AI & tech glossary

A

AEO (Answer Engine Optimisation)

Structuring content so search engines and voice assistants can lift it as a direct answer, for example in featured snippets or “People also ask”. Learn more →

Agentic AI

AI systems that can plan steps and take actions, such as searching, filling forms or calling APIs, to complete a goal, rather than only answering questions. Learn more →

AI agent

A piece of software that uses an AI model plus tools and instructions to carry out tasks on a user’s behalf, often across several steps. Learn more →

AI governance

The policies, roles and controls an organisation uses to make sure its AI is legal, fair, secure and accountable. Learn more →

AI readiness

How prepared an organisation is to adopt AI, usually measured across data, technology, people, processes and governance. Learn more →

API

An application programming interface, a defined way for one software system to request data or actions from another. Learn more →

C

Computer vision

AI that interprets images and video, for example to detect defects, read documents or count objects. Learn more →

D

Daraja API

Safaricom’s developer platform for integrating M-Pesa services, such as STK Push payments, into websites and apps. Learn more →

Data pipeline

An automated process that moves data from source systems, cleans and transforms it, and loads it where it can be analysed. Learn more →

Data Protection Impact Assessment (DPIA)

A documented assessment of the risks a data-processing activity poses to people’s privacy, and the safeguards used to reduce them. Learn more →

Data warehouse

A central database designed for reporting and analytics that combines data from many business systems. Learn more →

E

Embedding

A list of numbers that represents the meaning of text, images or other data, allowing AI systems to find similar items. Learn more →

F

Fine-tuning

Further training an existing AI model on your own examples so it adopts a specific style, format or domain knowledge. Learn more →

G

Generative AI

AI that creates new content (text, images, audio, video or code) based on patterns learned from large amounts of data. Learn more →

GEO (Generative Engine Optimisation)

Making a brand the source that generative AI assistants such as ChatGPT, Gemini, Claude and Perplexity cite in their answers. Learn more →

H

Hallucination

When an AI model produces information that sounds confident but is false or unsupported. Grounding answers in trusted data reduces it. Learn more →

Headless CMS

A content management system that stores and serves content via an API, so the same content can power a website, app and other channels. Learn more →

K

Kenya Data Protection Act 2019

Kenya’s main data-protection law, which governs how personal data is collected and processed and established the Office of the Data Protection Commissioner (ODPC). Learn more →

L

Large language model (LLM)

An AI model trained on large amounts of text that can understand and generate language, for example GPT, Claude, Gemini and Llama. Learn more →

llms.txt

A plain-text file at the root of a website that summarises the site and lists its key pages for AI systems. Learn more →

M

Machine learning

A branch of AI where systems learn patterns from data to make predictions or decisions, such as forecasting demand or scoring risk. Learn more →

MLOps

Practices and tools for deploying, monitoring and updating machine-learning models reliably in production. Learn more →

MVP (Minimum Viable Product)

The simplest usable version of a product that can be put in front of real users to test demand and learn quickly. Learn more →

P

Progressive web app (PWA)

A website that behaves like an app, installable on a phone, fast and able to work offline. Learn more →

Prompt engineering

Writing and structuring instructions for an AI model so it produces accurate, useful and consistent results. Learn more →

Proof of concept (PoC)

A short project that tests whether an idea is technically feasible, usually on real data, before investing in a full build. Learn more →

R

RAG (Retrieval-Augmented Generation)

A technique where AI first retrieves relevant passages from your own documents and then writes an answer based on them, often with sources. Learn more →

S

Schema markup

Structured data added to web pages (usually JSON-LD) that tells search engines and AI what the page is about, such as a service, FAQ or article. Learn more →

STK Push

An M-Pesa payment request (M-Pesa Express) that pops up on the customer’s phone asking them to confirm with their PIN. Learn more →

U

UGC (User-Generated Content)

Content in the style of real customers (reviews, unboxings, testimonials) used in marketing; it can be made by creators or AI presenters. Learn more →

V

Vector database

A database that stores embeddings and finds the most similar items quickly, the backbone of semantic search and RAG. Learn more →

W

Webhook

An automatic message one system sends to another when an event happens, for example a payment provider notifying your site that a payment succeeded. Learn more →