Draup for Sales

Get workforce trends for an account Returns a month-by-month talent-flow series for the company given by `id` across `filters.monthly_time_frame` (`min`/`max` as MM-DD-YYYY; by default the 12 months ending with the month three months before the current one), one entry per month keyed like `Aug 2025`. Counts are aggregated from Draup's workforce data; no individual records are returned: `hiring` is tenures at the company that started in the month, `attrition` tenures that ended in it, `net_gain_loss` their difference, and `total_workforce` the company's workforce at the end of the month. `req_type` and `workforce_type` are required. `req_type` `table` always returns all four measures per month; otherwise `workforce_type` `hiring`, `attrition`, `total_workforce` or `net_gain_loss` returns `{key, value, additional_data}` per month. Months are chronological unless `pagination.sortBy`/`sortType` is given. `response_data` accepts only `job_families`, `locations`, `competitors` and `projects`; any other key returns HTTP 400. `filters.work_experience` narrows by years of experience. Request Examples: Table view for all workforce without entity filters: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "table", "workforce_type": "all" } Graph view for total workforce filtered by location: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "graph", "response_data": { "locations": { "or": [ "United Kingdom" ] } }, "workforce_type": "total_workforce" } Graph view for total workforce filtered by location, job families, and companies: { "filters": { "monthly_time_frame": { "max": "07-31-2026", "min": "08-01-2025" } }, "req_type": "graph", "response_data": { "locations": { "or": [ "San Francisco Bay Area, United States" ] }, "competitors": { "or": [ "Intel Corporation", "Apple Inc." ] }, "job_families": { "or": [ "Software & Technology Management", "Systems Management & Engineering" ] } }, "workforce_type": "total_workforce" }

accounts_talent_flow_workforce_trends_v3

Turn a company search query into company directory filters Interprets a natural-language search query about companies and returns structured filters for the Draup company directory: boolean_response, an entity-keyed tree of or/and/not value lists (for example {"companies": {"or": ["Nvidia Corporation"]}}) to send as response_data to get_universe_companies_v3; synon_list with the Draup values each term was matched or expanded to; range filters such as revenue, employee count, funding amount or year established; a suggested pagination sort and view_name; and an identifier. Use it when you need company-search filter values from a free-text request. An AI model interprets the query together with today's date, the directory's filter vocabulary and the sortable columns available for the caller's product. Terms that do not map to a usable filter come back as free-text keywords. Only current_input is interpreted; the other body fields are accepted but ignored. When the query cannot be interpreted the call still returns HTTP 200, with is_valid false and an error_message instead of filters. Request Examples: Minimal body with only free-text input: { "current_input": "semiconductor companies in Bangalore" } Parse input with project context and different sort field: { "view_name": "Opportunities", "pagination": { "limit": 25, "offset": 0, "sortBy": "exec_movement_flag", "sortType": "DESC nulls last" }, "project_id": 267402, "current_input": "google" } Parse company name for Opportunities view with scoring sort: { "view_name": "Opportunities", "pagination": { "limit": 25, "offset": 0, "sortBy": "talent_oi_score", "sortType": "DESC nulls last" }, "current_input": "Nvidia Corporation" }

build_company_filters_v3

Turn a news search query into Signals filters Interprets a natural-language search query about company news and returns structured Signals filters: a rephrased search phrase, plus any companies, industry verticals, signal categories and saved project lists it recognises, a capture-date range when the query implies one, and synonym records for the matched company names. Use it when you need Signals filter values from a free-text request, then send boolean_response as response_data (and filters as filters) to a Signals search tool such as get_signal_news_v3. An AI model interprets the query, so the same query can give slightly different filters, and only entities enabled for the caller's Signals search are returned. When the query cannot be interpreted, the response has is_valid false and an optional error_message, and carries no filters. Request Examples: Topic query: { "current_input": "labor market news" } Query naming a signal category and a company: { "current_input": "recent deals and partnership news about Microsoft" }

