RevSure leverages advanced AI responsibly, ensuring compliance, transparency, and accuracy in pipeline forecasting, attribution, and GTM intelligence. This section addresses FAQs on AI usage, data extraction, governance, and visitor identification.

AI Usage FAQ's

Use of Google Gemini LLM Models‍

RevSure integrates Google’s Gemini LLM models into its AI offerings—Reli Assist and Reli Copilot, to power intelligent insights, recommendations, and GTM automation. This use is governed by strict compliance with global data privacy laws like GDPR and CCPA. RevSure only transmits structured, non-sensitive data (such as aggregated metrics and metadata) to Gemini, with multiple safeguards in place: encryption, access control, PII masking, and customer opt-outs. No customer data is ever used to retrain models. Customers retain full control over AI-driven features, ensuring transparency, security, and compliance at every level.

Security and AI FAQ

As part of RevSure’s commitment to transparency, data security, and responsible AI usage, we’ve compiled a detailed FAQ outlining our approach to Predictive and Generative AI, data handling practices, integrations, compliance frameworks, and safeguards. This document is designed to support security reviews, procurement evaluations, and technical due diligence processes.

Access the full RevSure AI & Data Usage FAQ here

AI Model Inputs and Logic

RevSure’s AI model powers advanced pipeline forecasting and attribution by leveraging a complete view of your GTM data—across CRM, marketing automation, ad platforms, and more. It combines ML-driven prediction with probabilistic attribution logic to uncover the true drivers of pipeline and bookings.

For a deeper look into model inputs, validation processes, interpretability features, and how to reconcile AI vs. rules-based attribution, explore the full technical FAQ.

Access the full RevSure AI Model Inputs & Attribution Logic FAQ here

Data Extraction

Data From RevSure to SFDC and Data Warehouses‍

RevSure can push various types of data, including lead reporting, pipeline reporting, and attribution data, to Salesforce (SFDC) and data warehouses. This enables a seamless integration of your reporting and attribution output tables into your existing systems.
RevSure supports the ability to expose reporting and attribution data via BigQuery, which can be easily queried and used to build reports in any Business Intelligence (BI) tool.

Data Extraction Format‍

The data pushed to your data warehouse will be in the form of precomputed tables. These tables are processed and computed within RevSure, so there is no need for additional recomputation or complex joins.
The tables will contain all necessary calculations and transformations, ready for immediate use. You can push these tables on a bulk or incremental basis, with sync schedules configurable to suit your business needs.

Advanced Data Handling FAQ's

RevSure is deeply committed to robust data governance, privacy, and enterprise-grade security. To help our customers understand how we manage data across our platform, including ingestion, processing, storage, access control, and compliance—we’ve created a comprehensive Advanced Data Handling FAQ.

Access the full RevSure Advanced Data Handling FAQ here

Data Handling and Resolution Scenarios

At RevSure, we understand that enterprise customers require clarity not just on how data is handled, but also on how exceptions, escalations, and edge cases are resolved. Our Data Handling & Resolution Scenarios outlines real-world situations—such as data access issues, deletion requests, system outages, and policy enforcement—and explains how RevSure responds to each.

This document is designed to provide confidence in our operational readiness, support protocols, and adherence to data protection best practices.

Access the full RevSure Data Handling & Resolution Scenarios Doc here

Data Security FAQ

To support legal, procurement, and IT due diligence, we’ve prepared a concise FAQ covering how RevSure handles PII, guarantees AI data isolation, and complies with global data protection standards.

It also outlines the protections built into our GenAI partner—Google Gemini.

View the full RevSure AI & Data Security FAQ here

Data Write-backs & Reporting Tables

Table Schemas for Data Warehouse/Lake storage
Yes, RevSure can write datasets back to various destinations, including data warehouses and data lakes. This includes:‍

‍Reporting Tables: Precomputed tables for quick reporting on leads, pipeline, and accounts, with user-friendly schema and funnel analytics context.

RevSure Entity Tables: Core tables containing data from all source systems, normalized and stitched together.

Source System Objects: Raw dumps of source system data, including standard and custom attributes from systems like Salesforce.

Attribution Outputs: Pre-computed tables enable dynamic querying and power attribution reporting, similar to Demand Generation Effectiveness (DGE). Attribution model scores are pre-computed at the Lead/Opportunity level, supporting report generation with dynamic filter criteria and direct exports from DGE.

Data Write back Destinations‍

RevSure can write back data to various destinations, including:

Data Warehouses: Snowflake, BigQuery, Redshift.
Customer Data Platforms (CDPs): Segment.
Object Stores: Google Cloud Storage, Amazon S3, Azure Blob Storage.

RevSure also supports writing back to on-premise databases or other systems like SQL Server via SSIS, and is not limited to cloud systems like Snowflake or BigQuery.

Below is the workflow diagram for RevSure to Write back to destinations:

Write-backs for Dynamic Reporting and Attribution Outputs

RevSure writes back precomputed reporting and attribution tables that are ready for dynamic querying. These tables are periodically synced with your destination system, either in bulk or incrementally. Sync schedules are configurable based on your requirements.

For example:

Attribution Outputs: These tables are precomputed at the lead and opportunity level, supporting attribution reporting with filters, date ranges, and attribution models configured for your use cases.
Direct Exports from Demand Generation Effectiveness (DGE): CSV exports can be configured for specific views in the DGE module and pushed directly to your destination system.

Sanity Checks and Corrections for AI Recommendations

RevSure’s machine learning (ML) models are exclusively built on your historical data (typically the last 2-3+ years) and are tailored to your specific business context, such as custom attributes and sales cycles.

We conduct extensive backtesting to ensure accuracy and fine-tune the models to reflect historical trends. Additionally, RevSure tracks historical projections to allow you to monitor trends and evaluate which factors are driving those projections.

Anonymous User or Company Identification for Website Visitors

RevSure offers anonymous visitor enrichment through:

6Sense Integration: Enriches anonymous visitors with company-level attributes like company name, industry, revenue, and region using the customer’s 6Sense account.
RB2B Integration: For additional person and company identification at an extra cost.
People Data Labs: Enriches anonymous visitor data by connecting it with detailed professional profiles, enabling businesses to identify key roles, companies, and industries visiting their website.
5x5coop: Identifies anonymous website visitors by translating IP data into identifiable company information, including company size and industry.

Additionally, when visitors fill out forms, RevSure’s first-party tracking pixel captures identifying information like names and email addresses, which are then mapped to CRM records (e.g., leads/contacts/accounts).

Fingerprinting and Consent Under ICO for Anonymous Visitor Tracking

RevSure uses both cookies and fingerprinting methodologies via a first-party tracking pixel. We comply with ICO guidelines by supporting consent management. Consent parameters are passed to the pixel, which signals the user’s preference for opt-in/opt-out.

We also support three levels of fingerprinting:

L0: IP, carrier, and geo-location.
L1: L0 + device and OS details.
L2: L1 + browser details.

For privacy and compliance, RevSure supports pseudo-anonymization of fingerprints.

Fingerprinting level 2 is at the browser level (which includes other attributes from Levels 0 & 1) and is the best option we have to stitch repeat visitors when the visitor hasn't enabled cookies.

Consider a scenario where 2 persons from the same organization are visiting the website using the same type of device, browser etc. The IP address for them could also be the same since they are connecting from the same network. In this case, these visitors will be classified as one visitor.

This is something to be aware of but is not a downside because the alternative is we end up not counting cookie-less visitors or we end up counting each cookie-less visit as a unique visitor which leads to over-stating the visitor numbers.