Is Ada Safe? — Trust Score: 68.8/100
Why This Score
- Security score: 0/100 (weak)
- Maintenance: 1/100 — low maintenance activity
- Compliance: 79/100 — covers 41 of 52 jurisdictions
- Documentation: 1/100 — limited documentation
- Popularity: 0/100 — 1 stars on github
According to Nerq's independent analysis of ada, this ai_assistant has a trust score of 68.8 out of 100, earning a C grade. With 1 stars on github, it is below the recommended threshold of 70. Security score: 0/100. Compliance: 79/100 across 52 jurisdictions. EU AI Act classification: minimal. Data sourced from 13+ independent signals including GitHub, NVD, OSV.dev, and OpenSSF Scorecard. Last updated: 2026-03-19. Machine-readable data (JSON).
Is Ada safe?
CAUTION — Ada has a Nerq Trust Score of 68.8/100 (C). It has moderate trust signals but shows some areas of concern that warrant attention. Suitable for development use — review security and maintenance signals before production deployment.
Trust Assessment
Moderate — ada shows mixed trust signals. Some areas are strong while others could be improved. We recommend reviewing the full KYA (Know Your Agent) report before integrating it into production workflows.
Trust Signal Breakdown
Details
| Author | alikhan017 |
| Category | ai_assistant |
| Stars | 1 |
| Source | https://github.com/alikhan017/ada |
| Frameworks | ollama |
| Protocols | mcp · rest |
Regulatory Compliance
| EU AI Act Risk Class | MINIMAL |
| Compliance Score | 79/100 |
| Jurisdictions | Assessed across 52 jurisdictions |
Popular Alternatives in ai_assistant
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What Is Ada?
Ada is a AI tool in the ai_assistant category. Build your AI assistant with Ada, which runs on your hardware and offers a personalized experience.
As of March 2026, Ada is available on github, making it an emerging tool in the AI ecosystem. But popularity alone does not equal safety — which is why Nerq independently analyzes every tool across 13+ trust signals.
How Nerq Assesses Ada's Safety
Nerq's Trust Score is calculated from 13+ independent signals aggregated into five dimensions. Here is how Ada performs in each:
- Security (0/100): Ada's security posture is poor. This score factors in known CVEs, dependency vulnerabilities, security policy presence, and code signing practices.
- Maintenance (1/100): Ada is potentially abandoned. We track commit frequency, release cadence, issue response times, and PR merge rates.
- Documentation (1/100): Documentation quality is insufficient. This includes README completeness, API documentation, usage examples, and contribution guidelines.
- Compliance (79/100): Ada is broadly compliant. Assessed against regulations in 52 jurisdictions including the EU AI Act, CCPA, and GDPR.
- Community (0/100): Community adoption is limited. Based on GitHub stars, forks, download counts, and ecosystem integrations.
The overall Trust Score of 68.8/100 (C) reflects the weighted combination of these signals. This is below the Nerq Verified threshold of 70. We recommend additional due diligence before production deployment.
Who Should Use Ada?
Ada is designed for:
- Developers and teams working with ai_assistant tools
- Organizations evaluating AI tools for their stack
- Researchers exploring AI capabilities in this domain
Risk guidance: Ada is suitable for development and testing environments. Before production deployment, conduct a thorough review of its security posture, review the specific trust signals above, and consider whether a higher-scored alternative meets your requirements.
How to Verify Ada's Safety Yourself
While Nerq provides automated trust analysis, we recommend these additional steps before adopting any AI tool:
- Check the source code — Review the repository's security policy, open issues, and recent commits for signs of active maintenance.
- Scan dependencies — Use tools like
npm audit,pip-audit, orsnykto check for known vulnerabilities in Ada's dependency tree. - Review permissions — Understand what access Ada requires. AI tools should follow the principle of least privilege.
- Test in isolation — Run Ada in a sandboxed environment before granting access to production data or systems.
- Monitor continuously — Use Nerq's API to set up automated trust checks:
GET nerq.ai/v1/preflight?target=ada - Review the license — Confirm that Ada's license is compatible with your intended use case. Pay attention to restrictions on commercial use, redistribution, and derivative works. Some AI tools use dual licensing or have separate terms for enterprise customers that differ from the open-source license.
- Check community signals — Look at the project's issue tracker, discussion forums, and social media presence. A healthy community actively reports bugs, contributes fixes, and discusses security concerns openly. Low community engagement may indicate limited peer review of the codebase.
