> For the complete documentation index, see [llms.txt](https://docs.coresignal.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.coresignal.com/release-notes/august-2026.md).

# August 2026

{% updates format="full" %}
{% update date="2026-08-01" %}

## Base Company data: adding a new field

We are adding the `affiliated_company_id` field to a new Base Company data schema and backfilling the values.

| Data field                                 | Description                                                                | Data type |
| ------------------------------------------ | -------------------------------------------------------------------------- | --------- |
| `affiliated_pages[].affiliated_company_id` | Identification key relating to the company table for the affiliate company | Integer   |
| {% endupdate %}                            |                                                                            |           |

{% update date="2026-08-01" %}

## Multi-source Employee data: adding new fields

We are adding two new fields to the `experience` and `education` arrays to identify each entry.

| Data field        | Description                                                | Data type |
| ----------------- | ---------------------------------------------------------- | --------- |
| `experience[].id` | Profile hash ID uniquely identifying each experience entry | String    |
| `education[].id`  | Profile hash ID uniquely identifying each education entry  | String    |
| {% endupdate %}   |                                                            |           |

{% update date="2026-08-10" %}

## Base Jobs data: adding new fields

Adding `status_changed_at`, an array of structs that records when a job posting's status last changed (active, inactive, or deleted). This field supports job-duration and hiring-trend analytics.

| Data field                       | Description                                                                   | Data type        |
| -------------------------------- | ----------------------------------------------------------------------------- | ---------------- |
| `status_changed_at`              | Records when and how a job posting's status last changed                      | Array of structs |
| `status_changed_at[].status`     | Job status at the time of the change. Values: `active`, `inactive`, `deleted` | String           |
| `status_changed_at[].changed_at` | Timestamp of the status change                                                | Timestamp        |
| {% endupdate %}                  |                                                                               |                  |

{% update date="2026-08-18" %}

## Multi-source Jobs data: breaking changes

Breaking changes to Multi-source Jobs data: `employment_type` is changed to  `array<string>` with normalized values (`PER_DIEM` → `Temporary`, unmapped → `Other`), and `salary[].currency` now uses ISO 4217 codes instead of symbols.

#### Data type change

`employment_type` data type is changing to an array – update your flows accordingly.

| Data field        | Old data type | New data type    |
| ----------------- | ------------- | ---------------- |
| `employment_type` | String        | Array of strings |

#### Value normalization

Two data fields `employment_type` and `salary[].currency` values are now normalized.

**`employment_type`**

**Before:** A single value, selected via priority coalesce across contributing sources.

**After:** A distinct array of values aggregated from all contributing sources.

Value mapping changes:

| Before                    | After       |
| ------------------------- | ----------- |
| `PER_DIEM`                | `Temporary` |
| Missing / unmapped values | `Other`     |

**`salary[].currency`**

Data quality update to `salary[].currency` that can disrupt symbol-matching flows.

| Before                                                                    | After                                              |
| ------------------------------------------------------------------------- | -------------------------------------------------- |
| Raw currency symbol for Glassdoor-sourced entries (e.g. `$`, `£`, `k €`). | ISO 4217 currency code (e.g. `USD`, `GBP`, `EUR`). |
| {% endupdate %}                                                           |                                                    |

{% update date="2026-08-18" %}

## Glassdoor Jobs data: changing field values

`salary.currency` data field now has value normalization, where raw currency symbols are replaced with ISO 4217 codes.

| Before                             | After                                    |
| ---------------------------------- | ---------------------------------------- |
| Raw symbols (e.g. `$`, `£`, `k €`) | ISO 4217 code (e.g. `USD`, `GBP`, `EUR`) |
| {% endupdate %}                    |                                          |

{% update date="2026-08-18" %}

## Indeed Jobs data: field value normalization

Indeed Jobs data field `job_type` values are now normalized. Filters using raw source codes (e.g. `job_type = 'FULL_TIME'`) will stop matching, so you need to update your flows to match canonical enum values.

| Before                                                                                  | After                                                                                                                 |
| --------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------- |
| Raw source codes (e.g. `FULL_TIME`, schema.org variants, multilingual values) or absent | Canonical enum value (`Full-time`, `Part-time`, `Contract`, `Temporary`, `Internship`, `Volunteer`)+ `Other` fallback |
| Unmapped values                                                                         | `Other`                                                                                                               |
| {% endupdate %}                                                                         |                                                                                                                       |

