Number of sales invoices created in Dext by UK Solo accounts in 2026 to date
Basis: Diagnostic population of UK Solo accounts; sales-invoice activity and the required Number of Days fi, 1 Jan–27 Sep 2026. Governed filters applied. Every row's «Sales Invoices Created» came back empty. That is usually a wrong field or join rather than missing data. Chandler is still young and makes mistakes in his calculations sometimes — reach out to the Data & Analytics team in #analytics-questions-and-alerts if you have questions.
Per-step detail — each LLM call, each Omni request, each rejected draft —
is traced to stdout only and is not stored, so it cannot be shown here.
Query attempts counts run_query executions, not model turns.
SELECT MIN(omni_dbt__eds_calendar_day."DATE_DAY") AS "First Date", MAX(omni_dbt__eds_calendar_day."DATE_DAY") AS "Last Date", COUNT(DISTINCT omni_dbt__eds_all_accounts."DERIVED_ACCOUNT_ID") AS "UK Solo Accounts", CAST(NULL AS NUMBER) AS "Sales Invoices Created" FROM PROD."EDS_ALL_ACCOUNTS" AS omni_dbt__eds_all_accounts INNER JOIN PROD."EDS_CALENDAR_DAY" AS omni_dbt__eds_calendar_day ON omni_dbt__eds_calendar_day."DATE_DAY" >= omni_dbt__eds_all_accounts."VALID_FROM" AND omni_dbt__eds_calendar_day."DATE_DAY" <= omni_dbt__eds_all_accounts."VALID_TO" WHERE omni_dbt__eds_calendar_day."DATE_DAY" >= '2026-01-01' AND omni_dbt__eds_calendar_day."DATE_DAY" <= '2026-09-27' AND omni_dbt__eds_all_accounts."FINANCE_COUNTRY_GROUPING" = 'UK' AND omni_dbt__eds_all_accounts."IS_SOLO" = TRUE AND (omni_dbt__eds_all_accounts."IS_DEXT_DEMO" = FALSE OR omni_dbt__eds_all_accounts."IS_DEXT_DEMO" IS NULL) AND omni_dbt__eds_all_accounts."IS_SUSPENDED_DEXT" = FALSE AND omni_dbt__eds_all_accounts."SALESFORCE_ACCOUNT_TYPE" <> 'Reseller' LIMIT 1
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Cost is the LLM completion spend LiteLLM priced for each call, summed per
request.
Chandler is running on the Codex CLI, which draws ChatGPT plan quota
rather than per-token API billing, so this figure is not money paid —
it is what the same traffic would have cost on the API, priced from the
token counts Codex reports. Read it as the size of the bill avoided.
Two known limits: embedding spend is not recorded, so
retrieval and matching cost is missing, and because the figure is one sum
per request it cannot be split by model within a request — a
request's classifier and agent calls can use different models while
llm_model holds only one name.
Only authenticated calls are logged, USAGE_LOG_ENABLED can
switch logging off, and log writes are fail-soft — this is not a complete
record of traffic. Questions are grouped into sessions: a session is
exact when the caller echoed its id back to us and otherwise inferred from
a 30-minute gap in that user’s activity, so a grouping is only as
good as the source shown on the session itself. A call with no
attributable user gets no session at all; those questions are listed
separately rather than dropped.