Optflow

OptFlow is an automated privacy compliance platform that helps organisations map personal data flows and manage DPDP, GDPR, and related compliance through structured workflows such as RoPA, DPIA, vendor assessments, DSARs, and risk tracking.

It solves the problem of fragmented and manual compliance by replacing spreadsheets, disconnected documentation, and repetitive processes with a centralised privacy operations system.

The following public GitHub repositories can be used as sample projects to test OptFlow’s repository scanning and privacy analysis features:

1. https://github.com/wasp-lang/open-saas.git
2. https://github.com/vercel/chatbot.git
3. https://github.com/mickasmt/next-saas-stripe-starter.git
4. https://github.com/dubinc/oss-gallery.git
5. https://github.com/papermark/papermark.git

You may also use any other public GitHub repository for testing, provided the repository size is below 200 MB.

At the current testing stage, OptFlow supports public repositories only. Private repository support can be introduced once the scanning workflow has been sufficiently tested and fine-tuned.

The main features of OptFlow are:

Data Flow Mapping – Identifies how personal data moves across departments, systems, vendors, APIs, databases, and applications. GitHub Repository Scanner – Scans public repositories to detect privacy-relevant data flows, PII exposure, secrets, insecure logging, cookies, storage risks, and other code-level privacy issues. Current testing limit: 200 MB.

I’m looking for help with increasing OptFlow’s visibility, connecting with professionals in privacy, cybersecurity, legal tech, and SaaS, and getting practical feedback on the idea, product positioning, and current features.

I’d especially value introductions, product feedback, testing support, and suggestions on how OptFlow can better solve real-world privacy compliance problems.