> For the complete documentation index, see [llms.txt](https://arcis-r.gitbook.io/arcis/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://arcis-r.gitbook.io/arcis/information/faq.md). # FAQ ## **General Usage** #### **Q: Is ARCIS® difficult to set up for small teams or startups?** A: Not at all. ARCIS® offers lightweight CLI-based setup and container images, allowing even single developers to benefit. For more complex deployments, you can integrate with Docker/Kubernetes for scaling. #### **Q: What programming languages does ARCIS® currently support?** A: ARCIS®’s Agents (e.g., CodeSynth, TestGenius) primarily target Python, Rust, Go, TypeScript; Translator extends these languages to Java and C# (coming Q1 2025), with PHP and others on the roadmap. #### **Q: How does ARCIS® fit into my existing CI/CD pipeline?** A: Each Agent can be triggered via CLI calls or Docker containers, making it straightforward to insert a job in GitHub Actions, Jenkins, or GitLab CI. ARCIS® also provides reference YAML configurations for standard pipelines. *** ## **Security & Compliance** #### **Q: Can ARCIS® handle sensitive, proprietary code?** A: Absolutely. ARCIS® uses TLS for data in transit, AES-256 for data at rest, and optional integration with on-prem Key Management Systems (KMS). Access is controlled via RBAC and integrated logging for full audit trails. #### **Q: Does ARCIS® offer official compliance certifications (SOC 2, ISO 27001)?** A: While ARCIS® as a platform aims to align with these standards, official certifications are targeted for Q2 2025. Nonetheless, the platform is designed to meet or exceed those compliance guidelines from inception. #### **Q: What if ARCIS® auto-applies a fix that breaks compliance?** A: Organizations can configure Agents to only suggest fixes rather than auto-apply them. For critical compliance or security settings, an approval workflow can block changes until a designated lead reviews them. *** ## **Performance & Scaling** #### **Q: How does ARCIS® scale with large repositories or multiple projects?** A: Each Agent is an independently deployable microservice, letting you horizontally scale for big or numerous codebases. PerfGuard, for instance, can spawn multiple test workers, while CodeSynth can parallelize code refactoring tasks. #### **Q: Does ARCIS® require powerful hardware or GPUs?** A: While GPUs can accelerate complex ML tasks or large code queries, ARCIS® Agents run fine on CPU-based systems. You can optionally integrate HPC or GPU nodes to speed up advanced analysis in CodeSynth or TestGenius. #### **Q: We have thousands of commits daily—can ARCIS® keep up?** A: Yes. ARCIS®’s orchestrator (ARCIS® Core) queues tasks and distributes them across available Agent instances. You can auto-scale Agents in Docker/Kubernetes to handle spikes in commit volume. *** ## **Customization & Extensions** #### **Q: Can I create my own ARCIS® Agent?** A: Yes, ARCIS® supports a plugin architecture. You can build Agents in Python, Rust, or Go, hooking into ARCIS® Core for scheduling, logging, and role-based access. A future Marketplace will let you share or monetize these Agents. #### **Q: Is the ARCIS® Trinity (THESIS, ANTI-THESIS, SYNTHESIS) mandatory or optional?** A: It is optional—an advanced feature for teams wanting a more collaborative AI approach to code optimization. Smaller teams or simpler projects may not need the Trinity, while large enterprises benefit from its self-improving capabilities. #### **Q: How do I integrate ARCIS® with an internal tool or legacy system?** A: ARCIS® offers a CLI, REST APIs, and an SDK (Python, partially in Rust/Go). You can either call ARCIS® services directly via HTTP or create a plugin bridging your internal tool’s logic with ARCIS®’s orchestration layer. *** ## **Licensing & Pricing** #### **Q: Is ARCIS® open-source, free, or commercial?** A: ARCIS® is released under the MIT License for the core platform. Certain Agents may have premium enterprise features or require paid tiers for advanced usage (e.g., higher concurrency or support). Check our pricing page for details. #### **Q: What’s the difference between the community and enterprise tiers?** A: The community tier offers basic Agent functionality, suitable for hobbyists or open-source contributors. The enterprise tier adds advanced compliance, 24/7 support, auto-scaling orchestration, and specialized enterprise integrations. #### **Q: Can I purchase individual Agents rather than the whole suite?** A: Yes, you can pick specific Agents (e.g., only CodeSynth & TestGenius) or buy a bundled subscription. The platform is modular to fit your exact needs and budget. *** ## **Support & Community** #### **Q: How do I get help or report an issue?** A: ARCIS® provides official support channels, along with a community forum. #### **Q: What about training or certification on ARCIS®?** A: Workshops, training videos, and certification paths (e.g., “Certified ARCIS® Practitioner”) are being rolled out in parallel with major releases, ensuring devs can master the platform quickly. #### **Q: Does ARCIS® have an active developer community?** A: Yes, we’re fostering a supportive, global community of developers and DevOps specialists via forums, social channels (Twitter, Telegram), and in-person/virtual events. *** ## **Future Scope** #### **Q: Will ARCIS® expand to other languages or frameworks (e.g., .NET, Swift)?** A: Yes, language support is a top priority. The roadmap includes Swift and .NET expansions post-Q2 2025, pending resource alignment and community feedback. #### **Q: Can ARCIS® handle specialized domains like blockchain or HPC?** A: ARCIS® is structured to accommodate domain-specific Agents. For instance, the Translator already supports smart contract languages, and HPC integration is targeted for Q2 2025 with GPU acceleration. #### **Q: Is ARCIS® aiming to become a fully autonomous coding platform?** A: ARCIS®’s vision is to automate as many repetitive tasks as possible, while still giving human developers control over creative decisions. Over time, deeper AI autonomy will emerge, but user oversight remains key to aligning solutions with real-world constraints.