Pipl connector

Use your Pipl identity and fraud signals for reporting, automation and AI.

Data Panda brings your Pipl identity searches, person records, contact methods and confidence scores together with the data from the rest of your business. From one place, we turn it into dashboards, automations, AI workflows and custom apps your team uses every day.

About Pipl

Identity resolution for trust and safety teams.

Pipl was founded in 2005 by Matthew Hertz, with offices in Tel Aviv and the United States. The company started as a deep-web people-search engine and over two decades repositioned the same identity graph for B2B trust and safety: payment platforms, marketplaces, ecommerce brands and investigation teams that need to put a confidence score on the person behind an email, phone number or username.

The product surface today sits in three places. Pipl Search is the investigator-facing tool, used by fraud and compliance analysts to look up a person and pull back linked emails, phone numbers, social handles, addresses and historical aliases with provenance. Pipl Trust is the API-and-decisioning side, scoring identities for payment authorisation, KYC onboarding and account-takeover detection through a model the company calls Elephant. Pipl Elements exposes the underlying identity components for teams that want to build their own decisioning logic on top. The data graph behind all three is described as more than five billion identities and several hundred billion trust signals collected over twenty years.

The reason to land Pipl in a warehouse is that the score the API returned and the decision your team made do not live in the same system. Pipl tells you how confident it is that the email and the phone belong to the same real person; your CRM, payment processor and chargeback file tell you whether that confidence held up. Auth-rate lift on high-confidence identities, false-positive cost on the manual-review queue, chargeback rate per score band and rules that fired but never closed an actual case all live in the join between Pipl, the order book and the agent timeline. Inside the Pipl UI those numbers stay in a single search; in a warehouse they become the renewal-and-tuning conversation.

Ideas

What you can automate with Pipl.

Pair with HubSpot

Land Pipl identity and confidence scores on HubSpot contacts and companies

Pipl identity searches, contact methods and confidence scores land on the matching HubSpot contact and company, with the linked aliases and prior addresses on the timeline. Sales sees whether a new lead carries a high-confidence verified identity or a thin one before booking the meeting, and RevOps trends Pipl spend against meetings booked on verified-versus-unverified contacts.

Pair with Salesforce

Push Pipl confidence and risk signals into Salesforce

Pipl Trust scores, KYC outcomes and account-takeover flags land on the Salesforce account, contact and case with the rule that fired and the analyst who closed the alert. AEs see which named accounts carry an open trust-and-safety case before they reach out, and RevOps audits chargeback rate per Pipl score band against the deal it sat under.

Pair with Slack

Page the on-call analyst in Slack on a high-risk Pipl flag

A Pipl Trust score below the team threshold or a high-confidence ATO match posts to the trust-and-safety Slack channel with the order, the linked identity and the buttons to approve, reject or escalate. The analyst hits a button, the decision lands on the case in your warehouse, and the SLA between flag and decision becomes a metric instead of a feeling.

Pair with monday.com

Run the Pipl manual-review queue on a monday.com board

Every Pipl flag that needs human review opens an item on a monday.com board with the score, the rule, the linked identity and the deadline. Analysts work the queue, the resolution writes back to your warehouse, and team leads watch backlog age and false-positive rate per rule on a board next to staffing instead of on a separate fraud-tool dashboard.

Pair with Intercom

Show Pipl identity context to support agents in Intercom

When a customer opens an Intercom conversation, the agent sees the linked Pipl identity record, prior aliases, the confidence score and any open trust-and-safety flag on the same view. Support stops asking three security questions on a routine refund and routes the genuinely thin-identity contacts to the analyst queue, with handle time per identity tier visible in your warehouse.

Pair with Exact Online

Tie Pipl flagged transactions to the Exact Online ledger

Pipl-flagged orders, refunds and chargebacks land on the matching Exact Online sales invoice and credit note, with the score band and rule that fired attached. Finance reconciles fraud loss against the booked revenue per channel and per score band, instead of pulling a separate report from the fraud tool every month-end and trying to match it by hand.

Your existing tools

Your data lands in a warehouse. Your BI tools read from it.

You keep the reporting tool you already have. We connect it to the warehouse where your Pipl data lives.

Power BI Microsoft

Fabric Microsoft

Snowflake Data warehouse

BigQuery Google

Tableau Visualisation

Excel Sheets & pivots

Three steps

From Pipl to answers in three steps.

Connect securely

OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.

Land in your warehouse

Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.

Reporting, automation, AI

We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.

Two ways to work with us

Pick the track that fits how you work.

Track 01

Self-serve

We set up the foundation. Your team builds on top.

Pipl connector configured and running
Warehouse set up in your cloud account
Clean access for your Power BI, Fabric or Tableau team
Documentation on what's in the data model
Sync monitoring so you're warned before reports break

Best fit Teams that already have a BI analyst or data engineer and want to own the build.

Track 02

Done for you

We build the whole thing, end to end.

Everything in Self-serve
Dashboards built to the questions your team actually asks
Automations between your systems
AI workflows scoped to real tasks your team runs
Custom apps where a dashboard does not cut it
Ongoing delivery at a pace that fits your team

Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.

Before you book

Frequently asked questions.

Who owns the data?

You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.

How fresh is the data?

Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.

Do I need a warehouse already?

No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.

GDPR-compliant

Data stays in the EU

You own the warehouse

A first deliverable live in four to six weeks.

We review your Pipl setup and the systems around it. Together we pick the first thing worth building.

Book a call See our other connectors