build_news_filters_v3

Get a service provider's top customers, customer verticals, delivery locations and workloads Returns a snapshot of a service provider's outsourcing business, built from the active outsourcing deals in which the company is the vendor: its top customers, the verticals those customers belong to, its main delivery locations and the workloads it delivers. Use it to see who an IT services, engineering services or professional services firm works for and what it delivers. Data exists only when the company's primary vertical is IT Services, Product Engineering Services or Professional Services; for any other company, or a service provider with no active deals, every list is null or left out. Each list holds up to the top three entries: customers by number of active deals with this vendor, customer verticals by number of distinct customers, and delivery locations and workloads by number of deals. Only deals whose customer is visible in the caller's product are counted, for all four lists. A list is null or left out when there is no data for it. A deal is active when it is not flagged inactive and has no end date or one in the future. Each customer's account_id is a Draup account ID. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.

customers_deals_v3

Count outsourcing deals matching entity filters Returns the total number of outsourcing/service-provider deals matching the given entity filters, as a single-element result list with a total_count field. Call it with the same response_data used for the matching deals_get_landing_data list to learn how many deals a filter combination matches, e.g. before paging through results. Filter with response_data using canonical plural keys such as "customers", "service_providers", "digital_products", and "hq_locations", each set as {"or": ["value"]}; never filter by numeric company id, use the company name instead. An empty response_data counts all deals in the corpus. Request Examples: Deal count for one customer: { "response_data": { "customers": { "or": [ "Walmart Inc." ] } } } Digital products (multi-value) plus HQ location: { "response_data": { "hq_locations": { "or": [ "India" ] }, "digital_products": { "or": [ "NetSuite", "NetSuite Supply Chain Management System" ] } } } Deal count for one service provider: { "response_data": { "service_providers": { "or": [ "Accenture" ] } } }

deals_get_data_count

Get organization data with decreasing workforce for a vertical Returns a list of organizations within the specified vertical/industry that have experienced a decrease in workforce, along with attrition percentages and percentile statistics. Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }

ecosystem_get_organization_decreasing_workforce

Get organization data for increasing workforce by vertical Retrieves a list of organizations within a specified vertical (analysis_entity) that are experiencing an increasing workforce trend. The response includes workforce counts, attrition percentages, and percentile thresholds (33rd and 67th) to help classify organizations into high, medium, or low categories based on attrition. Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }

ecosystem_get_organization_increasing_workforce

Get IT Spend Top Metrics Returns the current value and change percentage of IT spend for a specified analysis entity (vertical). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_it_spend

Get vertical key priorities Fetches a list of key priorities for a specific vertical or analysis entity. The response includes detailed descriptions, functional categories, and a relevance flag for each priority item. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_key_priorities

Get Top Employers for an Analysis Entity Returns a list of top employer organizations for the specified analysis entity (such as a vertical or industry). Each employer includes its account ID, name, logo URL, and employee count. Also returns percentile information for employee counts. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_organization_top_employers

Get Top Startups Organization Data Returns a list of top startups for a given analysis entity, with optional filters for sub-verticals or locations. Request Examples: No filters: { "analysis_entity": "Product Engineering Services" } Filter by locations: { "response_data": { "locations": { "AND": [ { "OR": [ [ "Greater Los Angeles Area, United States", "locations", false, true ] ] } ] } }, "analysis_entity": "Aerospace" } Filter by sub-verticals: { "response_data": { "sub_verticals": { "AND": [ { "OR": [ [ "Oil & Gas Upstream", "sub_verticals", false, true ] ] } ] } }, "analysis_entity": "Energy & Utilities" }

ecosystem_get_vertical_organization_top_startups

Get top hiring accounts for a vertical Returns a ranked list of top hiring accounts (organizations) for the specified analysis entity (typically a vertical such as an industry). Each account entry includes the internal account identifier, organization name, logo URL when available, and the hiring count used for ranking. The response also contains percentile thresholds that can be used for classifying accounts into high, medium, and low hiring intensity segments. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_organization_top_top_hiring_accounts

