Tmob AI Studio
AI-Native End-to-End Digital Product Delivery Operating System
New Product Delivery Model: 16 Years of
End-to-End Delivery Know-How
We transformed 16 years of end-to-end delivery know-how into a data moat--reusable accelerators, guardrails, and proven patterns. Tmob AI Studio turns delivery and production signals into governed, enforceable execution: quality gates, standards enforcement, and auditable releases.
Single Studio, Single Ownership
AI Studio centralizes delivery artifacts into a single system of record and runs orchestration on top--so specs become build-ready work with continuous validation and enforceable gates.
Unified Design & Alignment
A consistent artifact chain--Product Brief, PRD, Decomposition, OpenAPI/AsyncAPI, Test Plan, and Runbook--stays in sync as a single source of truth. Requirements become structured work items, while design specs and tokens remain continuously synchronized across engineering workflows.
AI-Native Creation
Agentic workflows continuously validate artifacts for standards, policy constraints, and audit readiness. They flag missing acceptance criteria, edge-case gaps, and release risks before build--reducing rework and stabilizing ALM throughput.
Parallel Engineering
Quality gates are enforced by default: no UI implementation starts without acceptance criteria and an edge-case matrix. No integration proceeds without contract tests, an approved auth model, and observability hooks--enabling safe parallel delivery without late-cycle surprises.
4-Step Delivery Model
A proven four step delivery model takes products from scope to production.
Discovery & Analysis
Set the delivery contract: baseline metrics, scope, bottlenecks, and risks.
Design
Define journeys and prototypes with clear acceptance criteria and edge-case coverage.
Development
Run design and engineering in parallel with API-first delivery and automated quality gates.
Run
Operate with SLOs and runbooks; production signals feed continuous optimization.
From Design Fidelity to
Operational Stability
AI Studio prevents design-code drift with enforceable quality gates, and governs operations with SLOs, runbooks, and observability--so teams ship faster with fewer incidents and auditable releases
Seamless Transition from Design to Development
Every design output is development-ready from day one. The platform enforces a single token strategy, maps Figma components to their codebase counterparts, and auto-generates skeleton components. Real-time Figma-to-code synchronization means designers iterate in Figma while developers work from the same living spec--drift detection runs on every pull request, and AI-assisted edge-case generation catches visual regressions before they reach review. The result: up to 90% less design rework, a single source of truth for layout, spacing, and theming, and a measurable improvement in delivery throughput.
Post-Launch Governance
Once a product is live, AI Studio shifts focus to observability and operational ownership. Every service is deployed with SLOs, alert policies, and runbooks pre-configured. Monitoring surfaces performance regressions, error-rate spikes, and resource saturation through unified dashboards. Runbooks encode remediation steps so on-call engineers resolve incidents faster. Continuous governance audits confirm that logging, tracing, and privacy controls remain compliant--turning post-launch operations into a repeatable, auditable discipline rather than ad-hoc firefighting.
