Sensient Technologies Corp: contract revenue excluding tax
Sensient Technologies contract revenue excluding tax: $1.61 billion for the year ending 2025-12-31, up 3.5% on the year. 10 values since 2016 from SEC filings.
All Sensient Technologies Corp financial histories
At a glance
Sensient Technologies reported contract revenue excluding tax of $1.61 billion for the year ending 2025-12-31, up 3.5% from $1.56 billion a year earlier. From 2016 to 2025 it grew at a compound 1.7% a year, from $1.38 billion to $1.61 billion. Across the last five reported years it ranged from $1.38 billion (2021-12-31) to $1.61 billion (2025-12-31).
Computed from the values in the table below, in USD; each links to the filing it came from.
What this measure means
Revenue from customer contracts excluding assessed taxes under this specific taxonomy concept. It is not automatically comparable to older revenue tags.
Exact concept: us-gaap:RevenueFromContractWithCustomerExcludingAssessedTax. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2016-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2025-01-01 | 2025-12-31 | 1,612,111,000 | USD | 2026-02-13 | 10-K · 0001140361-26-005311 SEC |
| 2024-01-01 | 2024-12-31 | 1,557,228,000 | USD | 2026-02-13 | 10-K · 0001140361-26-005311 SEC |
| 2023-01-01 | 2023-12-31 | 1,456,450,000 | USD | 2026-02-13 | 10-K · 0001140361-26-005311 SEC |
| 2022-01-01 | 2022-12-31 | 1,437,039,000 | USD | 2025-02-19 | 10-K · 0001140361-25-005084 SEC |
| 2021-01-01 | 2021-12-31 | 1,380,264,000 | USD | 2024-02-22 | 10-K · 0001140361-24-008963 SEC |
| 2020-01-01 | 2020-12-31 | 1,332,001,000 | USD | 2023-02-17 | 10-K · 0001140361-23-007579 SEC |
| 2019-01-01 | 2019-12-31 | 1,322,934,000 | USD | 2022-02-18 | 10-K · 0001140361-22-006156 SEC |
| 2018-01-01 | 2018-12-31 | 1,386,815,000 | USD | 2021-02-22 | 10-K · 0001140361-21-005623 SEC |
| 2017-01-01 | 2017-12-31 | 1,362,265,000 | USD | 2020-02-21 | 10-K · 0001140361-20-003752 SEC |
| 2016-01-01 | 2016-12-31 | 1,383,210,000 | USD | 2019-02-25 | 10-K/A · 0001140361-19-003714 SEC |
Related Sensient Technologies Corp histories
Inspect the source
- Entity
- Sensient Technologies Corp / CIK 0000310142
- Captured
- SEC response SHA-256
47409ef5dd5b558def3779c8a89e610a4e9c69abc94192026bf37498feaf471c
Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON
Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.
Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.
Use this in research
A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.
These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.
Research methodology · Execution and cost assumptions · Check backtest overfitting
Build with the open-source tools
Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.
- Get an API key and run your first validation
- Connect the MCP server to your coding assistant
- Inspect the ALPHAC engine on GitHub
- Read the MCP server source and integration examples
The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0000310142.json") as response:
record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
print(concept["tag"], next(iter(concept["observations"])))