Last updated: Aug 12, 2025, 01:09 PM UTC

HireBest AI Consultant - Phase 1 Proof of Concept

Date: August 12, 2025
Duration: 2 weeks
Investment: $4,000

Executive Summary

Transform HireBest's consulting expertise into an AI-powered virtual consultant that learns from your onboarding materials and delivers reports matching your consultant quality. This proof of concept strikes the optimal balance between cost and effort to prove the value before committing to full-scale implementation.

The Opportunity

HireBest has built exceptional consulting methodologies over 20+ years. Your current Bubble platform captures interview data but cannot access your institutional knowledge. This creates dependency on senior consultants who "remember that similar project from 2015."

Phase 1 Goal: Prove an AI can learn to think and write like a HireBest consultant by training on your onboarding deck and sample projects. This focused scope balances investment with meaningful validation - enough to demonstrate value without over-engineering.

Technical Approach

Infrastructure

  • Private US Server: Dedicated Sliplane-hosted environment (US-based, controlled by Knowcode)
  • AWS Bedrock LLM: Enterprise-grade security with private model deployment
  • Web Upload Interface: Simple browser-based document upload (no technical tools required)
  • Isolated Environment: Secure sandbox for your proprietary materials

AI Development Process

  • Ingest your consulting onboarding deck
  • Import existing AI prompts from your Bubble application
  • Process 2-3 complete project examples
  • Prompt engineering through close collaboration with Mike
  • Iterate until output matches consultant quality

Phase 1 Deliverables (2 Weeks)

Week 1: Discovery & Setup

  • Configure AWS Bedrock environment (untested platform - requires discovery)
  • Build web-based document upload system
  • Ingest training materials and project samples
  • Initial prompt engineering and optimization

Week 2: Virtual Consultant Development

  • Develop AI consultant methodology through prompt engineering
  • Generate test reports for recent projects
  • Comparative analysis: AI output vs human consultant reports
  • Theme extraction and recommendation patterns
  • Security and privacy documentation delivery

Specific Outcomes

1. AI Consultant Capability

  • System that demonstrates consultant-level thinking
  • Reports matching your quality standards
  • Side-by-side comparison showing AI vs human output

2. Pattern Recognition

  • Identify common themes across projects
  • Extract recurring recommendations
  • Healthcare industry patterns vs other sectors
  • Generate interview questions for similar scenarios

3. Security Documentation

  • Complete AWS Bedrock security architecture
  • Privacy compliance framework
  • Data handling procedures
  • HIPAA-ready configuration approach

4. Foundation for Growth

  • Validated approach for Phase 2 expansion
  • Clear path to full knowledge base integration
  • Roadmap for LinkedIn/social executive profiling
  • Integration strategy for Fable system

Required from HireBest

  • Onboarding deck and training materials
  • 2-3 complete project sets:
    • Source documents and CIMs
    • Interview transcriptions
    • Final consultant reports
  • Existing AI prompts from Bubble application
  • Mike's availability for prompt refinement sessions (4-6 hours total)

What's NOT Included (Phase 1)

  • Full 20-year file system analysis (Phase 2)
  • LinkedIn/social media integration (Phase 2)
  • Fable system integration (Phase 2)
  • Production deployment (Phase 2)
  • Automated workflows (Phase 2)

Success Criteria

AI produces consultant-quality analysis
Reports achieve 80%+ match to human output
Successfully identifies project themes and patterns
Security documentation approved
Mike confirms practical value for consulting team

Investment & Timeline

Phase 1 Investment: $4,000 (fixed price)

  • Week 1: Infrastructure setup and ingestion
  • Week 2: Training and validation
  • Deliverable: Working proof of concept with documentation

Phase 2 Preview (Separate Engagement):

  • Full knowledge base integration
  • Executive intelligence gathering
  • Fable integration
  • Production deployment
  • Investment: TBD based on Phase 1 findings

Risk Mitigation

  • AWS Bedrock Untested: We'll discover optimal configurations and have fallback LLM options
  • Prompt Engineering Complexity: Iterative refinement with frequent Mike feedback
  • Quality Variance: Focus on specific use cases first, expand gradually
  • Integration Challenges: Deferred to Phase 2 after validation

Next Steps

  1. Approve Phase 1 engagement
  2. Provide access to training materials
  3. Schedule kickoff with Mike
  4. Begin 2-week proof of concept

This proof of concept establishes the foundation for transforming HireBest's institutional knowledge into an AI-powered competitive advantage, dramatically reducing report creation time while maintaining quality standards.