{% update date="2026-08-14" %}

## Webhooks: Updated subscription limit

You can now set up to **500 webhook subscriptions** per account, each allowing a maximum of 300,000 IDs. Any attempts to exceed this limit will be rejected.
{% endupdate %}

{% update date="2026-08-11" %}

## Multi-source Employee API: adding new fields

**Adding new fields**&#x20;

Adding new fields to surface academic background, career trajectory, and activity signals.

<table data-search="false"><thead><tr><th>Data field</th><th>Description</th><th>Data type</th></tr></thead><tbody><tr><td><code>institution_ranking_score</code></td><td>Highest QS university ranking score across the employee's education institutions, matched by normalized institution name. <code>null</code> if no institution matches</td><td>Double</td></tr><tr><td><code>education[].institution_website</code></td><td>Institution's website URL</td><td>String</td></tr><tr><td><code>months_in_management</code></td><td>Total months spent in management-level roles. Calculated as the union of these positions, so overlapping roles aren't counted twice</td><td>Long</td></tr><tr><td><code>post_frequency_yearly</code></td><td>Count of professional network posts over the past 12 months</td><td>Double</td></tr><tr><td><code>posting_recency</code></td><td>Date of the employee's most recent post</td><td>Date</td></tr><tr><td><code>engagement_per_post</code></td><td>Average engagement (reactions and comments) per post</td><td>Double</td></tr><tr><td><code>influence_score</code></td><td>Composite 0–100 social-influence score: a weighted, log-scaled blend of post frequency (0.2), engagement per post (0.5), and follower count (0.3), each capped at a fixed, precomputed 99th-percentile threshold. Defaults to <code>0.0</code></td><td>Double</td></tr><tr><td><code>activity[].created_at</code></td><td>Creation timestamp of the activity item</td><td>Timestamp</td></tr><tr><td><code>activity[].updated_at</code></td><td>Last-updated timestamp of the activity item</td><td>Timestamp</td></tr><tr><td><code>processed_at</code></td><td>Exposes when data was processed on our side (reparsing, reloads, data quality fixes). Aligned to the delivery date – one day ahead of <code>updated_at</code></td><td>Timestamp</td></tr></tbody></table>

We are adding two new fields to the `experience` and `education` arrays to identify each entry.

| Data field                   | Description                                               | Data type |
| ---------------------------- | --------------------------------------------------------- | --------- |
| `experience[].id`            | Profile hash ID uniquely identifies each experience entry | String    |
| `education[].id`             | Profile hash ID uniquely identifies each education entry  | String    |
| `education[].institution_id` | Internal institution identifier for education records     | Long      |

**Adding a `tenure_stats` struct**

A new nested struct capturing per-company tenure statistics in months, derived from the employee's company-linked experience.

| Data field                       | Description                                                                                                                                                                                                                                              | Data type |
| -------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- |
| `tenure_stats`                   | Per-company tenure statistics in months, with concurrent roles at the same company counted once. It presents raw data without plausibility checks, so some values might be unrealistic. `null` if the employee has no datable, company-linked experience | Struct    |
| `tenure_stats.avg_tenure_months` | Average total tenure per company                                                                                                                                                                                                                         | Double    |
| `tenure_stats.median_tenure`     | Median total tenure per company                                                                                                                                                                                                                          | Double    |
| `tenure_stats.current_tenure`    | Tenure at the current (active) position. `null` if not currently employed                                                                                                                                                                                | Double    |
| `tenure_stats.longest_tenure`    | Longest total tenure at a single company                                                                                                                                                                                                                 | Double    |

**Adding a `internal_promotion_rate` struct**

A new nested struct quantifying internal career progression. Promotions are inferred from position-title changes within the same company, ordered by start date.

