California Compensation Data. Cleaned. Classified. Ready.
26.8 million position records across 5,400 agencies. All 29 SCO columns, AI-classified to 230+ canonical positions, with CalPERS rates and financial actuals. One API.
Data infrastructure only
Your methodology, your deliverables, your client relationships.
Classified Compensation Data
LIVE APICity of Pleasanton
Alameda County • 432 employees • Peer rank: 7/15
AI-classified • All 29 SCO columns • Benefits itemized
Workflow comparison
Skip the spreadsheet archaeology
15 – 25 hours
per study, per analyst
Download SCO CSVs
Clean & normalize titles
Classify positions to benchmarks
Build peer comparisons
Calculate cost-to-market
Under 30 minutes
automated, repeatable
Find your client agency
GET /v1/agencies?search=< 1 secPull all classified compensation data
GET /v1/positions?agency_id=< 2 secGet statistically-selected peer agencies
GET /v1/agencies/:id/similar< 1 secGenerate formatted Excel workbook
POST /v1/exports< 30 secProjected Impact
From 15 hours to 3 hours per study
Typical workflow improvement
A mid-size California compensation consulting firm conducting 15+ municipal studies per year currently spends 12–18 hours per study on data acquisition: downloading CSVs from publicpay.ca.gov, cleaning title inconsistencies across agencies, manually matching positions to benchmark classifications, and building peer comparisons from scratch.
With CalComp Data's pre-classified, normalized data accessible via API, firms can pull classified compensation data in minutes and go straight to analysis — reducing data gathering to 2–4 hours and freeing analysts to take on more engagements.
Based on typical compensation study workflows in California municipal consulting. Actual results vary by firm size, methodology, and study complexity.
15 hours
3 hours
4
7
Manual review
AI-verified
Data coverage
The most complete CA compensation dataset
Position Records
All 10 SCO employer types, 2009-2024
Agencies
Cities, counties, special districts, K-12, CSU, UC
Years of Data
2009 through 2024, updated annually
CalPERS Plans
Employer rates, formulas, tiers
Financial Records
SCO FTR + CDE SACS fiscal data
Taxonomy Entries
AI-classified with SOC crosswalks
Last updated: March 2026
Classification Engine
326,275 titles classified. Here's how.
Every title in the database passes through a 4-layer pipeline. The AI layer is the fallback, not the default — most titles are resolved by deterministic matching first.
Title Cache
Previously classified titles are instantly matched. Handles repeat lookups across 5,400+ agencies.
Heuristic Matcher
Regex patterns for ~40 common municipal titles (Police Officer, City Manager, etc.). Free, instant, 95%+ confidence.
Fuzzy Matcher
Normalized title comparison against 230+ canonical taxonomy entries. Catches abbreviations, misspellings, and variants.
AI Classifier
Claude API with full taxonomy context. Batch mode (20 titles/call) for unusual or ambiguous titles. Returns confidence score.
Worked Example
Raw SCO title:
"SR MGMT ANALYST"
ADMIN-05: Senior Management Analyst
Confidence: 94%
326K
Titles Classified
230+
Taxonomy Entries
21
Position Families
Pricing
One plan. Unlimited users.
$66,000/year, billed annually. Flat fee, unlimited users.
- All 29 SCO compensation columns
- 21 computed analytical fields
- 4-layer AI classification engine
- 230+ canonical position taxonomy
- Custom taxonomy crosswalk mapping
- CalPERS employer rate plans
Locked for 2 years. 2 of 3 spots remaining.
Shape the product roadmap. Priority feature requests. Direct Slack channel with the engineering team.
Save $12,000/year vs. standard pricing.
See the data for your next study
Schedule a 20-minute demo and explore the API with your own client agencies. Or request a 90-day pilot key — no commitment.
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