Data as of Nov 8, 2026

Professional retention rates

Name: ElevenFlo Professional retention rates
Creator: ElevenFlo
License: https://elevenflo.com/terms-of-use

Stated rate tiers of professional engagements, banded by seniority, for rate comparisons across firms, cases and years.

Questions to ask your AI

Once ElevenFlo is connected, paste one into Claude or ChatGPT and replace any bracketed text. Questions that query a dataset need Pro.

1.
What partner hourly rates did Kirkland & Ellis state in its retention applications each year since 2020?
2.
How do approved partner rates for debtor's counsel compare across firms in cases filed this year?
3.
What hourly rates did [firm] request for associates in [case name], and did the order approve them?

What the dataset covers

The served population is what the MCP tools return. The checked population is what the latest quality checks measured.

One row is: one stated rate tier of a served professional engagement
Served population: —
Checked population: —
Rows served: 44,538
Data as of: Nov 8, 2026
Freshness: Fresh

Read before relying on a row

Route-tag coverage for recent (2026) filings is incomplete and varies by professional role. An empty result means no structured row exists, not that no retention application was filed; fall back to docket browsing or content search before asserting absence.
A requested rate is not an approved one, and only single-level hourly tiers carry a seniority band.

Checked every day

Automated checks measure the dataset against its filings. Each aspect shows its weakest result.

Checked Nov 7, 2026

Scope: Every served engagement of any filing year; candidate sourcing from 2015-01-01

CoverageBelow target
How much of the checked population the dataset holds.
FreshnessPassing
How recently the dataset was updated and how far it trails its sources.
AccuracyPassing
Checks for known data defects. A pass does not verify every value against its filing.

What each row holds

A search returns the default fields unless it names others. Every field below can be requested.

Returned by default

id: Engagement and tier position in the current projection; positions can shift when the projection changes.
case_id: Canonical case identifier.
party_name: Retained organization, person, or roster program name, as filed.
professional_role: Professional role of the engagement.
retained_by: Party on whose behalf the professional is retained.
label: Tier label as filed, such as Partners or Senior Associates.

Example tool calls

The arguments a connected AI sends to the named ElevenFlo MCP tool. Each example validates against the public field policy.

aggregate_structured_data

{
  "dataset": "professional-retention-rates",
  "where": [
    {
      "field": "party_name",
      "op": "contains",
      "value": "Kirkland"
    },
    {
      "field": "band",
      "op": "eq",
      "value": "partner"
    },
    {
      "field": "period",
      "op": "eq",
      "value": "hour"
    },
    {
      "field": "currency_code",
      "op": "eq",
      "value": "USD"
    }
  ],
  "group_by": [
    {
      "field": "effective_date",
      "bucket": "year"
    }
  ],
  "metrics": [
    {
      "name": "median_low",
      "fn": "p50",
      "field": "lower_amount"
    },
    {
      "name": "median_high",
      "fn": "p50",
      "field": "upper_amount"
    },
    {
      "name": "engagements",
      "fn": "count_distinct",
      "field": "engagement_public_id"
    }
  ]
}

Query Professional retention rates with your AI

Searching and analyzing datasets takes Pro, at $99 per seat per month with 10,000 MCP credits a month. Free accounts can connect, read each dataset’s fields and caveats, and use 200 credits a month on case and filing research. See pricing