ROI Calculator

HoundDog.ai can save you time, money, and tokens.

Quantify the privacy, compliance, and AI coding productivity gains from automating sensitive data flow scanning, GDPR reporting, and cross-service API context for AI coding agents.

ProtoMap New Sensitive Data ProtectionPrivacy Compliance Automation

ProtoMap New

ProtoMap ROI

Feed AI coding agents real-time, cross-repo API context so they stop grepping files and burning tokens rediscovering dependencies. Calculate token savings and developer time saved on API or service changes.

50
5500
8
130
$100
$20$500
Token Cost Saved $48,000 per year
Developer Time Saved 16,640 hours per year
Productivity Gain 8.0 FTEs

Benchmarked on 9 gRPC repositories with 5 million lines of code, ProtoMap made Claude Code 7.7× faster and 6.4× cheaper per prompt, with higher accuracy (100% vs. 98%). See the benchmarks.

This calculator applies a conservative 5x improvement (80% less cost and time) to prompts about API or service updates.

Where the savings come from

Cross-service dependency awareness

The engine identifies every downstream service affected by an API change up front, instead of letting the agent rediscover dependencies prompt by prompt.

Field-level API context

Agents get exact call sites and line numbers for every field they change across repos, with no speculative file reads.

Fewer wasted tokens on code analysis

Static analysis runs once, deterministically. Agents stop burning tokens on repeated grep, file reads, and throwaway scripts.

Always-fresh service catalog

Catalog rebuilds on every commit. Agents never get stale documentation that drifts from the code.

Privacy Code Scanner

Sensitive Data Protection ROI

Detect PII, PHI, CHD, and auth tokens leaking into risky data sinks: logs, standard output, or third-party and AI integrations that may lack a DPA or receive data beyond its scope. Drag the slider to size the savings for your codebase.

1,000,000
100K10M
Average Privacy Leaks Detected 50 leaks
Time Saved 4,000 hours per year
Productivity Gain 1.9 FTEs

Based on current customer usage of HoundDog.ai, there are on average 5 sensitive data leaks per 100,000 lines of code, where PII, PHI, CHD, or auth tokens flow into risky data sinks. Each leak requires at least 80 hours to remediate if discovered in production: code changes to stop logging or to mask sensitive data, halting log ingestion by third-party systems like Datadog and Splunk, access log review to determine exposure, risk assessment, and customer notification (if exposed auth tokens or passwords need to be rotated).

Cleartext Exposure of Sensitive Data Examples

CategoryData TypesSeverityFrameworks
Account Data Passwords, Access Tokens High NIST, GDPR, CCPA
Financial Data Card numbers, Bank accounts, Payroll High PCI, GDPR, CCPA
Personal Identification Passport, Driving License, SSN, National ID, TIN High NIST, GDPR, CCPA
Health Data MRN, Family Health History, Test Results, Diagnoses, Vital Signs High HIPAA, GDPR, CCPA
Contact Data Name, Address, Phone, DOB, Gender Medium GDPR, CCPA
Online Identifiers Username, IP Address, MAC Address Low GDPR, CCPA

Privacy Code Scanner

Privacy Compliance Automation ROI

Maintain GDPR data maps at development speed, keep your Records of Processing Activities (RoPA) updated with the latest processing activities and subprocessors, and complete Privacy Impact Assessments (PIAs) and DPIAs as fast as your engineering team ships code.

50
1500
Manual Work Eliminated 80% of compliance tasks
Time Saved 2,000 hours per year
Productivity Gain 1.0 FTEs

Based on current customer usage of HoundDog.ai, privacy teams can slash 80% of the average 50 hours spent on manual privacy compliance tasks per code repository per year. Manual tasks include documenting processing activities for RoPA, tracking data flows to third-party systems, completing PIA and DPIA questionnaires, and validating adherence to data processing agreements (DPAs).

These savings do not include the additional gain from replacing manual privacy reviews and legal checks with an automated process that unblocks product development earlier in the SDLC.

See your own ROI on your own codebase.

Run a privacy scan in seconds, plug API context into your AI coding agents, and talk to us when you are ready for org-wide coverage.

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