Why ADRI is Open Source: Our Honest Answer
Last updated: January 2025
The Straight Truth
We get asked this question a lot: "Why did Verodat open source ADRI?" Here's our honest answer, without the typical corporate marketing speak.
1. AI Data Quality Must Be Transparent
You need to see exactly what's happening to your data.
When your AI agent is making financial decisions, medical recommendations, or any business-critical choices, you cannot afford black boxes in your data pipeline. You need to understand:
- What quality checks are being applied
- How scores are calculated
- Why data was accepted or rejected
- What standards are being enforced
ADRI's source code is open because transparency isn't optional for AI data quality. You should be able to audit every line of code that touches your data.
2. You Need to Understand the Problem First
Use ADRI. See what happens when you scale.
Start with one AI agent protected by ADRI. Watch it generate data quality standards, audit logs, and assessment reports. Everything works beautifully.
Now imagine you have 20 AI agents. Or 50. Each one generating its own:
- Data quality requirements
- Compliance logs scattered across systems
- Different standards formats
- Isolated assessment reports
Feel that pain. Experience the chaos of decentralized AI data management. Because only when you understand the real problem can you make an informed decision about the solution.
3. Then Decide: Build or Buy
We built Verodat because we faced this exact problem.
After using ADRI across multiple AI agents, you'll face three critical needs:
- Centralized Compliance Logging - Unified audit trails across all AI agents for enterprise governance
- Data Supply Communication - Standardized way for AI teams to communicate data requirements to data engineering teams
- Controlled Data Access - Tunable, deterministic AI query endpoints to your data warehouse
You have two choices:
- Build your own platform to handle enterprise-scale AI data management
- Use Verodat's Enterprise Data Supply Platform
Both are valid choices. We're not here to lock you in or hide the complexity.
4. We Earn Your Business Through Excellence, Not Lock-In
Every day, we have to be more cost-effective than your internal build.
This is the competitive pressure we've chosen. We can't rely on:
- Vendor lock-in
- Hidden complexity
- Proprietary data formats
- Black box algorithms
Instead, we have to win by being:
- More cost-effective than building internally
- Faster to deploy than custom solutions
- More reliable than homegrown platforms
- Better supported than DIY approaches
This pressure makes us better. It forces us to build something truly world-class.
The Risk We're Taking
Yes, this is risky for Verodat.
By open sourcing ADRI, we're:
- Giving away the tool that reveals the problem
- Enabling competitors to build similar solutions
- Making it easier for customers to build their own platforms
- Putting ourselves in direct competition with internal development teams
But it's the right kind of risk - the kind that forces excellence.
Our Commitment
We believe the future of AI data management should be:
- Transparent - You see exactly how your data is processed
- Standards-based - Open formats that don't lock you in
- Community-driven - Improved by the collective intelligence of AI engineers
- Economically honest - We earn revenue by delivering value, not by creating dependency
What This Means for You
Use ADRI freely. Audit the code. Contribute improvements. Fork it if you want. Build your own enterprise platform if that makes sense for your organization.
And if you decide Verodat's platform offers better economics than building your own, we'll have earned that business through merit, not manipulation.
Questions?
This approach isn't typical for enterprise software companies. If you have questions about our open source strategy, our business model, or anything else, we're happy to discuss openly.
Contact: thomas@verodat.com
GitHub: ADRI Repository
Verodat Platform: verodat.com
We believe transparency builds trust, and trust builds better software. This is our contribution to that cycle.