Speak the Language
of Innovation.

An AI system architecture where the model autonomously plans, executes, observes, and iterates to complete a complex goal, rather than just responding to a single prompt.

A technique that optimizes the output of a Large Language Model by referencing an authoritative knowledge base (like a vector database) outside its training data before generating a response.

A database that stores data as high-dimensional vectors (numbers). It enables semantic search, allowing AI to find data based on meaning rather than exact keyword matches. Examples: Pinecone, Weaviate.

Processing data closer to the user's physical location (at the 'edge' of the network) rather than in a centralized cloud server. Reduces latency for real-time applications.

User interfaces that are dynamically generated by AI at runtime based on the user's specific intent and context, rather than being statically hardcoded by developers.

The process where client-side JavaScript attaches to HTML rendered by the server to make it interactive. In modern frameworks like Next.js, this is optimized via Partial Hydration.

A cryptographic method by which one party can prove to another that they know a value (like a password) without conveying any information apart from the fact that they know the value.

An architectural style where independently deliverable frontend applications are composed into a greater whole. Allows multiple teams to work on different parts of a UI simultaneously.

A migration strategy where a legacy system is gradually replaced by a new system. New features are built in the new system, and old features are slowly moved over until the legacy system is obsolete.

A software architecture where a single instance of software runs on a server and serves multiple tenants (customers), keeping their data isolated logically rather than physically.