PredictLeads: Technologies

Returns a list of all tracked Technologies.

Tool ID: predictleads_technologies

Run this action

Use the TypeScript SDK for a single call. Put ctx.tools.execute(...) inside a Play when the call should be durable, scheduled, or run across a CSV.

import { Deepline } from 'deepline';

const deepline = await Deepline.connect();
const result = await deepline.tools.execute(
  'predictleads_technologies',
  {
    "fuzzy_name": "Example",
    "order_by": "created_at_asc",
    "page": 1
  },
);

console.log(result.toolResponse.raw);

CLI

deepline tools execute predictleads_technologies --input '{
  "fuzzy_name": "Example",
  "order_by": "created_at_asc",
  "page": 1
}' --json

Example response

The static output schema is not detailed enough to generate a reliable example. Use deepline tools get predictleads_technologies --json for the complete live contract.

Input reference

Returns a list of all tracked Technologies.

Name	Type	Required	Default	Details
`payload.fuzzy_name`	`string`	No	—	Filter results based on Technology’s fuzzy name.
`payload.order_by`	`string`	No	`"created_at_asc"`	Order of `TechnologiesDatasets`.
`payload.page`	`integer`	No	`1`	Page number of shown items. NOTE: If the parameter is not provided, the meta property `count` will be omitted from response for performance reasons. Minimum: 1.
`payload.limit`	`integer`	No	`100`	Limit the number of shown items per page. Maximum: 1000.

Output reference

Standard tool result payload.

Name	Type	Required	Default	Details
`result.data`	`object`	Yes	—	Technologies dataset consists of some 53,000 technologies we track. NOTE: If you’re searching for technologies a given company is using please check the Technology Detections Dataset section. Technologies are collected from script tags, DNS records, IP ranges, cookies…, and also from job descriptions where companies mention them as required skill sets. Subpages checked for technology data are of the following categories: main, login, support, trust, retail, blog, news, press and news See the live schema for the complete constraint.
`result.data.data`	`array`	Yes	—	—
`result.data.data[].id`	`string`	Yes	—	ID of the `TechnologyLite` object. Format: `uuid`.
`result.data.data[].type`	`"technology"`	Yes	—	Type of the `TechnologyLite` object.
`result.data.data[].attributes`	`object`	Yes	—	Attributes of the `TechnologyLite` object.
`result.data.data[].attributes.name`	`string`	Yes	—	—
`result.data.data[].attributes.description`	`null \| string`	Yes	—	—
`result.data.data[].attributes.categories`	`array`	Yes	—	—
`result.data.data[].attributes.parent_categories`	`array`	Yes	—	List of parent categories assigned to the technology.
`result.data.data[].attributes.domain`	`null \| string`	Yes	—	—
`result.data.data[].attributes.url`	`null \| string`	Yes	—	Format: `uri`.
`result.data.data[].attributes.pricing_data`	`object`	Yes	—	—
`result.data.data[].attributes.pricing_data.min_usd`	`null \| number`	Yes	—	—
`result.data.data[].attributes.pricing_data.max_usd`	`null \| number`	Yes	—	—
`result.data.data[].attributes.pricing_data.average_spend`	`null \| number`	Yes	—	The average technology spend price is derived from estimating company revenue and number of paid users.
`result.data.data[].attributes.pricing_data.interval`	`null \| string`	Yes	—	—
`result.data.data[].attributes.pricing_data.tags`	`array`	Yes	—	Pricing model and/or cost tags.
`result.data.data[].attributes.created_at`	`string`	Yes	—	Format: `date-time`.
`result.data.data[].relationships`	`object`	Yes	—	The data contains references to related objects listed in the `included` property.
`result.data.data[].relationships.company`	`object`	Yes	—	The data contains a reference to related `CompanyLite` object listed in the `included` property.
`result.data.data[].relationships.company.data`	`object`	Yes	—	—
`result.data.data[].relationships.company.data.id`	`string`	Yes	—	ID of the included `CompanyLite` object. Format: `uuid`.
`result.data.data[].relationships.company.data.type`	`"company"`	Yes	—	Type of the included `CompanyLite` object.
`result.data.included`	`array`	Yes	—	Contains objects referenced in property `relationships`.
`result.data.included[].id`	`string`	Yes	—	ID of the `CompanyLite` object. Format: `uuid`.
`result.data.included[].type`	`"company"`	Yes	—	Type of the `CompanyLite` object.
`result.data.included[].attributes`	`object`	Yes	—	Attributes of the `CompanyLite` object.
`result.data.included[].attributes.domain`	`string`	Yes	—	Company domain name.
`result.data.included[].attributes.company_name`	`string \| null`	Yes	—	Company name if available.
`result.data.included[].attributes.ticker`	`string \| null`	Yes	—	Company stock symbol (ticker) if available.
`result.data.meta`	`object`	No	—	Meta information about `TechnologiesDataset` object.
`result.data.meta.schema_version`	`string`	Yes	—	Represents schema version of objects.
`result.data.meta.record_state`	`"active"`	Yes	—	Represents record state of objects.
`result.data.meta.count`	`integer`	No	—	Total number of results. NOTE: Only included in API responses when the request parameter `page` is provided, for performance reasons.
`result.meta`	`object`	No	—	Additional response metadata (status, paging).

Deepline cost

Pricing model: fixed (per call).
Estimated Deepline credits: 0.56 per pricing unit.

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Reference

PredictLeads: Technologies

Run this action

CLI

Example response

Input reference

Output reference

Deepline cost

​Run this action

​CLI

​Example response

​Input reference

​Output reference

​Deepline cost

​Related documentation

Run this action

CLI

Example response

Input reference

Output reference

Deepline cost

Related documentation