SABABAT Goes Public Alpha —
Available for Every Researcher

On March 23, 2025, we quietly launched SABABAT 4.0 in closed beta. No press release. No grand announcement. We invited a small number of undergraduate and postgraduate students — largely through word of mouth — handed them access, and asked a simple question: does this actually work for you?

Five months later, we have our answer. And today — August 8, 2025 — SABABAT enters public alpha. Every statistical analysis tool in SABABAT 4.0 is now accessible to any researcher, student, or professional who needs it. At no cost.

This is not a marketing milestone. It is the direct result of the researchers who trusted us early, pushed back when things were broken, and kept using SABABAT anyway — because they believed something real was being built here.

The beta was far from smooth. We were honest about that from the beginning. The form builder had gaps. Some payment flows misfired — users completed transactions but the generation button did not activate. Some users were charged twice by error.

Every single one of those complaints was resolved. Every duplicate payment was refunded. Every stuck user was unblocked. We responded quickly — sometimes within hours — not because we had a large support team, but because we understood something important: in the early days of a product, trust is the only currency that matters. Trust is built not when everything works, but in how you respond when things don't.

Those moments of friction became defining. Students who had complained — and seen us resolve it — became our most vocal advocates. Not because SABABAT was perfect. Because we listened. That group of 50 to 100 beta users grew quietly through peer recommendation, not advertising. The compound effect of genuine trust is slow to start and hard to stop.

We do not quote our users to flatter ourselves. We quote them because their words reveal something about what research in Nigeria actually feels like — and why SABABAT fills a gap that no existing tool was designed to fill.

That third review from the MSc researcher? We took it to heart immediately. The Form Builder was rebuilt to support full Likert scale tables, matrix-style questionnaire layouts, and dynamic response options. Today it is one of our most-used features — particularly among nursing and health sciences students whose instruments rely heavily on validated scale structures.

Public alpha means one thing above all else: the doors are open. You no longer need an invitation. You no longer need a referral. If you are a student, researcher, nurse, analyst, or academic professional — SABABAT is available to you right now, and the full statistical analysis suite is free.

Here is what that means in practice:

The most common comparison we hear is to Jenni AI. That comparison reveals something important about what SABABAT is — and what it is not.

Jenni AI was built to solve writer's block. It is a writing co-pilot: helpful for generating prose, expanding outlines, and keeping academic text flowing. It does that well. But it was never designed to run a chi-square test, clean a dataset, build a validated research questionnaire, or interpret regression coefficients in the context of your specific study.

SABABAT was built to handle the full quantitative research lifecycle — from instrument design through statistical analysis to written interpretation — without requiring you to know SPSS, R, or any tool with a steep learning curve. It is not a writing assistant. It is an autonomous research system that happens to write exceptionally well.

SPSS costs institutional licenses that most Nigerian universities cannot afford. R and Python require programming fluency most final-year students do not have time to acquire mid-project. Jenni AI does not run statistics. SABABAT does all of it — and was designed from day one to work for researchers who are not computer scientists.

What makes SABABAT different from every surface-level AI tool is not its features list. It is the philosophy embedded in its architecture.

SABABAT is not a text generator pointed at academic topics. It is a research intelligence system. It understands your research questions and objectives — not just your words. It knows that Chapter 3 must be methodologically consistent with Chapter 1. It knows that the interpretation of a chi-square result must reference your study variables, not generic statistical boilerplate.

That is the standard we hold ourselves to. Not just functional output — intelligent, coherent, academically defensible research that you are proud to submit. A research companion that elevates your work while keeping you, the researcher, in command of it.

Public alpha is not the finish line. It is the beginning of the next phase. Over the coming months, we will expand the statistical engine with additional advanced methods, deepen the Form Builder's flexibility, and launch the Project Wizard for guided end-to-end research project generation.

SABABAT 4.5 — our qualitative research engine — is in development, extending the same level of intelligence to thematic coding, interview analysis, and narrative synthesis for researchers whose work is not quantitative.

And beyond academia, Abbadh Labs is building the same infrastructure into healthcare, governance, and large-scale data benchmarking across Africa. The research intelligence we are developing today will power predictive clinical systems, national workforce analytics, and evidence-based policy tomorrow.

But all of that starts here. With a student who needed their literature review in two days. With a chemistry student who told their friends. With a postgraduate researcher who asked for a Likert scale table and watched us build it.

Ruqoyyat Omolayo

CFO & Product Manager, Abbadh Labs · August 8, 2025