Coorva

AI-SDLC Implementation Services

Delegate More Engineering Work to AI Without Losing Control.

Coorva helps engineering teams integrate AI agents across requirements, development, testing and review, using their existing tools and engineering standards.

Keep your tools. Keep your standards. Make AI part of your delivery process.

Start an AI-SDLC ImplementationSee How It Works

Software delivery lifecycle

  • Engineers
  • AI agents

  1. 01Define

    • Engineers: Requirements
    • AI agents: Draft tasks

  2. 02Context

    • Engineers: Standards
    • AI agents: Project knowledge

  3. 03Build

    • Engineers: Guidance
    • AI agents: Code and tests

  4. 04Validate

    • Engineers: Review
    • AI agents: Automated checks

  5. 05Release

    • Engineers: Approval
    • AI agents: Change summaries
Engineers guide, validate and own delivery.

Brands That Have Trusted Coorva

  • Siemens
  • Shell
  • InterCement
  • Attune
  • Denim Social
  • Poppy
  • NavigatingCare
  • Handl Health
  • HITN
  • Loma Negra
  • Smithsonian Channel
  • XAPPAI

Beyond AI Coding

Generating Code Is Only Part of Software Delivery.

AI agents can accelerate implementation, but software still needs clear requirements, coordinated workflows and reliable validation.

  • Context Matters

    Agents need project knowledge, specifications and technical constraints to work effectively.

  • Quality Still Matters

    Code must meet engineering standards, pass appropriate checks and be reviewed before release.

  • Delivery Needs Coordination

    AI-generated work must fit into the same repositories, processes and responsibilities as the rest of the team.

An AI-Enabled Engineering Workflow

From Requirements to Release, With AI in the Process.

  1. Stage 01

    Define the Work

    Turn business needs into clear engineering requirements and acceptance criteria.

  2. Stage 02

    Prepare the Context

    Give agents the architecture, conventions, constraints and tools needed to work within the project.

  3. Stage 03

    Build with AI Agents

    Use coding agents to implement changes, generate tests and prepare pull requests.

  4. Stage 04

    Validate and Review

    Apply automated checks, engineering reviews and quality standards before accepting changes.

  5. Stage 05

    Release and Improve

    Integrate approved work into the existing delivery process and use engineering feedback to refine how AI is applied.

From Approach to Implementation

AI-SDLC Built Around Your Engineering Team.

Coorva works with your team to incorporate AI into the software delivery process you already use.

  • Workflow Design

    Define where AI agents participate and how their work moves through engineering.

  • Agent Integration

    Connect AI-assisted development practices with your repositories, backlog and CI/CD.

  • Engineering Standards

    Establish project context, testing practices, review expectations and clear responsibilities.

  • Adoption and Measurement

    Evaluate how the new workflow operates and identify where it makes sense to expand AI participation.

Practical Adoption

Start with Real Engineering Work.

You don't need to redesign your entire SDLC to introduce AI-assisted delivery.

  1. Step 1: Choose a Workstream

    Select an engineering workflow where AI-assisted execution is relevant.

  2. Step 2: Implement the Approach

    Adapt the process, tools and engineering practices with your team.

  3. Step 3: Evaluate and Expand

    Review the results against agreed engineering measures and decide where to extend the approach.

What We Measure

AI-assisted work, human intervention, review effort, rework, defects and acceptance quality.

Our Commitment

The AI-SDLC Implementation Guarantee

Start with one real engineering workflow. We'll agree upfront on the scope, engineering practices, responsibilities and acceptance criteria your implementation needs to establish.

If we can't demonstrate the agreed AI-assisted development workflow within the first 30 days of your initial implementation, we'll refund your implementation fee.

Clear Scope. Visible Progress. Human Accountability.

Engineering Experience

Built on Experience. Driven by Engineering.

The team at Coorva brings years of software engineering and entrepreneurial experience to AI-assisted development.

  • 20+ Years of Experience

    Building digital solutions for businesses, US startups and enterprise-level companies.

  • A Decade Building Coorva

    Developing software and AI solutions grounded in real engineering experience.

  • Entrepreneurial Recognition

    Our team’s previous venture, Walead, was recognized through Founder Institute Córdoba 2020 and IncuBAte 2019.

The Coorva team standing together and smiling

What Clients Say About Coorva

  • We’ve noticed reduced downtime, faster feature releases, and increased platform stability.

    Julien Stamatakis

    CTO, Attune

    Attune

  • One of the owners traveled to Houston to personally meet with me. We were completely satisfied with Coorva’s work and could not have asked for a better outcome.

    John Oren

    CEO, TUYA Technologies

    TUYA Technologies

  • Our Coorva resources have met our engineering velocity and coding quality standards.

    Gary Manfredi

    Engineering Manager, Navigating Care

    NavigatingCare

Let's Talk About Your Engineering Workflow

Bring AI Into Your Software Delivery Process.

Explore how Coorva can help your team integrate AI agents into real engineering work, using your existing tools and standards.

Start with one engineering workstream. Build from there.

Implementation Clarity Commitment

Before implementation begins, we define the workstream, expected deliverables, engineering responsibilities and acceptance criteria. Review the results against those expectations before deciding where to expand.