The programming languages, frameworks, databases, and infrastructure that power the Glass platform. This is the technical detail — for the sales overview, see the main Glass page.
Each service picks the right language for the job — PHP for domain logic, Go for high-throughput, Python for AI pipelines.
| Service | Language / Framework | What It Does |
|---|---|---|
| CRU-Glass | PHP 8.3 · Vite · ES6 | Core monolith — 11 dashboards, ticket UI, admin, AI report builder, 3D facility viewer |
| glass-core | PHP 8.3 · Slim 4 · JWT RS256 | Auth & identity — SSO/OIDC, MFA, 7-tier RBAC, settings manager |
| glass-tickets | PHP 8.3 · Slim 4 | PSA/ITSM — lifecycle state machine, rules engine, time tracking |
| glass-tickets-sla-go | Go 1.25 daemon | SLA sidecar daemon — high-frequency deadline tracking and alert triggers |
| glass-assets | PHP 8.3 · Slim 4 | CMDB — asset lifecycle, dynamic health scoring, warranties, RMA tracking |
| glass-cyber | PHP 8.3 · Slim 4 · PostgreSQL JSONB | Cybersecurity awareness training & testing — interactive modules & quizzes, phishing simulations, risk scoring |
| glass-rmm | Go 1.25 · RustDesk + MeshCentral | RMM & dual remote access — remote shell, auto-checkin tokens, interactive terminal, patch deployment |
| glass-invoice | PHP 8.3 · Symfony / Platform | Native billing engine (SolidInvoice) — invoices, recurring subscriptions, quotes, payment gateways (replaces QBO) |
| glass-unifi | Go 1.25 + Python | Telephony & audio — UniFi Talk, Android Call & Meeting Audio Pipeline (Whisper ASR + Pyannote diarization) |
| glass-chat | Go 1.25 · WebSocket · React 18 | Real-time messaging — WebRTC voice/video, call transcription (10k+ concurrent connections) |
| glass-superops | PHP 8.3 · PostgreSQL | PSA sync & native replacement — retired in production at Sterling Innovations (110x speedup: 30.5 ms search) |
| glass-procurement | PHP 8.3 · Slim 4 | Procurement — purchase-order lifecycle, supplier catalog, automated totals |
| glass-feedback | PHP 8.3 · Slim 4 | Bug tracking — AI developer-prompt generation, threaded notes |
| glass-crm | Go 1.25 · Chi · React SPA | CRM — campaigns, Redis Streams, SKIP LOCKED queue dispatch |
| glass-sentinel | Go 1.25 · Chi | XDR & security ops — Wazuh SIEM on DMZ, multi-tenant isolation, blocklists, posture & sandboxed remediation |
| glass-strix | Python / Docker | Automated penetration testing — vulnerability scanning, attack simulation, and CVE mapping |
| glass-ai-worker | Python 3.11 · FastAPI · Pydantic | AI worker — Dual-LLM sandbox, pgvector RAG, Pydantic schema validation |
| glass-email | PHP 8.3 · Slim 4 · EWS | Email — Exchange ingestion, AI triage & noise scoring |
Highlighted rows = Go / Python (non-PHP)
Glass runs on your own hardware — the Docker platform (40+ containers) plus AI inference. And you choose how the AI runs: host it locally on a GPU for full data sovereignty, or point it at a frontier-model subscription and skip the GPU entirely.
Run Ollama on your own GPU or DGX Spark. 100% data sovereignty — nothing ever leaves your network — and zero per-request cost after a one-time GPU spend. Needs 24–48 GB VRAM / unified memory (see build tiers below).
Prefer not to host AI? Bring your own API key — Anthropic Claude, OpenAI GPT, or Google Gemini — through Glass's built-in model router. No GPU required; the platform runs on a modest CPU-only server. Pay-as-you-go, and fastest to stand up.
Either way, all 7+ AI features work — triage, semantic RAG search, transcription, and the report builder — and you can mix local and frontier models per feature.
| Workload | Minimum | Recommended | What CRU runs |
|---|---|---|---|
| Docker platform (no AI) | 8 cores · 16 GB · 256 GB SSD | 16 cores · 32 GB · 512 GB NVMe | 80 cores · 512 GB |
| AI inference (Ollama) | 16 GB VRAM / 32 GB unified | 48–64 GB VRAM / unified | 128 GB unified (Blackwell) |
| Combined (one machine) | 16 cores · 64 GB · GPU | 32 cores · 128 GB · GPU | DGX Spark + Server stack |
Runs the full platform; AI swaps models between requests. No deep reasoning.
Full Dual-LLM + all AI features (except deep reasoning). Best for 5–10 techs.
Everything — all models resident, deep reasoning, headroom for future models. CRU's setup.
The GPU is only for self-hosted AI. Choose the frontier-model subscription instead and the Budget/Recommended builds drop the GPU entirely — Glass then runs on a modest CPU-only server. Docker Compose profiles let you deploy only the services you need.