Get Outsourcing Customers by Vertical Retrieves a list of outsourcing customers for the specified vertical (analysis_entity). The response includes company details and percentile information. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_outsourcing_customers

Get Outsourcing Vendors by Vertical Retrieves a list of outsourcing vendors for the specified vertical (analysis_entity). The response includes vendor details and percentile information. Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_outsourcing_vendors

Get Outsourcing Workloads by Analysis Entity Returns a list of outsourcing workloads and their sizes for a specified analysis entity (vertical/industry). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_outsourcing_workloads

Get Top Metrics Revenue Fetches the top metrics revenue for a specified analysis entity (vertical). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_revenue

Get Top Metrics R&D Spend Returns the current value and change percentage of R&D spend for a given analysis entity (vertical). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_rnd_spend

Get Growing Tech Stack Products Retrieves a list of growing technology stack products for a specified analysis entity (vertical/industry). The response includes product details and percentile statistics. Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_techstack_growing

Get Popular Tech Stack Products Retrieves a list of popular technology stack products for a specified analysis entity (vertical/industry). The response includes product details and percentile statistics. Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }

ecosystem_get_vertical_techstack_popular

Get IT vertical geographic map Returns a list of metropolitan statistical areas (MSAs) with company strength and associated geographic metadata for a specified analysis entity (e.g., an industry vertical like "Automotive"). Request Examples: Automotive vertical example: { "analysis_entity": "Automotive" }

ecosystem_vertical_map_data_it

Get R&D geographic distribution for a vertical Returns a list of metro or regional statistical areas (MSAs) and related geographic metadata where companies in the specified vertical have R&D presence, along with an aggregated company_strength metric per area. The request body requires an analysis_entity such as a vertical name (for example, "Automotive"). Request Examples: Automotive vertical: { "analysis_entity": "Automotive" }

ecosystem_vertical_map_data_r_and_d

Resolve names in a user query to Draup taxonomy values Maps names and phrases in a user query to Draup's canonical taxonomy values, including synonyms, alternate spellings, abbreviations and former names (for example 'Bangalore' resolves to 'Bengaluru Area, India'). Call this first whenever a query mentions a company, location, industry, business function, technology or workload, and pass the returned values exactly as given to other Draup tools, which expect taxonomy values rather than free text. Supported entity types: company, location (cities, metro areas, states, countries), vertical, sub_vertical (industries and sub-industries), business_function, tech_stack, workload. One query can return several entities. If an expected entity is missing from the result, the term was not recognised: retry with just that phrase, or ask the user to clarify. Request Examples: Resolve a location written in a common alternate spelling: { "user_query": "quality of life in bangalore" } Resolve an industry name to its vertical: { "user_query": "key trends of automobile industry" } Resolve a company and a location from one query: { "user_query": "Infosys hiring for data engineers in Pune" }

extract_entities

Get a company's profile overview Returns the profile overview of one company tracked by Draup: name, business description, primary vertical, verticals and sub-verticals, headquarters and HQ street address, employee count, year established, ownership type (Public or Private), vision and mission statements, website and social media links, parent company, and the Draup Opportunity Index score. Use it for a quick factual summary of a company before deeper research. oi_score is Draup's Sales Opportunity Index, a 0-10 score rounded to two decimals that weighs outsourcing size, number of service-provider partners, job postings, globalization, revenue, revenue growth, executive movement and investments equally; it is null for companies without an index. Parent company fields are filled only when the parent is itself a Draup account. Fields without data are null or left out. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.