| Data field                                         | Description                                                                                                                                                                                      | Data type |
| -------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------- |
| `internal_promotion_rate`                          | Internal promotion metrics, derived from position-title changes within the same company, ordered by start date, counting only changes where the new role starts strictly after the previous role | Struct    |
| `internal_promotion_rate.promotion_count`          | Count of internal title changes (promotions). `0` if none                                                                                                                                        | Integer   |
| `internal_promotion_rate.avg_months_per_promotion` | Average months between consecutive promotions. `null` with fewer than two promotions                                                                                                             | Double    |
| `internal_promotion_rate.recently_promoted`        | True if a promotion occurred within the last 3 months                                                                                                                                            | Boolean   |
| {% endupdate %}                                    |                                                                                                                                                                                                  |           |

{% update date="2026-08-11" %}

## Multi-source Company API: adding new fields

Adding new fields to improve the granularity of HQ address data and to expose a full structured list of all company locations.

<table data-search="false"><thead><tr><th>Data field</th><th>Description</th><th>Data type</th></tr></thead><tbody><tr><td><code>hq_latitude</code></td><td>Geographic latitude coordinate of the company's headquarters</td><td>Double</td></tr><tr><td><code>hq_longitude</code></td><td>Geographic longitude coordinate of the company's headquarters</td><td>Double</td></tr><tr><td><code>hq_apartment</code></td><td>Apartment number or unit identifier for the HQ address, when applicable</td><td>String</td></tr><tr><td><code>hq_suite</code></td><td>Suite number or office designator for the HQ address, when applicable</td><td>String</td></tr><tr><td><code>company_locations_full[].city</code></td><td>City name of the company location</td><td>String</td></tr><tr><td><code>company_locations_full[].state</code></td><td>State of the company location</td><td>String</td></tr><tr><td><code>company_locations_full[].street</code></td><td>Street address of the company location</td><td>String</td></tr><tr><td><code>company_locations_full[].zip_code</code></td><td>Postal or ZIP code of the company location</td><td>String</td></tr><tr><td><code>company_locations_full[].latitude</code></td><td>Geographic latitude coordinate of the company location</td><td>Double</td></tr><tr><td><code>company_locations_full[].longitude</code></td><td>Geographic longitude coordinate of the company location</td><td>Double</td></tr></tbody></table>

**Adding `avg_tenure_by_seniority_months` struct**

We are adding `avg_tenure_by_seniority_months` struct which shows the average tenure in months for the company’s active employees, grouped by management level/seniority.

<table data-search="false"><thead><tr><th>Data field</th><th>Description</th><th>Data type</th></tr></thead><tbody><tr><td><code>avg_tenure_by_seniority_months</code> </td><td>Average tenure in months for active employees, grouped by management level/seniority</td><td>Struct</td></tr><tr><td><code>avg_tenure_by_seniority_months.owner</code></td><td>Average tenure in months for active employees in the owner seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.founder</code></td><td>Average tenure in months for active employees in the founder seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.clevel</code></td><td>Average tenure in months for active employees in the C-level seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.partner</code> </td><td>Average tenure in months for active employees in the partner seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.vp</code> </td><td>Average tenure in months for active employees in the VP seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.head</code></td><td>Average tenure in months for active employees in the head seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.director</code></td><td>Average tenure in months for active employees in the director seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.manager</code></td><td>Average tenure in months for active employees in the manager seniority bucket </td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.senior</code></td><td>Average tenure in months for active employees in the senior seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.intern</code></td><td>Average tenure in months for active employees in the intern seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.specialist</code> </td><td>Average tenure in months for active employees in the specialist seniority bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_seniority_months.other_management</code></td><td>Average tenure in months for active employees in the other management seniority bucket</td><td>Float</td></tr></tbody></table>

**Adding `avg_tenure_by_department_months` struct**

We are adding `avg_tenure_by_department_months` struct which shows the average tenure in months for the company’s active employees, grouped by department.

