The unglamorous part
of applied AI, done well.
Jantia takes the information an organisation already has (documents, systems, the public web) and turns it into data that can be trusted, connected, queried in plain language, and pushed into the tools people already use. That is the whole offer, and it is the part that decides whether the rest works.
Why we exist
Most organisations already own the information they need to run better. It sits in PDFs nobody opens, in systems that do not talk to each other, on public web pages that change weekly, and in the heads of people who are about to retire.
Most of what an organisation knows is unstructured. People spend a working day a week looking for something that already exists. Records decay quietly. And AI projects fail for data reasons, not model reasons: poor data quality, no connection to real systems, no path from demo to daily workflow.
Jantia exists to do the unglamorous part well: get the data out, get it right, get it connected, and keep it that way. We are a B2B company headquartered in Harare, Zimbabwe, serving clients across Africa and internationally. We work with the people who buy the work (operations, finance, IT leadership) and the people who will use the result (service desks, analysts, field staff, administrators).
- Founded
- December 2025
- Headquarters
- Harare, Zimbabwe
- Entity
- Jantia (Private) Limited
- Registration
- 73284A02122025
“The model is rarely the problem. The plumbing is.”
Roughly 95 percent of enterprise generative AI pilots show no measurable return. Fewer than 15 percent of knowledge graph pilots make it to production. The stated causes are data quality, entity resolution, and the absence of a path into daily work. None of those are model problems. All of them are the work we do.
Four habits you will notice in the first week.
We count before we process
How many files, of what type, how many pages, how many duplicates by content. Confirmed with you before the estimate, the price, or the plan is final.
We sample before we scale
A representative slice, processed and shown: extraction quality, records produced, gaps. Adjusted before the full run, not discovered at the end.
We dry-run before we write
No record reaches your systems until you have read exactly what will be written and what could not be matched.
We verify from the target
After a write, the count you see comes from your system, not from our logs.
The rules our work runs on.
Nothing is invented
Every fact traces to a source. When the sources are silent, the answer is “not stated.”
Everything is traceable
Counts at every stage, the dry run before every write, the audit log of every assistant conversation.
Every step is checked
Before the next begins. The shape of the work is what prevents the failures the research describes.
Start with what you already have.
An assessment takes one to two weeks at a fixed price and tells you, in writing, what your information can answer and what it would take. Useful on its own even if nothing follows.