get_account_details_v3

Get a company's latest financial snapshot Returns the latest financial snapshot of one company tracked by Draup: revenue, IT spend, R&D spend and EBITDA with their year-over-year growth, the financial year they refer to, the ownership type, and private funding details (number of rounds, total raised, date and amount of the last round, latest valuation, latest investor). Use it to size a company or check its recent financial trajectory. The four headline figures are in millions of the company's reporting currency, named in each figure's currency field. avg_conversion_rate is the US-dollar value of one unit of that currency, so multiply by it to get US dollars. A figure's value is null or left out when the figure or the rate is unavailable. Growth fields are percentages versus the previous year. concerned_year is the latest financial year with revenue data. Funding amounts are absolute US-dollar values, not millions, and funding fields are null or left out for companies with no recorded funding rounds, which is typical of public companies. The result holds at most one record. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.

get_account_financials_v3

Find a company's Draup account ID Looks up companies by name or website in Draup's company directory and returns each match with its Draup account id (`id`, the id that account tools such as get_account_details_v3 take), company name (`key`), logo, a 0 to 1 match `score` and whether the match was AI-suggested. Use it first whenever you have a company name or website and need its account id. A search term that looks like a website domain (for example microsoft.com) is matched against every known company web address, including subsidiary and brand domains, and returns those companies with score 1, up to ten. Otherwise the name goes to Draup's company name-matching service, which keeps companies scoring at least 0.5 and returns at most five, highest score first (direct matches before AI-suggested ones at the same score). Send `type` as "universe". Results are empty when nothing matches or the caller's plan does not include company search. Request Examples: Look up by website: { "type": "universe", "search_key": "microsoft.com" } Look up Microsoft: { "type": "universe", "search_key": "microsoft" }

get_account_id

Get the most widely used technology products a company develops Returns up to 20 technology products developed by the company, ranked by how many companies use them. Use it to see which of a software or technology vendor's products are most widely adopted. Each product has its Draup product ID, name, logo URL and accounts_using, the number of companies whose tech stack includes it; products are sorted by accounts_using, highest first. The result is empty when the company develops no tracked product, which is common for companies that are not technology vendors. The endpoint takes no filters. An unknown account ID, or one the caller cannot access, returns an empty response with no result.

get_account_key_solution_offerings_v3

Get a company's strategic priorities Returns the strategic business priorities Draup has identified for one company. Each priority includes its name and narrative description, business function, the functional workloads it involves, the use cases it applies to (with each use case's description and technology areas), its source (earnings call Transcript and/or news Signal) with the fiscal quarter or publication month, up to six of the company's tech stack products whose workloads overlap the priority plus the total number of overlapping products, and up to six service providers with active outsourcing engagements on those workloads. Use it to learn what a company is investing in or trying to achieve, and which tools and vendors are linked to each initiative. {id} is the company's Draup account ID, as returned by get_account_id or get_universe_companies_v3. Narrow the list with response_data (business_functions, workloads, usecases, technology_areas) or with search_key, which matches part of the priority name. Earnings call (Transcript) priorities come first, latest fiscal quarter first, followed by news (Signal) priorities, latest month first, so an older transcript priority is listed before a recent signal priority. Results come 50 per page by default; use pagination.limit and pagination.offset for more. Fields with no value are left out, and is_competitor is always false for API calls. Request Examples: ER&D priorities: { "response_data": { "business_functions": { "or": [ "ER&D" ] } } } Priorities whose name contains 'service', excluding Legal: { "search_key": "service", "response_data": { "business_functions": { "not": [ "Legal" ] } } } Priorities with AI use cases, first 10: { "pagination": { "limit": 10, "offset": 0 }, "response_data": { "technology_areas": { "or": [ "Artificial Intelligence" ] } } }

