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 through Fivetran, the industry standard for data replication. Over 1,000 connectors. Setup takes less than 5 minutes per source. No engineering, no CSV uploads, no API keys to manage.
Map records across systems
Your HubSpot contacts don’t know about your Xero invoices. Your Stripe subscriptions don’t connect to your Intercom conversations. Each system is an island. You can’t ask cross-system questions because the data doesn’t link.
Tidyr automatically discovers relationships between records across every connected source. Contacts map to invoices map to subscriptions map to support tickets. One unified graph of your business data.
Clean with AI matching
“Acme Corp” in HubSpot. “ACME Corporation” in Xero. “acme-corp-inc” in Stripe. Same company, three names. Multiply that across hundreds of records and you have a data quality disaster.
Tidyr resolves entities using three complementary methods. Each catches what the others miss. 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. If two records share the same unique key, they match. Fast and certain.
Fuzzy
String similarity algorithms for near-matches. Catches typos, abbreviations, formatting differences. “Acme Corp” and “ACME Corporation” score high because they’re clearly the same entity.
AI Embedding
Semantic understanding via 768-dimensional vector embeddings. Catches matches that rules and string comparison miss. Knows that “IBM” and “International Business Machines” are the same company.
You stay in control
Every AI-suggested match lands in a review queue. You see the confidence score, the source records, and the matching method. Approve, reject, or override. Tidyr learns from your decisions and improves over time.
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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