Gov-AIdeaS videos

Research on the shelf

Every year, Samar State University finishes studies that answer real LGU questions. Most of them stay on the shelf. When an LGU prepares its CDP, its AIP or its Executive-Legislative Agenda, the right local study is hard to find, long to read, and rarely written as policy.

Meet Gov-AIdeaS

Meet Gov-AIdeaS, the Government AI-Driven Ideas System, by Samar State University and SICGLG.

How it works

It puts four things in one place: a repository of SSU studies, AI that reads them, people who check the AI, and direct links between LGUs and SSU researchers. For each study, the AI works in layers: a quick summary, key insights, a deeper analysis, and the research gaps. Then it drafts policy recommendations, each with an implementation plan.

Three checks

Nothing reaches an LGU unchecked. Each recommendation passes an automated quality check, a review by the research desk, and final approval by SICGLG. Here, a validator reads the draft, adds notes, and approves it. Drafts can also be sent back for revision, or rejected.

Use case 1: planning with evidence

Use case one: planning with evidence. A municipal planning coordinator, updating the CDP, searches for research unit and finds an SSU study on it. The AI summary explains the findings in plain language, with an LGU relevance score and key insights. The top recommendation: institutionalize a municipal research unit through an executive order, led by the planning office. Its implementation plan has four phases over 13 weeks, a ₱20,000 budget, six offices with clear roles, risks to watch, and the legal steps, starting with the executive order. Before acting, the coordinator can ask the study's SSU researchers for a consultation.

Use case 2: barangay justice

Use case two: barangay justice. An LGU wants policy options from SSU's study on the Katarungang Pambarangay. Anyone can read a study's preview. Signed-in users get the full abstract and the AI analysis. Policy tools need an approved request. The officer states the purpose, and the request goes to SICGLG. SICGLG reviews it, and grants access for a set period, here ninety days.

Use case 3: when no study exists yet

Use case three: when no study exists yet. Coastal barangays flood every typhoon season. So the LGU posts a study request: the problem, the place, and how the results will be used. SSU's research office reviews it and assigns a researcher, and the system suggests existing studies that may already help. The LGU follows every step: submitted, under review, accepted or matched, in progress, and completed.

Use case 4: the researcher's side

Use case four: the researcher's side. An SSU faculty member wants a study to be used. The researcher uploads it with the abstract, keywords, sector and PDF. Once it is published, the AI analysis begins. When an LGU asks for help, the researcher answers right in the platform, and the study is put to work.

Who gains

For LGUs: local evidence in plain language, with ready steps to act. For SSU researchers: studies that reach the people who can use them. For DILG: a way to help every LGU plan with evidence.

How DILG can help

Here is how DILG can help. Endorse Gov-AIdeaS to LGUs through your city and municipal local government operations officers. Support a pilot with Samar's 26 LGUs. And send us the questions your LGUs need answered. Gov-AIdeaS. From research to action: AI-assisted, people-validated.

Introduction

A quick tour of Gov-AIdeaS, role by role.

Who can do what

Four kinds of users share one platform. Each sees more as they sign in and get access, and SICGLG keeps the AI in check.

The guest

Chapter one: the guest. With no account, anyone can search, browse by sector, and read study previews. Anyone can open Gov-AIdeaS: SSU research in one place, organized by sector. Studies are organized into six sectors, each with its latest research and trending topics. No account needed. Search SSU research by topic, title or author. Guests see a preview of each study. Registering unlocks the full abstract and the AI tools.

The LGU official

Chapter two: the LGU official. Signed in, an officer reads AI summaries, asks about a study, requests policy tools, consults researchers, and posts study requests. Signed in, an LGU officer gets an AI summary in plain language, an LGU relevance score, and the key insights. The officer can also ask about the study itself, for example, how an LGU could implement it. Policy tools need approval. The officer states the purpose, and SICGLG reviews the request. Once approved, the LGU sees ranked policy recommendations, each with responsible offices, timelines and an implementation plan. Each recommendation opens into a full implementation plan, with its timeline, phases, activities and budget, ready to download as a PDF. Need expert help? Request a consultation with the SSU researcher behind the study. Have a problem no study answers yet? Post a study request, so SSU can research what your LGU needs. The LGU tracks each study request and its status in one list. When a program works, the LGU can share it as a best practice, so other towns can repeat it. Admins review it before it is published.

The SSU researcher

Chapter three: the SSU researcher, who uploads studies and answers the LGUs that ask for help. SSU researchers upload a study with its abstract, keywords, sector and PDF. AI analysis starts once it is published. Researchers answer LGU consultations right in the platform.

SICGLG and the research office

Chapter four: SICGLG and the research office. They validate the AI, approve access, triage study requests, and watch the analytics. SICGLG and the research office manage everything from one dashboard. Admins review each access request and set how long access lasts. Every AI recommendation goes through validation. A validator reads it, adds notes, and approves, returns or rejects it. The research office reviews each study request, assigns a researcher, and checks the auto-suggested studies that may already answer it. Analytics show how research is used and which problems LGUs bring to SSU. Gov-AIdeaS. From research to action: AI-assisted, people-validated.

Planning with evidence

Use case one: planning with evidence.

Search

A municipal planning coordinator, updating the CDP, searches for research unit and finds an SSU study on it.

The AI summary

The AI summary explains the findings in plain language, with an LGU relevance score and key insights.

The recommendation

The top recommendation: institutionalize a municipal research unit through an executive order, led by the planning office.

The implementation plan

Its implementation plan has four phases over 13 weeks, a ₱20,000 budget, six offices with clear roles, risks to watch, and the legal steps, starting with the executive order.

Consult SSU

Before acting, the coordinator can ask the study's SSU researchers for a consultation. Gov-AIdeaS. From research to action: AI-assisted, people-validated.

Barangay justice

Use case two: barangay justice. An LGU wants policy options from SSU's study on the Katarungang Pambarangay.

Three levels of access

Anyone can read a study's preview. Signed-in users get the full abstract and the AI analysis. Policy tools need an approved request.

The request

The officer states the purpose, and the request goes to SICGLG.

SICGLG's approval

SICGLG reviews it, and grants access for a set period, here ninety days.

Three checks

Nothing reaches an LGU unchecked. Each recommendation passes an automated quality check, a review by the research desk, and final approval by SICGLG. Gov-AIdeaS. From research to action: AI-assisted, people-validated.

When no study exists yet

Use case three: when no study exists yet. Coastal barangays flood every typhoon season.

The study request

So the LGU posts a study request: the problem, the place, and how the results will be used.

Triage

SSU's research office reviews it and assigns a researcher, and the system suggests existing studies that may already help.

Step by step

The LGU follows every step: submitted, under review, accepted or matched, in progress, and completed. Gov-AIdeaS. From research to action: AI-assisted, people-validated.

The researcher's side

Use case four: the researcher's side. An SSU faculty member wants a study to be used.

The upload

The researcher uploads it with the abstract, keywords, sector and PDF. Once it is published, the AI analysis begins.

How the AI reads it

For each study, the AI works in layers: a quick summary, key insights, a deeper analysis, and the research gaps. Then it drafts policy recommendations, each with an implementation plan.

Answering an LGU

When an LGU asks for help, the researcher answers right in the platform, and the study is put to work. Gov-AIdeaS. From research to action: AI-assisted, people-validated.