get_account_priorities_v3

Get the technology products a company uses Returns the software and technology products Draup has detected in one company's tech stack, one row per product: product name and ID, tech stack category, G2 sub-category, developer company, the workloads the product supports, the countries where its use was evidenced (which can include Remote or Hybrid), first and last evidence dates, a usage index (High, Medium or Low; rarely NA) and a detection confidence score from 0 to 1. Products Draup no longer detects are still listed but have no usage index; use last_evidence_date to judge how current a product is. Rows are sorted by G2 sub-category, then product name. Use it to find which tools and vendors a company uses, or whether it uses a given product or vendor. {id} is the company's Draup account ID, as returned by get_account_id or get_universe_companies_v3. Narrow the list with response_data (tech_stack_categories, tech_stack_sub_categories, tech_stack_developer_companies, workloads, countries). Each product has one category and one sub-category, so use only or / not for those two; "and" on them returns an error. Results come 50 per page by default; use pagination.limit and pagination.offset for more, since large companies can have thousands of products. Fields with no value are left out, and is_competitor is always false for API calls. Request Examples: Security software used in the United States, first 20: { "pagination": { "limit": 20, "offset": 0 }, "response_data": { "countries": { "or": [ "United States of America" ] }, "tech_stack_categories": { "or": [ "Security Software" ] } } } Cybersecurity products not developed by Microsoft: { "response_data": { "workloads": { "or": [ "Cybersecurity" ] }, "tech_stack_developer_companies": { "not": [ "Microsoft" ] } } } Products developed by Microsoft: { "response_data": { "tech_stack_developer_companies": { "or": [ "Microsoft" ] } } }

get_account_tech_stack_products_v3

Get a company's most-outsourced workloads Returns the five workloads a company outsources most, ranked by how many of its active outsourcing deals cover each workload. Use it to see where a company relies most on external service providers. {id} is the company's Draup account id, as returned by get_account_id or get_universe_companies_v3. Only deals that name at least one workload, are flagged active, have no end date or one in the future, and have a vendor that is itself a Draup account are counted. Workload names come from Draup's workload taxonomy, such as Customer Service & Support or Software Testing. The deal counts drive the ranking but are not returned, and ties are ordered by workload name in reverse alphabetical order. The list is empty when the company has no qualifying deal. The request body is optional: widget and filters are accepted but do not change the result. Request Examples: Basic request with no filters: { "widget": "top_outsourced_workloads" }

get_account_top_outsourced_workloads

Rank customers by number of matching outsourcing deals Ranks the customers (the companies that outsource) in Draup's outsourcing-deal data by how many deals match the `response_data` filters, most deals first, ties by name. Each row has the customer name (`key`), the deal count (`count`), its Draup account id (`id`) and `logo_url`; only customers that are companies Draup covers appear. `response_data` only narrows which deals are counted; it does not change what is ranked. `hml` gives the 33rd and 67th percentiles of `count` across the returned rows, for high/medium/low banding. Returns the top 50 rows unless `pagination` sets limit and offset. Request Examples: Visualize for customer Microsoft: { "response_data": { "customers": { "OR": [ "Microsoft" ] } } } Visualize for service provider Capgemini and Government & Non profit organisation vertical: { "response_data": { "verticals": { "OR": [ "Government & Non profit organisation" ] }, "service_providers": { "OR": [ "Capgemini" ] } } } Visualize for service provider Accenture: { "response_data": { "service_providers": { "OR": [ "Accenture" ] } } } Visualize for customer list 'RAW comp' with synonym mapping: { "synon_list": { "customer_list": { "raw comp": [ { "id": 79569, "name": "RAW comp" } ] } }, "response_data": { "customer_list": { "OR": [ "RAW comp" ] } } } Visualize for customer list 'Signal Audit Filter Logic' with synonym mapping: { "synon_list": { "customer_list": { "signal audit filter logic": [ { "id": 139889, "name": "Signal Audit Filter Logic" } ] } }, "response_data": { "customer_list": { "OR": [ "Signal Audit Filter Logic" ] } } }

