The concepts we use every day in custom software, AI, cloud and product projects — explained without unnecessary jargon.
A contract that lets two systems talk to each other.
An API (Application Programming Interface) exposes a system's functions so another can consume them. REST and GraphQL APIs are the current standard to connect frontends, mobile apps, third-party integrations and microservices.
Turning data into decisions through dashboards and reports.
Tools like Power BI, Looker or Metabase visualize KPIs, cohorts and trends. Good BI replaces meetings where "everyone argues with different spreadsheets".
Automation that tests and deploys every code change.
Continuous Integration validates each commit with tests; Continuous Delivery/Deployment ships it to staging or production automatically. Reduces errors and speeds up delivery.
On-demand infrastructure paid per use.
Compute, storage and database services delivered by providers like AWS, Azure or Google Cloud. Lets you scale without buying servers and pay only for what you consume.
Google metrics on speed and user experience.
LCP (loading speed), INP (interactivity) and CLS (visual stability). They directly impact ranking and conversions.
Applications designed exclusively for your operation.
Software built from scratch to match a company's specific processes, business rules and goals. Unlike packaged SaaS, every module, integration and flow is tailored to the client's reality, allowing you to scale without per-user licenses or functional limits.
Central repository optimized for analytics.
BigQuery, Snowflake or Redshift store large historical volumes and allow complex queries without impacting the transactional business database.
Culture and practices to deliver software continuously.
Combines development and operations with automation (CI/CD), infrastructure as code and monitoring. The goal: reduce the time between "I have an idea" and "it's in production" without sacrificing stability.
Numeric representation of the meaning of a text.
Vectors of hundreds of dimensions that capture semantics. They enable similarity search — finding "what looks like this query" even without exact word overlap.
Processes that move and transform data across systems.
Extract, Transform, Load. Used to consolidate data from multiple sources into a data warehouse and feed dashboards or AI models.
Retraining a model with your data to specialize it.
Adjusts the model weights with your own examples so it learns a style, domain or specific task. More expensive than RAG and only justified when a prompt is not enough.
Models that create new text, images, code or audio.
Systems based on LLMs (Large Language Models) and diffusion models that produce content from instructions. Applied to copilots, customer service, summaries, code generation and automation of cognitive processes.
Optimizing content to be cited by AI-powered search engines.
Practices to make your brand appear in ChatGPT, Perplexity and Google AI Overviews responses: structured content, domain authority, Schema.org markup and direct answers to questions.
Connecting two or more systems so they share data.
Can be direct (API to API), through middleware or via iPaaS platforms (Zapier, Make, n8n). Done well, it eliminates manual rework and information silos.
An AI model trained on large volumes of text.
GPT, Claude, Gemini or Llama are examples. They understand and generate natural language with high quality and integrate into enterprise products via APIs.
Architecture where each capability lives in an independent service.
Instead of a single monolithic block, the system is split into small services with a single responsibility (auth, payments, notifications). Each one is deployed and scaled separately, which simplifies maintenance and resilience.
The smallest version of a product that already delivers value.
An MVP includes only the essential features required to validate the main hypothesis with real users. The goal is to learn fast — not to launch "something incomplete" — and decide with data whether to iterate, pivot or scale.
The phase where you validate what to build before coding it.
User interviews, value maps, prototypes and benchmarks to reduce the risk of building something no one wants. Saves weeks of misdirected development.
Designing instructions to get the best result from an LLM.
Techniques — few-shot, chain of thought, structured output — so the model responds with precise content, format and tone. It is the cheapest, fastest layer to improve AI quality.
Combines an LLM with your knowledge base for accurate answers.
Before answering, the system retrieves relevant fragments from your documents (via vectors) and injects them as context into the LLM. Reduces hallucinations and enables answers with your own, up-to-date information.
Software as a Service — you pay a subscription to use the platform.
A multi-tenant distribution model in the cloud. Ideal for products with repeating demand; when deep customization is needed many companies pair a SaaS with custom development.
Optimizing your site to show up on Google.
Search Engine Optimization spans content, technical architecture, speed, structured data and backlinks. In 2026 it also includes optimization for generative answers (AI Overviews).
Run code without managing servers.
A model where the cloud provider handles the infrastructure and you only write functions. Ideal for variable workloads because cost scales to zero when there is no traffic.
Designing the product experience and interface.
UX (User Experience) defines flows, information architecture and usability. UI (User Interface) defines the visual look, typography, colors and interactions. Both determine product adoption.
A database optimized for similarity search over embeddings.
Pinecone, Weaviate, pgvector or Qdrant store vectors and answer "give me the N most similar" in milliseconds. They are the backbone of RAG and semantic search.
HTTP notification a system sends when an event happens.
Instead of your app polling another system every minute, the source system "pings" you when something changes. Used for payments (Stripe, Wompi), CRMs and automations.
We design and build tailor-made solutions using exactly these technologies.