Christopher Blakey Full Stack Engineer
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Product case study / AI / Workflow automation

AIVA SystemConnected AI intake

Connect voice and chat inquiries with lead qualification, follow-up, and scheduling.

AI voiceChat intakeCRM workflows

Relevant technical skills

  • API integration
  • Async workflows
  • LLM integration
  • Prompt design
  • Response evaluation
  • Error handling
  • Observability
  • Integration testing

These skills describe a proposed engineering approach. They are not a verified list of the company’s internal technologies.

01 / The problem

Context

Potential clients arrive across calls, forms, and messages. AIVA presents a connected intake process for personal injury firms, including follow-up and consultation scheduling.

02 / The experience

A connected product workflow

The product organizes an inquiry into a structured lead journey. Qualification, booking, pipeline visibility, and manual review form a connected workflow.

  1. 01Receive inquiry
  2. 02Gather details
  3. 03Route for review
  4. 04Schedule consultation

03 / Technical perspective

Engineering approach

A proposed implementation should preserve a single lead record across channels, validate contact details, and make appointment creation idempotent. Sensitive or uncertain requests need a clear path to staff review.

This section outlines a proposed approach, rather than the company’s verified internal implementation.

04 / Reliability

Testing priorities

Exercise duplicate inquiries, interrupted calls, unavailable time slots, opt-outs, time zones, and staff escalation. Confirm that retries cannot create duplicate bookings or follow-up messages.

05 / Source & attribution

Explore the product

This independent study is based on the company’s public website. The gallery contains imagery sourced from the company’s official website and public product resources. Images belong to their respective owners. This study does not claim a personal role in building the product.

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