get_deals_customer_v3

Rank service-provider delivery locations by number of matching deals Ranks the metro areas (MSAs) where service providers deliver outsourcing deals, by how many deals match the `response_data` filters, most deals first, ties by name. Each row has the metro area (`key`), the deal count (`count`), `country_code`, `country`, `state_code`, `state`, `latitude` and `longitude`; deals whose delivery location is not a known metro area are left out. Returns at most the top 500 locations, with no paging. `response_data` only narrows which deals are counted; it does not change what is ranked. `hml` gives the 33rd and 67th percentiles of `count` across the returned rows, for high/medium/low banding. Request Examples: Filter by customer Microsoft: { "response_data": { "customers": { "OR": [ "Microsoft" ] } } } Filter by service provider Accenture: { "response_data": { "service_providers": { "OR": [ "Accenture" ] } } } Filter by service provider and vertical: { "response_data": { "verticals": { "OR": [ "Government & Non profit organisation" ] }, "service_providers": { "OR": [ "Capgemini" ] } } } Filter by customer list (RAW comp) with synonyms: { "synon_list": { "customer_list": { "raw comp": [ { "id": 79569, "name": "RAW comp" } ] } }, "response_data": { "customer_list": { "OR": [ "RAW comp" ] } } } Filter by customer list (Signal Audit Filter Logic) with synonyms: { "synon_list": { "customer_list": { "signal audit filter logic": [ { "id": 139889, "name": "Signal Audit Filter Logic" } ] } }, "response_data": { "customer_list": { "OR": [ "Signal Audit Filter Logic" ] } } }

get_deals_service_provider_location_v3

Rank service providers by number of matching outsourcing deals Ranks the service providers (vendors) in Draup's outsourcing-deal data by how many deals match the `response_data` filters, most deals first, ties by name. Each row has the provider name (`key`) and the deal count (`count`), plus its Draup account id (`id`) and `logo_url` when the provider is a company Draup covers. `response_data` only narrows which deals are counted; it does not change what is ranked. `hml` gives the 33rd and 67th percentiles of `count` across the returned rows, for high/medium/low banding. Returns the top 50 rows unless `pagination` sets limit and offset. Request Examples: Visualize by customer Microsoft: { "response_data": { "customers": { "OR": [ "Microsoft" ] } } } Visualize using a named customer list with synonym mapping: { "synon_list": { "customer_list": { "signal audit filter logic": [ { "id": 139889, "name": "Signal Audit Filter Logic" } ] } }, "response_data": { "customer_list": { "OR": [ "Signal Audit Filter Logic" ] } } } Visualize by service provider Accenture: { "response_data": { "service_providers": { "OR": [ "Accenture" ] } } } Visualize by service provider Capgemini and a vertical: { "response_data": { "verticals": { "OR": [ "Government & Non profit organisation" ] }, "service_providers": { "OR": [ "Capgemini" ] } } } Visualize using RAW comp customer list with synonym mapping: { "synon_list": { "customer_list": { "raw comp": [ { "id": 79569, "name": "RAW comp" } ] } }, "response_data": { "customer_list": { "OR": [ "RAW comp" ] } } }

get_deals_service_provider_v3

Rank workloads by number of matching outsourcing deals Ranks the outsourced workloads in Draup's outsourcing-deal data by how many deals match the `response_data` filters, most deals first, ties by name. A deal that lists several workloads counts once for each of them. Each row has the workload name (`key`) and the deal count (`count`). `response_data` only narrows which deals are counted; it does not change what is ranked. `hml` gives the 33rd and 67th percentiles of `count` across the returned rows, for high/medium/low banding. Returns the top 50 rows unless `pagination` sets limit and offset. Request Examples: Filter by customer Microsoft: { "response_data": { "customers": { "OR": [ "Microsoft" ] } } } Filter by service provider Accenture: { "response_data": { "service_providers": { "OR": [ "Accenture" ] } } } Filter by customer list value with synonym mapping (Signal Audit Filter Logic): { "synon_list": { "customer_list": { "signal audit filter logic": [ { "id": 139889, "name": "Signal Audit Filter Logic" } ] } }, "response_data": { "customer_list": { "OR": [ "Signal Audit Filter Logic" ] } } } Filter by customer list value with synonym mapping (RAW comp): { "synon_list": { "customer_list": { "raw comp": [ { "id": 79569, "name": "RAW comp" } ] } }, "response_data": { "customer_list": { "OR": [ "RAW comp" ] } } } Filter by service provider Capgemini and vertical Government & Non profit organisation: { "response_data": { "verticals": { "OR": [ "Government & Non profit organisation" ] }, "service_providers": { "OR": [ "Capgemini" ] } } }

