Status: Deployed

AI Workflow Repair Intake

A programmatic diagnostic system that analyzes broken workflows and recommends architectural fixes without discovery calls, powered by Elitza AI.

5min

Avg. Diagnosis

Zoom Calls

100%

Async

The Problem

Traditional consulting relies on costly discovery calls, manual analysis, and weeks of back-and-forth to understand technical debt and workflow issues. This is slow, expensive, and often produces generic recommendations that don't address the actual root causes.

The Solution

AI Workflow Repair Intake is a programmatic diagnostic system that replaces discovery calls with automated analysis. Clients submit a brief description of their broken workflow, and Elitza AI performs deep technical analysis, identifies bottlenecks, and recommends specific fixes.

How It Works

Submit Issue

Describe what's breaking in your technical stack. No need for lengthy explanations—just the core problem.

Automated Analysis

Elitza analyzes your stack configuration, identifies failure patterns, and benchmarks against 13+ frontier AI models' evaluation criteria.

Tiered Recommendations

Receive priority-ranked fixes: critical, high, medium, or low priority with specific implementation steps.

Direct Consultation

Choose your communication channel (WhatsApp, Telegram, Discord, or Email) for follow-up technical discussion.

Technical Architecture

Powered by Elitza AI

# Diagnostic Pipeline
input = client_issue_description

# 1. Parse stack configuration
stack_config = parse_technical_context(input)

# 2. Identify failure patterns
patterns = elitza.analyze(
    config=stack_config,
    models=['claude-3.5', 'gpt-4o', 'gemini-1.5'],
    criteria=['performance', 'scalability', 'maintainability']
)

# 3. Benchmark against known solutions
benchmarks = compare_against_production_systems(
    patterns,
    database=100+_business_workflows
)

# 4. Generate tiered recommendations
recommendations = prioritize_fixes(
    patterns,
    benchmarks,
    urgency='high'
)

# 5. Route to appropriate channel
route_to_channel(client, recommendations)

Key Features

Zero Human Intervention: Fully automated analysis pipeline
Elitza-Powered: Uses the same AI system that runs Gapfeed
Multi-Model Analysis: Benchmarks against Claude, GPT, and Gemini
Tiered Priority: Critical, High, Medium, Low classifications
Async-First: No meetings, no calls, pure technical analysis

Use Cases

CRM Bottlenecks: Automated lead routing failures, duplicate prevention issues
Workflow Automation: Broken Zapier/Make chains, API integration failures
Technical Debt: Legacy system migration, SaaS stack optimization
Performance Issues: Slow sync times, rate limiting, data consistency problems

Run My Stack Diagnosis

Submit your technical issue and receive automated analysis within minutes.

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