DatriseAI-first ETL

Source connector

Clio connector

Clio integration for databases, warehouses and BI tools

Legal practice management for matters, time, and billing. Datrise captures Clio entities such as matters, contacts, time entries, bills, documents and calendar events, then lands normalized and typed models for warehouse reporting, attribution, and AI workflows.

The Clio Manage API v4 authenticates with OAuth 2.0, incremental runs key on updated_since, and Clio caps calls at 50 requests per minute per access token during peak hours (US/CA 04:00-19:00 PT, EU 07:00-22:00 GMT, AU 06:00-21:00 AET, Mon-Fri); limits are raised off-peak by an unpublished, region-dependent amount.

Of the 6 objects, 5 sync as upserts keyed on the primary key and 1 as append-only streams, so each incremental run moves only what changed since the last watermark. Every object lands in its own table (for example `clio_matters`) with a schema derived from the Clio API rather than a flattened CSV, in any of the 43 supported destinations.

Datrise is in early access: pick a destination below to open the Clio pipeline page, and join the waitlist to get the Clio connector (CRM) with guided onboarding.

Incremental syncSchema-aware mapping43 destinations available

What Clio data Datrise extracts

Each object lands in its own typed table. Sync mode is derived from the object: history-style objects append, everything else upserts.

ObjectLanding tableSync mode
mattersclio_mattersUpsert by primary key, incremental on updated-at
contactsclio_contactsUpsert by primary key, incremental on updated-at
time entriesclio_time_entriesUpsert by primary key, incremental on updated-at
billsclio_billsUpsert by primary key, incremental on updated-at
documentsclio_documentsUpsert by primary key, incremental on updated-at
calendar eventsclio_calendar_eventsAppend-only, incremental by timestamp

Clio API: setup facts for the connector

Verified against the vendor documentation on 2026-09-02. Unknown values are left blank rather than guessed.

APIClio Manage API v4
AuthenticationOAuth 2.0 — Clio implements standard OAuth 2.0 authorization-code grant through a registered app; tokens are scoped per model (e.g. a matters scope, a webhooks scope).
Paginationcursor — Cursor pagination is the default (order=id(asc), no offset) and follows `meta.paging.next` until absent; the alternative offset method is capped at 10,000 total records (50 pages) and index actions return 200 results per page unless otherwise noted.
Rate limit50 requests per minute per access token during peak hours (US/CA 04:00-19:00 PT, EU 07:00-22:00 GMT, AU 06:00-21:00 AET, Mon-Fri); limits are raised off-peak by an unpublished, region-dependent amount
Incremental cursorupdated_since — List endpoints accept a documented `updated_since` (and `created_since`) standard query filter for delta syncs, e.g. `matters.json?updated_since=<ISO8601>`.
WebhooksYes — Clio Webhooks (created/updated/deleted events per model, HTTPS callback only)
Bulk exportNo
Deletes detectableYes — no polling-based delete flag on core objects (matters/contacts); deletes are only observable in near-real time via a `deleted` event webhook subscription

Official API reference

What bites when replicating Clio

  • Peak-hour rate limiting is 50 requests/minute per access token and returns `429 Too Many Requests` with a `Retry-After` header; the off-peak increase is real but its size is unpublished and varies by region.
  • Offset pagination silently stops working past 10,000 records (50 pages of 200): large objects need cursor pagination (`order=id(asc)`, no `offset` param) with no upper bound instead.
  • The `fields` parameter is required to get anything beyond a minimal default field set on every index/show response, which is easy to miss when first wiring up an endpoint.
  • There is no `is_deleted` filter on core list endpoints (matters, contacts); detecting deletes requires a standing `deleted`-event webhook subscription rather than polling.

Compare this against every other documented API

Popular destinations for Clio

Choose a destination below to open the ready pipeline page.

  • A
    Airtable

    Relational spreadsheet destination for ops and go-to-market teams.

    View pipeline
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    Amazon Athena

    Serverless SQL over S3 data lake tables.

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    Amazon DynamoDB

    Serverless key-value and document store on AWS.

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  • A
    Amazon QuickSight

    AWS serverless BI with SPICE and embedded analytics.

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  • A
    Amazon Redshift

    AWS petabyte-scale warehouse with Spectrum.

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  • A
    Amazon S3 Data Lake

    Object storage landing zone for parquet and snapshots.

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  • A
    Apache Superset

    Open-source BI for SQL exploration, charts, and dashboard publishing.

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  • A
    Azure Data Lake Storage

    ADLS Gen2 object storage for analytics workloads.

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    Azure Synapse

    Microsoft analytics workspace with SQL pools.

    View pipeline

Clio connector FAQ

What Clio data does the connector extract?
6 objects: matters, contacts, time entries, bills, documents and calendar events. Each lands in its own table with types preserved; history-style objects (1: calendar events) load as append-only streams.
Is the Clio integration incremental?
Yes. After the initial full load, every run reads only records changed since the last watermark (updated-at or event timestamp) and applies an upsert or an append depending on the object.
Where can I load Clio data?
Into 43 destinations: relational databases, cloud warehouses, data lakes, spreadsheets and BI tools. Each Clio → destination pair has its own page with the object-to-table mapping.

Related CRM sources

Other sources in the same category, each with its own connector page.

Early access

Launch your Clio pipeline with guided onboarding

Join the waitlist to get priority access for Clio integrations with guided setup, schema-aware mapping, and production-grade incremental sync.