get_deals_workloads_v3

Get Demographics Data Details Retrieves demographic data details for the specified filters. Filters can include job location and job country. The response includes latitude, longitude, country code, country, and availability status. Request Examples: Filter by job country: { "filters": { "job_country": [ "United Kingdom" ] } } Filter by job location: { "filters": { "job_location": [ "Greater New York City Area, United States" ] } } Filter by multiple job locations and country: { "filters": { "job_country": [ "United States of America" ], "job_location": [ "Abilene, Texas Area, United States", "Amarillo, Texas Area, United States", "Austin, Texas Area, United States", "Brownsville, Texas Area, United States", "Houston, Texas Area, United States", "Laredo, Texas Area, United States", "McAllen, Texas Area, United States" ] } }

get_demographics_data_details

Get Employers Data Fetches employers data based on provided filters such as location, vertical, and sub-verticals. Returns a list of employers with their account details and percentile information. Request Examples: Location - India: { "widget": "employers_v2", "location": "India", "is_country": "true", "analysis_type": "location" } Vertical - Automotive: { "widget": "employers_v2", "vertical": "Automotive", "analysis_type": "vertical" } Location - Capital District, Colombia: { "widget": "employers_v2", "location": "Capital District, Colombia", "analysis_type": "location" } Location with vertical filter: { "widget": "employers_v2", "filters": { "verticals": [ "media & entertainment" ] }, "location": "Greater Los Angeles Area, United States", "analysis_type": "location" } Location with vertical and sub-vertical filters: { "widget": "employers_v2", "filters": { "verticals": [ "media & entertainment" ], "sub_verticals": [ "film & music" ] }, "location": "Greater Los Angeles Area, United States", "analysis_type": "location" }

get_ecosystem_employers_data

Get Globalization Summary Returns the globalization summary of the company given by `id` for one business function, or site class: current headcount at its sites, the number of site locations and its globalization index score with the change from the previous record. Use it to size an account's footprint for a given function. A site class is required, chosen from IT, R&D, Sales & Marketing, Customer Support & Service, Legal, Procurement and Finance & Accounting, and an option widens headcount and locations to all of the account's sites. Results can also be limited to sites in one city, state or country. Headcount is summed across the matching sites, and the index score is rounded to two decimals and left empty when there is no index data. With a location limit the index is left out, IT and R&D return headcount while other functions return a headcount range, and the location count is kept only when the location is not a city.

get_globalization_summary

Get Location Demographics Data Fetches demographic data for a given location. Optionally, specify if the location is a country using the 'is_country' parameter.

