AI Consulting for Startups
Production RAG in Weeks, Not Months

Transform underutilized business data into measurable revenue. Production-ready RAG patterns with confidence scoring and citation accuracy. 2-5 day proof-of-concepts using your actual data.

What AI Consulting Delivers

Fast Value Delivery

2-5 day proof-of-concepts using your actual data. 2-4 week production deployments. No 6-month roadmaps.

2-5 Days

PoC Timeline

Data Monetization

Unlock $100K-500K in trapped value from content libraries, operational data, customer conversations.

$180K+

Annual Savings

Production Patterns

Confidence scoring, citation accuracy, explicit uncertainty. Systems that work with real business data.

60-70%

Time Reduction

AI Consulting Services

Production RAG Architecture

Hierarchical RAG with parent-child indexing. Confidence scoring. Citation accuracy. Explicit uncertainty handling.

  • Content monetization (video/webinar libraries)
  • Operational intelligence (CRM/accounting data)
  • Sales intelligence (contextual decision support)

AWS Bedrock & SageMaker Implementation

Production-grade GenAI on AWS: Bedrock for managed models, SageMaker for custom fine-tuning, RAG orchestration.

  • QuickSuite for simple use cases
  • Bedrock for enterprise RAG
  • SageMaker for advanced ML

Data Readiness & Governance

Assess data assets for RAG feasibility. PII handling. Quality scoring. Schema mapping for structured data.

  • Content library audit
  • Operational data mapping
  • Privacy and compliance

AI Consulting Use Cases

Content Library Monetization

Transform 500+ hours of webinars, presentations, research into searchable knowledge base.

Outcomes
  • 60% reduction in consultant prep time
  • $180K annual labor savings
  • $45K new revenue from identified offerings
View Case Study →

Operational Intelligence

Natural language access to disconnected operational data: CRM, accounting, support tickets.

Outcomes
  • 65% reduction in analyst time
  • $280K retained revenue (churn prevention)
  • $85K duplicate payments discovered
View Case Study →

Sales Intelligence

Real-time contextual intelligence during sales calls: competitive positioning, objection handling, case studies.

Outcomes
  • 32% sales cycle reduction
  • 23% win rate improvement
  • 50% faster new rep ramp
View Case Study →

What Makes This Different

Production Patterns Over Demos

  • Confidence scoring and explicit uncertainty
  • Citation accuracy with source attribution
  • Error handling for real-world data
  • Graceful degradation when coverage is low

Fast Value Delivery

  • 2-5 day PoCs (not 6-month roadmaps)
  • Working prototypes using your actual data
  • Validates approach before commitment
  • 2-4 week production deployments

Data Monetization Focus

  • Identify which data assets have highest ROI
  • Measure impact in business outcomes
  • Reduced costs, accelerated revenue, margin improvement
  • Not just technical implementation

AI Consulting FAQ

How is this different from ChatGPT or generic AI tools?

ChatGPT is trained on public internet data and can't access your proprietary business data. Our RAG systems search your specific data assets (content libraries, operational data, customer conversations) and provide grounded, citation-backed answers with confidence scoring. It's the difference between asking a generalist consultant versus accessing your company's institutional knowledge systematically.

What if our data is messy or incomplete?

Production RAG systems explicitly handle data quality issues rather than hiding them. We implement confidence scoring, explicit uncertainty handling ('I don't have enough information'), and data quality reporting. A system that says 'I don't know' when appropriate is more valuable than one that hallucinates convincingly.

Do you work with non-AWS cloud providers?

Yes, we're cloud-agnostic. However, AWS Bedrock and SageMaker are often the right choice for startups due to managed services, cost-effective pricing, and integration with existing AWS infrastructure. We also work with Azure OpenAI and Google Cloud Vertex AI.

Can you help if we want to build this in-house eventually?

Yes. All code is fully documented, modular, and transferable. We provide knowledge transfer documentation and can train your team on the architecture. Many clients start with our implementation to validate business value, then gradually take over maintenance as their team builds capability.

Ready to Unlock Value from Your Data?

Schedule a free data asset analysis. We'll identify which data has highest monetization potential and outline a PoC approach.

Schedule AI Assessment