Use Case Delivery

End-to-end AI solution development with predictable outcomes

8-10 Week Timeline
100% Cloud-Hosted
90 Day Support

What You Get

A fully operational AI solution deployed to your cloud environment, with complete documentation, trained staff, and ongoing support. We don't just build models—we deliver production-ready systems that integrate with your existing infrastructure and create immediate business value.

Production-Ready Solution

Deployed, tested, and validated in your environment

Full Source Code

Complete codebase with infrastructure-as-code

Documentation Package

Technical specs, runbooks, and user guides

Training Sessions

Hands-on training for your technical team

Delivery Process

Our structured approach ensures predictable timelines and quality outcomes

Use Case Delivery Timeline
1

Stakeholder Alignment

Week 1

We begin by establishing clear alignment across all stakeholders. This phase ensures everyone shares the same understanding of objectives, constraints, and success criteria before any development begins.

Key Activities

  • Executive Sponsor Alignment — Define business objectives, ROI expectations, and organizational readiness
  • Technical Leadership Review — Assess existing infrastructure, data availability, and integration requirements
  • End User Workshops — Understand current workflows, pain points, and adoption considerations
  • Risk Assessment — Identify potential blockers, dependencies, and mitigation strategies

Deliverables

Project Charter
Stakeholder Map
Success Metrics
2

Requirements Gathering & Analysis

Week 1-2

Deep dive into your data landscape, business rules, and technical requirements. We document everything needed to design a solution that fits your specific context.

Key Activities

  • Data Discovery — Catalog available data sources, assess quality, identify gaps
  • Business Rules Documentation — Capture domain logic, edge cases, and compliance requirements
  • Integration Mapping — Document upstream/downstream systems and data flows
  • Performance Requirements — Define latency, throughput, and availability targets
Requirements Analysis Process

Deliverables

Data Dictionary
Requirements Spec
Integration Map
3

Solution Design & Architecture

Week 2-4

We design a solution architecture optimized for your cloud environment (Azure or AWS), with clear component boundaries, scalability considerations, and operational requirements built in from the start.

Key Activities

  • Architecture Design — Define cloud resources, networking, security boundaries
  • ML Pipeline Design — Specify data processing, feature engineering, model training workflows
  • API Contract Definition — Document interfaces, authentication, rate limits
  • Infrastructure Planning — Size compute resources, define scaling policies
Solution Architecture Example

Deliverables

Architecture Diagram
API Specifications
Infrastructure Plan
4

Implementation & Deployment

Week 4-8

We build and deploy your solution using infrastructure-as-code practices. Everything is version-controlled, reproducible, and designed for maintainability. The final deliverable is a fully wrapped cloud-hosted service deployed to your Azure or AWS environment.

Your Solution Includes

Infrastructure Terraform/ARM templates for all cloud resources
CI/CD Pipeline Automated build, test, and deployment workflows
Monitoring Dashboards, alerts, and logging configured
Security RBAC, encryption, network isolation

Key Activities

  • Sprint-Based Development — Two-week sprints with demos and feedback cycles
  • Model Development — Feature engineering, training, validation, optimization
  • Integration Development — Connect to source systems, build APIs, implement auth
  • Testing — Unit tests, integration tests, load tests, UAT
  • Deployment — Staged rollout to dev, UAT, production environments
Deployment Architecture

Deliverables

Source Code Repository
Deployed Services
Monitoring Dashboard
5

Training & Documentation

Week 8-10

We ensure your team has everything needed to operate, maintain, and extend the solution independently. Training is hands-on and tailored to different audience levels.

Technical Operations

For DevOps and platform teams

  • Infrastructure management
  • Deployment procedures
  • Monitoring and alerting
  • Incident response

Data Science

For ML and analytics teams

  • Model retraining workflows
  • Feature engineering
  • Performance monitoring
  • Drift detection

Business Users

For end users and stakeholders

  • System overview
  • Interpreting outputs
  • Feedback mechanisms
  • Escalation paths

Documentation Package

Technical Design Document Complete architecture and design decisions
Operations Runbook Step-by-step procedures for common tasks
API Documentation Complete API reference with examples
User Guide End-user documentation and FAQs
6

90-Day Post-Launch Support

Week 10-22

We don't disappear after deployment. Our 90-day support period ensures your team has backup while they build confidence with the new system.

Response SLA

4-hour response for critical issues, 24-hour for standard requests

Bug Fixes

Resolution of any defects discovered during the support period

Office Hours

Weekly Q&A sessions for your team to ask questions

Minor Enhancements

Small adjustments based on real-world usage feedback

Ready to Build Your AI Solution?

Let's discuss your use case and create a tailored delivery plan.

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