Architecture and Risk Review
Two-week technical assessment to identify model, data, safety, and deployment bottlenecks.
- Model and prompt evaluation plan
- Failure mode register with mitigation options
- Delivery roadmap with prioritized milestones
GTCode Consulting
AI Systems That Hold Up in Production
Architecture, delivery, and reliability engineering for applied AI
AI consulting and engineering services from GTCode: strategy, architecture, delivery, and reliability for production-grade AI systems.
How We Engage
Flexible structures depending on your stage, risk profile, and internal team capacity.
Implementation and Hardening
Hands-on delivery for teams shipping agentic workflows, retrieval systems, and AI product features.
- Reference architecture and production scaffolding
- CI/CD, observability, and incident playbooks
- Security and governance controls for release
Fractional AI Engineering Lead
Senior technical guidance for roadmap, hiring, architecture decisions, and delivery governance.
- Technical decision support for leadership
- Vendor and model selection criteria
- Execution coaching for internal engineering teams
Typical Outcomes
Engagements focus on practical throughput: shipping reliable systems faster with fewer regressions.
What You Receive
- Clear target architecture with implementation sequencing
- Documented evaluation framework and acceptance gates
- Operational dashboards and on-call runbooks
- Security and governance checklist aligned to launch risk
GTCode helps teams ship AI systems that survive real production constraints: latency ceilings, brittle data, changing model behavior, and audit requirements.
We work at the architecture-and-delivery layer, not just prototype demos.