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Qeltrava AI LogoQeltrava AI

Qeltrava Delivery OS

Our systematic framework to ensure flawless software architecture, transparent sprint progress, and clear business outcomes.

Delivery Phases

1. Diagnose & Design

We map your operational landscape, identify where AI and modern architecture create ROI, and compile a 90-day execution roadmap before writing code.

2. Architect & Build

Dedicated engineering pods build in 2-week iterations — modular, tested, and documented. Every milestone ends with a working demo, not a static presentation.

3. Validate & Deploy

Every rollout undergoes automated test suite sweeps, HIPAA/SOC 2 compliance checks, performance profiling, and an incremental deployment window.

4. Optimize (Retainer)

Post-release, we provide dedicated support pods for cloud cost optimization, agent telemetry monitoring, server maintenance, and product features velocity.

How Qeltrava AI Thinks & Executes

Hover over each execution node along our spine to see our core values and phase metrics.

1Identification of the need

Diagnosing operational inefficiencies, analyzing legacy architectures, and defining clear business goals.

Audit Complete in 5 Days

2Create digital solutions

Drafting scalable cloud blueprints, defining agent workflow pipelines, and security compliance parameters.

24-Hour Discovery Blueprint

3Develop a software

Writing modular, clean, and testable codebases in rapid sprints under dedicated pods.

4-Week Rapid Prototype MVP

4Quality assurance

Automated end-to-end integration tests, unit regression audits, security penetration testing, and load checks.

100% Automated Test Coverage

5Maintenance

24/7 server log inspections, API latency audits, system upgrades, and model safety checkups.

99.99% Production Uptime

6Design websites & portals

Crafting beautiful, responsive, and intuitive UX/UI designs designed to convert visitors.

Responsive Web/App Delivery

7Business point of view

Measuring final platform execution outcomes against business ROI, efficiency targets, and budget caps.

Fixed-Price Value Bundles

Pricing Models

We price based on business value, technical complexity, and risk boundaries. We charge for diagnostic sprints and align project deliverables with clear payment milestones.

ModelWhat it isWhen we use it
Fixed-scope projectDefined deliverables, milestone payments (40% upfront / 40% mid-project / 20% launch) based on approved architectural specifications.Well-scoped builds with clear technical requirements and defined feature boundaries.
Time & materialsWeekly or monthly billing with strict scope controls, regular velocity updates, and agile backlog prioritization.Evolving products and continuous iteration where requirements adapt to live user feedback.
Outcome retainerMonthly engineering pod fee with defined KPIs, dedicated developers, priority support SLAs, and continuous system monitoring.Long-term engineering partnerships, agent fine-tuning, and cloud infrastructure operations.

AI Adoption Strategy for Business

Click on any step of the wave to see detailed engineering outputs, deliverables, and timelines.

Understand the AI Potential
1
Identify Your End Goal
2
Evaluate Internal Capabilities
3
Build or Integrate AI Solution
4
Test the AI System
5
Measure and Evaluate Performance
6
Stay Updated with AI Trends
7
Phase 1Timeline: Week 1

Understand the AI Potential

Discover how generative AI, machine learning, and agents can solve specific operational challenges inside your business.

Key Deliverables
  • Opportunity Map
  • Technology Feasibility Report
  • ROI Hypotheses Matrix

Ready to build?

Start with an AI Opportunity Audit to diagnose technical bottlenecks and outline a structured ROI plan.

Book an AI Strategy Call →
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