AI-generated delivery breaks when agents lack system context.
Your AI agents write code. Cubyts ensures they understand the system.
Built for CTOs and engineering leaders looking to get more reliable outcomes from AI-assisted software delivery.
Works alongside Cursor, Claude, Copilot, GitHub, GitLab, Azure DevOps, Jira and equivalent tools, and your existing CI/CD workflows — and we'll integrate with any tool of your choice as part of a custom engagement.
Two ways to bring system context into AI-driven engineering.
Use the Cubyts platform out of the box, or work with us to build custom AI agents and live context systems around your enterprise workflows.
Cubyts SDLC Platform
A deployable SDLC platform that gives AI coding agents live system context across requirements, code, tests, releases, and workflows. Designed to reduce delivery drift, rework, and governance gaps.
Best for teams looking to operationalize AI-driven SDLC quickly.
Custom AI Services
We design and deploy enterprise AI agents and live context systems built around your workflows, systems of record, governance rules, and operational processes.
Best for enterprises needing custom AI agents, or domain-specific context systems.
AI agents operating across your software delivery lifecycle.
Every enterprise delivers software differently. All Cubyts agents operate on the same live SDLC context layer, integrating with your systems of record and governance workflows.
Code Atlas
Surface hidden dependencies, risky code areas, and downstream system impact.
Explore agent →System Context
Give AI agents live system-wide understanding across requirements, code, tests, releases, and workflows.
Explore agent →Process Guardian
Continuously enforce delivery workflows, approvals, and governance policies across the SDLC.
Explore agent →Feature Quality
Track feature health from planning through release and identify delivery drift early.
Explore agent →Code Sentinel
Detect risky code patterns, architectural drift, and emerging technical debt before release.
Explore agent →Doc Assurance
Keep technical and delivery documentation continuously aligned with implementation.
Explore agent →System-aware AI, proven in real software delivery workflows.
Explore how live SDLC context reduces delivery drift, improves governance, and helps AI-driven engineering teams ship more reliably.
Each implementation runs on the same live SDLC context layer, adapted to different enterprise workflows and governance models.
Delivery Health Intelligence
B2B SaaS Product Company
PR rework reduced from ~30% to ~15%
Real-time signals from Jira, Git, and CI/CD that surface rework and drift early — turning sprint execution into a predictable, measurable system.
SDLC Governance
Fintech Platform
Same-day audit readiness across releases
Continuous validation across requirement, code, test, and release — cutting feature misalignment and making audit readiness a same-day activity.
SDLC Context Engineering
Internal Reference Implementation
45% fewer AI correction cycles
A unified context graph exposed to AI coding agents — reducing PR rework, iteration cycles, and AI correction loops across multi-repo development.