AI Integration & Data Solutions
Applied AI on your own data, with the limits stated up front.
We build AI features that solve a specific, checkable problem: answering questions from your own documents, classifying or extracting data from incoming paperwork, drafting routine replies. We are equally direct about where a language model is the wrong tool — and about the fact that these systems need a human review path.
Typical investment
KES 400,000 – 3,500,000+
Per project
Whether your data is already clean and reachable, ongoing model hosting costs, and how much accuracy testing is required before go-live.
The band narrows to a single fixed price in a signed statement of work before any work begins. See bands for every service.
What you get
Deliverables, not adjectives
- A defined use case with a success measure agreed before we build
- Document question-answering over your own content, with cited sources
- Extraction and classification pipelines for invoices, forms and records
- Dashboards and reporting over data you already collect
- Guardrails: input limits, cost controls, logging and a human review path
- A written note on the model's known failure modes and how to spot them
Good fit for
Is this the right service?
- Teams answering the same questions from a large document set
- Back offices keying data out of PDFs and scans by hand
- Businesses with data they collect but never actually report on
Technologies
The ecosystems we work in
Models
Retrieval
Data & analytics
Operations
How we work
From first call to handover
- 01
Discovery call
A free 30-minute conversation about the problem, the constraints and the budget range. If we are not the right fit, we say so on this call.
- 02
Scope & written quote
We define what the first release includes and excludes, then quote it as a fixed price in a statement of work you can take to procurement.
- 03
Design & architecture
Screens and data model agreed before the build. Changing a diagram is cheaper than changing a shipped feature.
- 04
Build in increments
Short cycles with something reviewable at the end of each. You see progress in a working environment, not in a status report.
- 05
Test & launch
Functional, performance and security checks, a staged rollout with a rollback path, and a launch date agreed rather than announced.
- 06
Handover & support
Documentation, training and code in a repository you own — followed by a support retainer if you want us to keep it running.
Questions
What buyers ask before signing
Will our data be used to train someone's model?
Not without your explicit decision. We use providers whose business terms exclude training on API data, and where that is not acceptable we deploy an open-weight model on infrastructure you control.
How do you stop it giving wrong answers?
We ground answers in your own documents and return citations so a person can verify them, we test against a fixed set of real questions, and we keep a human in the loop for anything consequential. We do not claim these systems are error-free.
Is AI the right answer for our problem?
Often it is not, and a database query or a rules-based automation is cheaper and more reliable. We will tell you that before you spend money on it.
Often combined with
Let's scope your ai & data work
Tell us the problem and the constraints. You get a written scope and a fixed price within three working days — or an honest note that this is not something we should take on.