How Tidyr Works
Your data is scattered, siloed, messy, and missing context. Tidyr fixes each problem in sequence—then hands Claude a unified intelligence layer via the Model Context Protocol. No data team required.
Connect everything
Your data lives in 5–15 different tools. Someone asks a question and you open HubSpot, then Xero, then Stripe, then Intercom—piecing together an answer manually. There’s no front door.
Tidyr connects to your tools with pre-built integrations. Over 100 connectors covering CRM, finance, billing, and support. Setup takes less than 5 minutes per source. No engineering, no CSV uploads, no API keys to manage.
Plus Shopify, Monday, Notion, Google Sheets, and 100+ more
Match & unify across systems
“Acme Corp” in HubSpot. “ACME Corporation” in Xero. “acme-corp-inc” in Stripe. Same company, three names. Your systems are islands—contacts don’t link to invoices, subscriptions don’t connect to support tickets.
Tidyr resolves entities using three complementary AI methods, then links records across every system into a single unified graph. You stay in control—every match goes through a review queue where you approve, reject, or override.
Deterministic
Exact rules on shared identifiers. Email addresses, phone numbers, domain names, tax IDs. Fast and certain.
Fuzzy
String similarity for near-matches. Catches typos, abbreviations, and formatting differences.
AI Embedding
Semantic understanding via vector embeddings. Catches what rules and string comparison miss.
The result: one unified record
Clean, enrich, fill the gaps
Unified data is only useful if it’s accurate. Missing fields, stale records, inconsistent formats—these erode trust in every report and every AI answer.
Tidyr continuously monitors data quality, flags anomalies, and enriches records to fill gaps. Standardize formats, detect missing fields, and layer in external data so your intelligence layer is always complete.
Data Quality
Automated monitoring catches issues before they reach your dashboards. Missing emails, invalid formats, stale records, duplicate entries.
Enrichment
Fill in missing company data, industry classifications, employee counts, and domains. Turn sparse records into complete profiles.
Standardization
Normalize formats across every system. Consistent naming, addresses, phone numbers, currencies. No more “US” vs “United States” vs “USA.”
Continuous quality scoring
Every record gets a quality score. Tidyr tracks completeness, freshness, consistency, and accuracy over time. You see exactly where your data stands and what needs attention—before it becomes a problem in your reports.
Add your business context
This is the step most platforms skip. Clean, connected data is necessary but not sufficient. Claude still doesn’t know what “churn” means to YOUR business, or how YOU segment customers, or which metrics YOUR board cares about.
Tidyr lets you layer your business logic on top of unified data. Define your metrics, your segments, your operational rules. This is what transforms generic AI answers into intelligence that sounds like it came from someone who actually works at your company.
Metric Definitions
Customer Segments
When Claude answers “What’s our churn rate?” it uses YOUR definition—not a generic one. That’s the difference between a chatbot and a business intelligence layer.
Claude with real intelligence
Connected, mapped, cleaned, and contextualized. Tidyr serves your unified data to Claude via the Model Context Protocol. Claude doesn’t just get data—it gets your business understanding.
Which enterprise customers are at risk of churning this quarter?
3 enterprise accounts match your at-risk criteria (overdue invoice + open ticket + declining usage): Acme Corp ($42K ARR, 2 overdue invoices, 3 open tickets), Globex ($28K ARR, 1 overdue invoice, declining logins), and Initech ($22K ARR, support escalation + 45-day payment delay). Total ARR at risk: $92K.
Reconcile our HubSpot pipeline with actual Xero revenue for Q1.
HubSpot shows $312K in closed-won deals for Q1. Xero shows $298K in recognized revenue. The $14K gap comes from 2 deals: one invoiced but payment deferred to Q2 ($9K, Nexus Ltd), and one with a billing address mismatch that delayed invoicing ($5K, Atlas Inc). Both are resolved in your unified records.
What does our customer health look like by segment?
Enterprise (12 accounts, $284K ARR): 9 healthy, 3 at-risk. Mid-Market (34 accounts, $156K ARR): 28 healthy, 4 at-risk, 2 churned in March. SMB (201 accounts, $89K ARR): 178 healthy, 15 at-risk, 8 churned. Overall health score: 84%. Biggest concern: Enterprise at-risk accounts represent 17% of your total ARR.
These aren’t hypothetical. These are the kinds of answers Claude gives when it has unified data with your business context. Cross-system, reconciled, using your definitions.
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