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Qiva
The Intent-Driven Software Pipeline

By Qubiz

Agentic pipeline for software delivery lifecycle

You assign a task. An AI agent runs it autonomously in an isolated sandbox and hands back a pull request, while your team reviews and approves at every gate you set. From new features to modernizing decades-old code.

Start with a Discovery
Qiva
70–80%Lifecycle time reduction
80–90%Automated test coverage
7Agents in production today
5×Digital revenue for modernization leaders

The agents in production

Seven specialists,
each owning one text

Foundation → Repository

Architecture Analyst

Helps you design your architecture foundation by selecting from a built-in catalog of state-of-the-art components, which you can tailor to your needs. The result is a generated repository wired with those components, a production-ready foundation you can start building features on from day one.

Curated componentsBuilt from vetted, production-grade patterns.
Repository generatedA wired, ready-to-run deliverable, not a diagram.
Production-readyYour team approves the outcome before it moves on.

Interactive Mode — steer any agent mid-task. Ask questions, correct course, approve decisions live.

Request a demo

Legacy modernization

Bring old code
into a modern stack

Qiva reads applications written in older languages like COBOL, Progress, and Visual Basic, works out how they fit together, and helps move them toward modern architecture and technology. Long-stalled migrations become tractable again.

Legacy application
→→
Modern stack

Intent is the artifact

Expressed need, not code, is the system of record.

One specialized agent per stage

Each agent is an expert at exactly one job.

Humans approve every gate

Agents draft; your people own every outcome.

Feature explorer

What makes Qiva different

Review and iterate in chat

The workflow pauses at any phase you mark for approval and waits for a human. You review proposed change-sets as diff cards in chat, then approve, reject, or send feedback.

Iterate without paying for a full rerun

The workflow pauses at any phase you mark for approval and waits for a human. You review proposed change-sets as diff cards in chat, then approve, reject, or send feedback.

Declarative multi-phase workflows

Flows are defined in YAML with phases, branches, and nodes: analysis, intent generation, implementation, testing, PR. They combine deterministic steps with AI-driven ones.

Agents that know your stack

In workflows and in live chat, agents work with your repositories and documents. Your context stays close to the work and improves every outcome.

Let’s find your ideal solution

Complete the form and we’ll contact you within the next 24 hours to schedule a call with one of our experts.