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Studio overview, packages, selected work, and FAQ.

How the Bangalore studio works with US and EU teams.

Fifteen-minute scoping call. Written appetite after.

Firm CV: competencies, team, anonymized past performance.

HTML directory of public pages.

Machine-oriented facts about Quorve Labs.

LLM apps, RAG that cites sources, agents with tool-calling, and evals that keep the thing honest in production.

Golang, Node, and Python services you can hand to a team: OpenAPI, tests, queues when they earn their keep.

CI/CD, containers, a landing zone, and cost discipline. Kubernetes only when you already need it.

JS/TS end-to-end: auth, one primary workflow, payments if needed, hosted and yours.

Fixed scope, fixed price. One user type, one loop, auth, database, hosted. AI is a paid add, not a surprise.

Architecture and LLD for three anonymized systems.

A production pipeline that scans documents and schemas once, writes a masking blueprint, then fans out synthetic copies with human review, vaultless tokenization, and an agent tool bus.

Three deployables: a document ingest pipeline into vector search, an orchestrator API, and a chat client. Answers are generated from indexed chunks, not from a naked prompt.

Retrieve tickets, wiki pages, and indexed docs, then generate a structured software requirements spec. Features become tickets, gaps close the loop, traceability stays read-only.

System map, principles, trust boundaries

Extractor, ensemble, blueprint, emitter

Registry, personas, gateway, errors

Schema RAG, providers, tool minting

Layers, data flow, event triggers

Processors, index fields, APIs, security

Six layers from UI to traceability

Graph nodes, state, sequences, services