AI Use Policy

Codepixel is an AI-augmented software development studio. We use enterprise AI tools to help us deliver client work faster, with stronger consistency, and at lower risk. We publish this policy so that clients, prospects, and partners can see exactly how we work with AI — and what we won't do.

This policy applies to AI usage across all Codepixel client engagements and internal operations. For data processed through this website, see also our Privacy Policy.

1. Our approach in one paragraph

Codepixel uses enterprise AI tools to augment human engineering work, not replace it. Every AI-assisted output passes through human review before it reaches a client. We restrict ourselves to a small set of vetted Tier A tools that contractually do not train on customer data and that we configure for restricted retention. Clients always retain the option to require human-only delivery.

2. Approved tools

We use only the following enterprise-tier AI tools for client work:

Each is configured so that, by default:

• The vendor does not train on our or our clients' inputs.
• Retention is restricted to what the vendor's enterprise policy requires.
• Where the vendor offers regional controls (e.g., EU regions), we prefer EU residency for EU client data.

We update this list when our tooling changes. If a tool moves out of Tier A status (for example, if a vendor changes its data-handling defaults), we stop using it for client work and remove it from this list.

3. What we do NOT do

The following are out-of-bounds for Codepixel's AI usage:

• No consumer-grade AI for client work. We do not paste client code or data into free / consumer accounts of any AI provider.
• No production secrets in prompts. Production API keys, database credentials, customer PII samples, or other secrets are never sent to AI tools.
• No special-category data without explicit approval. GDPR Article 9 data (health, biometric, religious, political, etc.) is not sent to AI tools unless the client explicitly approves and we put appropriate safeguards in place (pseudonymization, contracted DPA, vendor certifications).
• No autonomous decisions on client systems. AI agents may propose changes; humans approve and execute them. There is no auto-merge or auto-deploy gated only by AI.
• No model fine-tuning on client code without consent. We only use general-purpose models. We do not fine-tune or distill models on a client's codebase unless explicitly contracted to do so.

4. Mandatory human review gates

Every Codepixel deliverable passes through two AI-assisted review gates, with humans as the final authority:

• Gate 1 — Per Pull Request. Before any PR can merge, it must pass:
  • Automated secrets scanning (we use tools that flag accidentally committed credentials).
  • AI-assisted security and correctness review (with human reviewer sign- off).
• Gate 2 — Pre-Delivery. Before a deliverable ships to a client:
  • A codebase-level AI review surfaces broader correctness, architecture, security, and maintainability issues.
  • Findings are captured in a written Findings Register, then triaged and closed (fix, accept-with-rationale, or document for handoff) by a human reviewer who signs the register.

These gates are part of every engagement. They are described in our Security Statement at a high level.

5. Data handling guarantees

For client work performed with AI assistance, we guarantee:

• No training on your data. All Tier A tools are configured to opt out of training on customer inputs.
• Restricted retention. Per-vendor enterprise configuration; we document the exact retention window in the DPA we sign with each client on request.
• Regional controls where available. EU residency for EU client data where the vendor supports it.
• Pseudonymization for production samples. If we need to test code against real-shaped data, we pseudonymize or synthesize the dataset before any AI tool sees it.
• Audit trail. We keep records of which AI tool worked on which deliverable, available for review by the client per the SOW.

6. Disclosure and labeling

When an AI tool materially contributed to a deliverable, we say so:

• PRs: PR descriptions for AI-assisted PRs include a one-line disclosure.
• Deliverables: Handover notes flag any meaningful AI-assisted content (code, documentation, designs).
• Research / analysis documents: AI-assisted artifacts are labeled in their footer.

We do not over-disclose for trivial uses (e.g., autocomplete suggestions that a human accepted token-by-token). The threshold is "would a reviewer need to know this came from AI to verify it?"

7. Client controls

Clients have the following rights regarding our AI usage on their engagement (codified in the SOW):

• Opt out completely from AI assistance, in which case the engagement is delivered entirely by humans. Pricing and timeline may adjust.
• Restrict to specific tools (e.g., "we approve Copilot but not Claude for this codebase").
• Restrict data types (e.g., "you may use AI for documentation but not on source code").
• Audit usage. On request, we share the audit trail described in Section 5.
• Require zero-data-retention configuration where the vendor supports it. Our default for Anthropic Claude Code is zero data retention; we configure other tools to the strictest retention option each offers.

8. Compliance alignment

Our AI practices are designed to align with:

• EU General Data Protection Regulation (GDPR) — as a controller for our own data and as a processor under our client SOWs. We do not use AI to make solely automated decisions with legal or similarly significant effects on data subjects (GDPR Art. 22).
• EU AI Act (Regulation 2024/1689) — we operate as a "deployer" of general-purpose AI systems in low- and limited-risk contexts. The staged enforcement timeline is now in force (general-purpose model obligations since August 2025, high-risk obligations since August 2026); neither set changes our classification, and we review it whenever our tooling or use cases change.
• Canada PIPEDA and BC PIPA — same human-review-gate and no- training-on-data commitments apply to Canadian client data.
• Sectoral regulations — for engagements in regulated sectors (health, finance, public sector), we tighten controls and document them in the SOW.

9. Incident handling

If an AI tool contributes to a defect, data exposure, or security incident on a client engagement, our incident response covers it like any other root cause. We notify the affected client per the engagement SLA and our Security Statement. We do not hide AI-related causes in post-mortems.

10. Internal use of AI

Beyond client deliverables, Codepixel uses AI internally for:

• Engineering productivity (code completion, documentation, refactoring).
• Sales and marketing operations (drafting, research, content review).
• Internal automation (the same review-gate principle applies).

The same Tier A restriction applies internally: no consumer-grade AI accounts for any business use.

11. Updates to this policy

This policy reflects our practice as of the effective date above. We update it as our tooling, contractual posture, and regulatory environment evolve. Material updates are reflected in the version number and a change- log entry below.

If you are a current client and an update materially affects how we work on your engagement, we will notify you per the SOW.

12. Contact

Questions, audit requests, or feedback on this policy:

• Email: privacy@codepixel.me (subject: "AI Use Policy")
• For client engagement-specific AI questions, use your usual Codepixel point of contact.

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Change log

• v1.1 — August 2026. Updated the EU AI Act wording to reflect that the staged enforcement obligations are now in force. No change to our tooling, gates, or practices.
• v1.0 — Initial publication (May 2026).