get_location_demographics_data

Get the latest company news signals Returns a page of company news signals captured by Draup. Each signal carries its headline, source, link, image, highlights, capture date, categories and locations, the companies it mentions with logos, your helpful vote, a new flag and the IDs of your saved lists that contain it. Signals can be narrowed by company name or Draup company ID, industry vertical, signal category, signal location, your saved lists and a capture-date range. They come newest first, 10 per page by default, and without a page setting every match is returned. Popularity sorting ranks up to 1,000 of the newest matches by story coverage minus two points per day of age, 20 per page by default. Highlights are an AI summary when available, else snippets. The new flag marks signals added since your previous visit. Only companies Draup covers appear, and no match returns an empty list. For Sales trial accounts, only companies on the trial list appear. Allowed keys: account_ids, accounts, categories, company_ids, locations, projects, rephrased_query, verticals. Request Examples: Signals about companies in India: { "pagination": { "limit": 20, "offset": 0 }, "response_data": { "locations": { "or": [ "India" ] } } } Layoff signals, most popular first: { "sort_by": "popularity", "pagination": { "limit": 20, "offset": 0 }, "response_data": { "categories": { "or": [ "Layoff" ] } } } Two companies, two verticals and three categories: { "sort_by": "popularity", "pagination": { "limit": 20, "offset": 0 }, "response_data": { "accounts": { "or": [ "Microsoft", "Google Inc." ] }, "verticals": { "or": [ "Enterprise Software", "Banking & Financial Services" ] }, "categories": { "or": [ "Center Setup and Expansion", "Deals and Partnerships", "Executive Movement" ] } } } Microsoft center setup and expansion signals: { "pagination": { "limit": 20, "offset": 0 }, "response_data": { "accounts": { "or": [ "Microsoft" ] }, "categories": { "or": [ "Center Setup and Expansion" ] } } } Any-of companies with an exclusion, verticals and Layoff: { "sort_by": "popularity", "pagination": { "limit": 20, "offset": 0 }, "response_data": { "accounts": { "or": [ "Microsoft", "Tesla, Inc." ], "not": [ "OpenAI" ] }, "verticals": { "or": [ "Automotive", "Enterprise Software", "Banking & Financial Services" ] }, "categories": { "or": [ "Layoff" ] } } }

get_news_feed_v3

Get outsourcing summary for an account Returns headline outsourcing metrics for an account's active engagements with service providers and vendors. `outsourcing_size` is the summed maximum headcount across those engagements, `active_service_provider_partners` the number of distinct vendors, and `workflows_count` the number of active engagements. A `footnote` describing how the metrics are defined accompanies the data. Figures cover accounts visible in the caller's product. Optional `response_data` filters narrow the engagements: `workloads`, `business_functions`, `vendor_locations`, `vendor_accounts` and `relationship_type`, each with or/and/not operators; any other key returns HTTP 400. When a `business_functions` filter is applied, `outsourcing_size` is returned as null, while the partner and engagement counts still reflect the filter. Request Examples: Filter outsourcing summary by vendor location: { "response_data": { "vendor_locations": { "or": [ "India" ] } } } Filter outsourcing summary by a single business function: { "response_data": { "business_functions": { "or": [ "Sales & Marketing" ] } } } Include one business function and exclude another: { "response_data": { "business_functions": { "or": [ "Sales & Marketing" ], "not": [ "R&D" ] } } }

get_outsourcing_summary_v3

List the workloads in a company's strategic priorities Returns the functional workloads that appear in a company's strategic priorities, each with the number of priorities that involve it, sorted by that count (highest first) and then by name. Use it to see which work areas a company's priorities concentrate on, or to get exact workload names for the workloads filter of get_account_priorities_v3. {id} is the company's Draup account ID, as returned by get_account_id or get_universe_companies_v3. Send only id to count every priority; response_data limits the priorities counted by business_functions, usecases, technology_areas or workloads. Workloads you list under workloads (or, and, not) are left out of the result. Their or / and values restrict the priorities counted, so the list shows the workloads that occur alongside them, and their not values drop the priorities that involve those workloads. If applied_filters is non-empty, it replaces the workloads values as the list of names left out of the result. All matching workloads are returned in one response, with no paging. The result is empty when no priority matches. Request Examples: Workloads in ER&D priorities: { "response_data": { "business_functions": { "or": [ "ER&D" ] } } } Workloads that occur alongside Artificial Intelligence & Data Science: { "response_data": { "workloads": { "or": [ "Artificial Intelligence & Data Science" ] } } }

get_priorities_top_workloads_v3