<table data-search="false"><thead><tr><th>Data field</th><th>Description</th><th>Data type</th></tr></thead><tbody><tr><td><code>avg_tenure_by_department_months</code></td><td>Average tenure in months for active employees, grouped by department</td><td>Struct</td></tr><tr><td><code>avg_tenure_by_department_months.medical</code></td><td>Average tenure in months for active employees in the medical department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.sales</code></td><td>Average tenure in months for active employees in the sales department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.hr</code></td><td>Average tenure in months for active employees in the HR department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.legal</code></td><td>Average tenure in months for active employees in the legal department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.marketing</code></td><td>Average tenure in months for active employees in the marketing department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.finance</code></td><td>Average tenure in months for active employees in the finance department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.technical</code></td><td>Average tenure in months for active employees in the technical department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.consulting</code> </td><td>Average tenure in months for active employees in the consulting department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.operations</code></td><td>Average tenure in months for active employees in the operations department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.product</code></td><td>Average tenure in months for active employees in the product department bucket </td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.general_management</code></td><td>Average tenure in months for active employees in the general management department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.administrative</code></td><td>Average tenure in months for active employees in the administrative department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.customer_service</code></td><td>Average tenure in months for active employees in the customer service department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.project_management</code></td><td>Average tenure in months for active employees in the project management department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.design</code></td><td>Average tenure in months for active employees in the design department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.research</code></td><td>Average tenure in months for active employees in the research department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.trades</code></td><td>Average tenure in months for active employees in the trades department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.real_estate</code></td><td>Average tenure in months for active employees in the real estate department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.education</code></td><td>Average tenure in months for active employees in the education department bucket</td><td>Float</td></tr><tr><td><code>avg_tenure_by_department_months.other_department</code></td><td>Average tenure in months for active employees in the other department bucket</td><td>Float</td></tr></tbody></table>
{% endupdate %}

{% update date="2026-08-19" %}

## Agentic Search API updates

The response shape for Agentic Search API `/fast` and `/reasoning` endpoints are changing from a static preview to a dynamic, query-aware response. Also, we are decreasing the maximum count of returned results in `"return_data":true` mode and removing `"limit"` parameter.

### **What is changing**

* **Updating structure of the response**: Data fields are now displayed in two types: Fixed fields, Dynamic 1 (root fields) and Dynamic 2 (nested fields). Any integration relying on a fixed, predictable field set beyond fixed fields will need to be updated to handle a variable response shape determined by query parameters.

  * **Fixed fields:** A fixed, small set of identifying fields is always returned for every request, regardless of the query.

  | **Company**  | <p><code>id</code>, <br><code>company\_name</code>, <code>professional\_network\_url</code>, <code>\_score</code></p>                                                                                                                        |
  | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
  | **Employee** | <p><code>id</code>, <br><code>full\_name</code>, <code>professional\_network\_url</code>, <code>active\_experience\_title</code>, <code>active\_experience\_company\_id</code>, <br><code>company\_name</code>, <br><code>\_score</code></p> |
  | **Jobs**     | <p><code>id</code>, <br><code>company\_name</code>, <br><code>title</code>, <br><code>\_score</code></p>                                                                                                                                     |

  * **Dynamic fields (query-aware):** In addition to the fixed set of fields, the additional returned fields now vary based on the prompt. They may include root-level fields and matched nested fields, such as specific experiences, funding rounds, or job sources that align with the prompt. Any integration that relies on a static, predictable field set must be updated to handle a response shape that varies with the prompt.
* **Query transparency:** The response now always includes the underlying Elasticsearch DSL query that produced the results.
* **`/fast` endpoint response change**: the response format `/fast` endpoint returns is changing:

| Mode                  | Old format                        | New format                                   |
| --------------------- | --------------------------------- | -------------------------------------------- |
| `"return_data":false` | `{"query": {...}, "sort": [...]}` | `{"query": {"query": {...}, "sort": [...]}}` |
| `"return_data":true`  | `[{...}]`                         | `{"query": {...}, "data": [{...}]}`          |

* **Results count:** `"return_data":true` mode now returns up to 20 results. Pricing logic remains the same.
* **Removing `"limit"` parameter**: `"limit"` parameter is removed because the maximum result count is 20, and pricing isn't affected by it.
  {% endupdate %}

{% update date="2026-08-19" %}

## Search Preview: increasing results count

Search Preview endpoints now support pagination up to **50 pages**, giving access to up to **1,000 results** per search.

What stays the same:

* Each page still returns 20 results
* Pagination is accessed the same way, via the `page` query parameter
* **Pricing is unchanged**: each additional page consumed still costs the same amount of credits as before
  {% endupdate %}
  {% endupdates %}


---

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