[100..500]` or `between`. To filter a numeric range, use TWO separate filter conditions with `>` and `<` (or `=>` and `=<`):

```json theme={null}
[
  {
    "filter_type": "employee_metrics.latest_count",
    "type": ">",
    "value": "100"
  },
  {
    "filter_type": "employee_metrics.latest_count",
    "type": "<",
    "value": "500"
  }
]
```

**Headcount filtering:** For headcount, prefer `employee_count_range` (string enum like `"51-200"`, `"201-500"`) with the `in` operator when exact buckets work. Use `employee_metrics.latest_count` with `>` / `<` only when you need precise numeric boundaries. Note: `employee_metrics.latest_count` is valid for `sorts` and `filters`, but `employee_count_range` uses string enum values.

### Examples

```bash theme={null}
deepline tools execute crustdata_companydb_autocomplete --payload '{"field":"linkedin_industries","query":"software","limit":5}'
```

```bash theme={null}
deepline tools execute crustdata_companydb_search --payload '{"filters":[{"filter_type":"linkedin_industries","type":"(.)","value":"software"},{"filter_type":"hq_country","type":"=","value":"USA"}],"limit":5}'
```

```bash theme={null}
deepline enrich --input accounts.csv --output accounts.csv.out.csv --with '{"alias":"company_lookup","tool":"crustdata_companydb_autocomplete","payload":{"field":"company_name","query":"{{Company}}","limit":1}}'
```