Common Safety Concerns with Ada
When evaluating whether Ada is safe, consider these category-specific risks:
Understand how Ada processes, stores, and transmits your data. Review the tool's privacy policy and data retention practices, especially for sensitive or proprietary information.
Check Ada's dependency tree for known vulnerabilities. Tools with outdated or unmaintained dependencies pose a higher security risk.
Regularly check for updates to Ada. Security patches and bug fixes are only effective if you're running the latest version.
If Ada connects to external APIs or services, each integration point is a potential attack surface. Audit all third-party connections, verify that data shared with external services is minimized, and ensure that integration credentials are rotated regularly.
Verify that Ada's license is compatible with your intended use case. Some AI tools have restrictive licenses that limit commercial use, redistribution, or derivative works. Using Ada in violation of its license can expose your organization to legal liability.
Ada and the EU AI Act
Ada is classified as Minimal Risk under the EU AI Act. This is the lowest risk category, meaning it faces minimal regulatory requirements. However, transparency obligations still apply.
Nerq's compliance assessment covers 52 jurisdictions worldwide. For organizations deploying AI tools in regulated environments, understanding these classifications is essential for legal compliance.
Best Practices for Using Ada Safely
Whether you're an individual developer or an enterprise team, these practices will help you get the most from Ada while minimizing risk:
Periodically review how Ada is used in your workflow. Check for unexpected behavior, permissions drift, and compliance with your security policies.
Ensure Ada and all its dependencies are running the latest stable versions to benefit from security patches.
Grant Ada only the minimum permissions it needs to function. Avoid granting admin or root access.
Subscribe to Ada's security advisories and vulnerability disclosures. Use Nerq's API to get automated trust score updates.
Create and maintain a clear policy for how Ada is used within your organization, including data handling guidelines and acceptable use cases.
When Should You Avoid Ada?
Even promising tools aren't right for every situation. Consider avoiding Ada in these scenarios:
- Production environments handling sensitive customer data
- Regulated industries (healthcare, finance, government) without additional compliance review
- Mission-critical systems where downtime has significant business impact
For each scenario, evaluate whether Ada's trust score of 68.8/100 meets your organization's risk tolerance. We recommend running a manual security assessment alongside the automated Nerq score.
How Ada Compares to Industry Standards
Nerq indexes over 204,000 AI agents and tools across dozens of categories. Among ai_assistant tools, the average Trust Score is 62/100. Ada's score of 68.8/100 is above the category average of 62/100.
This positions Ada favorably among ai_assistant tools. While it outperforms the average, there is still room for improvement in certain trust dimensions.
Industry benchmarks matter because they contextualize a tool's safety profile. A score that looks moderate in isolation may actually represent strong performance within a challenging category — or vice versa. Nerq's category-relative analysis helps teams make informed decisions by showing not just absolute quality, but how a tool ranks against its direct peers.
Trust Score History
Nerq continuously monitors Ada and recalculates its Trust Score as new data becomes available. Our scoring engine ingests real-time signals from source repositories, vulnerability databases (NVD, OSV.dev), package registries, and community metrics. When a new CVE is published, a major release ships, or maintenance patterns change, Ada's score is updated within 24 hours.
Historical trust trends reveal whether a tool is improving, stable, or declining over time. A tool that consistently maintains or improves its score demonstrates ongoing commitment to security and quality. Conversely, a downward trend may signal reduced maintenance, growing technical debt, or unresolved vulnerabilities. To track Ada's score over time, use the Nerq API: GET nerq.ai/v1/preflight?target=ada&include=history
Nerq retains trust score snapshots at regular intervals, enabling trend analysis across weeks and months. Enterprise users can access detailed historical reports showing how each dimension — security, maintenance, documentation, compliance, and community — has evolved independently, providing granular visibility into which aspects of Ada are strengthening or weakening over time.
Ada vs Alternatives
In the ai_assistant category, Ada scores 68.8/100. There are higher-scoring alternatives available. For a detailed comparison, see:
- Ada vs Mastra Docs — Trust Score: 51.9/100
- Ada vs openchamber — Trust Score: 89.1/100
- Ada vs openakita — Trust Score: 81.8/100
Key Takeaways
- Ada has a Trust Score of 68.8/100 (C) and is not yet Nerq Verified.
- Ada shows moderate trust signals. Conduct thorough due diligence before deploying to production environments.
- Among ai_assistant tools, Ada scores above the category average of 62/100, demonstrating above-average reliability.
- Always verify safety independently — use Nerq's Preflight API for automated, up-to-date trust checks before integration.
Safer Alternatives
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