Everything You Need to Make Smarter Technology Decisions

All figures are ranges — actual cost depends on complexity, integrations, and team composition. Book a free call for a fixed-price quote specific to your project.

AI Integration

Connecting AI capabilities — language understanding, prediction, automation — to your existing software or workflows via APIs or embedded models. The AI adds intelligence to what you already use without replacing it.

Large Language Model (LLM)

An AI system trained on large amounts of text data that can understand and generate human language. Examples: GPT-4o (OpenAI), Claude (Anthropic), Gemini (Google). The foundation of modern AI chatbots and assistants.

RAG (Retrieval-Augmented Generation)

A technique where an AI model retrieves relevant information from your own documents or database before generating a response — so it can answer questions about your specific business accurately, not just generic public knowledge.

AI Agent

An AI system that can autonomously plan multi-step tasks, use tools, make decisions, and take actions to achieve a goal — without a human directing every step. Different from a chatbot, which only responds to direct input.

API (Application Programming Interface)

A defined set of rules that allows two software systems to communicate. When you connect your CRM to your website, or add an AI model to your app, you typically do it via an API.

Machine Learning (ML)

A type of AI where a computer learns patterns from data and uses those patterns to make predictions or decisions on new data — without being explicitly programmed with rules. Used for fraud detection, demand forecasting, recommendation engines, and more.

SaaS (Software as a Service)

Software delivered over the internet on a subscription basis. Users access it via a browser — no installation required. Examples: Salesforce, Slack, HubSpot. Building a SaaS product means creating this kind of cloud-hosted, multi-tenant application.

MVP (Minimum Viable Product)

The smallest version of a product that delivers enough value to real users to validate the concept and gather feedback. The goal is to learn quickly with minimal investment before building the full product.

DevOps

A practice that combines software development and IT operations to shorten the development cycle and deliver updates more reliably. Includes automated testing, CI/CD pipelines, containerisation, and infrastructure-as-code.

CI/CD (Continuous Integration / Continuous Deployment)

An automated pipeline that tests code every time a developer makes a change, and deploys it to production automatically when tests pass. Reduces manual release risk and allows teams to ship multiple times per day.

Multi-Tenancy

A SaaS architecture where one instance of the application serves multiple customers (tenants), with each customer's data isolated from others. Essential for scalable SaaS products — it means your software can serve 10 or 10,000 customers without separate deployments.

Legacy Modernisation

Rebuilding an outdated software system — often a desktop application or old web system — as a modern web or cloud application, preserving the business logic and data while replacing the outdated technology stack.