TUNTAS AI: Strategy Execution Intelligence

Inspiration

Organizations often have strategic plans and KPI dashboards, yet execution still fails because assumptions remain untested, weekly actions are disconnected from measurable outcomes, and task completion is mistaken for impact.

TUNTAS AI was created to make strategy execution accountable. It helps leaders see what is working, what remains unproven, and what should happen next.

What it does

TUNTAS AI turns a strategic priority into a connected execution chain:

Strategy → Hypotheses → Action Drivers → Evidence → Impact → Review → Adapt

The application supports multi-tenant workspaces, strategy cascading, accountable owners, weekly execution actions, evidence submissions, deterministic impact calculations, executive review, and human-approved adaptation decisions.

Instead of merely reporting KPIs, TUNTAS AI connects weekly actions to the evidence and outcome movement needed to justify management decisions.

How we built it

TUNTAS AI is a PHP and MySQL application designed for shared hosting. It uses GPT-5.6 through the OpenAI Responses API to structure strategy drafts, audit assumptions, generate evidence-aware execution analysis, and support review workflows.

The app also connects to a verified journal-metadata database. Research metadata informs hypotheses, while the interface clearly distinguishes research relevance from strategy-specific causal proof.

How Codex helped

Codex was used throughout the project to shape the PHP architecture, implement multi-tenant access and login flows, design the strategy-execution data model, integrate GPT-5.6, adapt the journal-evidence provider, build the responsive interface, add automated tests, diagnose shared-hosting deployment issues, and prepare documentation.

Key product decisions included keeping human approval traceable, treating missing observations as unavailable rather than zero, and ensuring AI-generated assessments never replace executive judgment.