Proof of Methodology: AI Built on Captured Expertise

Before we had clients, we proved the approach on ourselves. These AI models demonstrate what happens when you capture expertise through scenario workshops. Same process we use for you.

Why These Matter

Each of these AI assistants was built using the same methodology we apply to client work. We identified expertise gaps, ran scenario workshops, captured decision patterns, and trained AI on the results.

The difference? These know about general domains. Yours will know about YOUR business, YOUR edge cases, YOUR way of working.

DataForge: Financial Data Expert

Building AI that understands financial market conventions

The Challenge

Financial data has context that generic AI misses. Market conventions, regulatory nuances, instrument-specific logic, and trading system dependencies. Documentation captures rules but not the reasoning behind them.

The Approach

We captured expertise from financial operations teams through scenario workshops focused on real data challenges:

  • Trade lifecycle scenarios across different asset classes
  • Data validation challenges in portfolio management systems
  • Reconciliation workflows and exception handling
  • Regulatory reporting requirements and edge cases

The Result

DataForge understands financial data structures, trading systems, and risk management context. It knows when data rules have exceptions, why certain conventions exist, and how different systems interact. Not perfect, but proof the methodology works.

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PitchPerfect: Sales Messaging AI

Scaling expertise in technical sales conversations

The Challenge

Every sales rep explains solutions differently. Your best performers have patterns they use for positioning, objection handling, and closing. That expertise lives in their heads, not in your playbook.

The Approach

We documented effective sales scenarios and captured decision patterns:

  • Discovery call frameworks that uncover real needs
  • Technical positioning for different buyer personas
  • Objection handling for common concerns
  • Competitive differentiation without badmouthing

The Result

PitchPerfect helps sales teams position technical solutions consistently. It suggests discovery questions, provides positioning frameworks, and offers objection responses based on captured expertise. Your version would know YOUR products, YOUR competitors, YOUR market.

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Workshop Sales Assistant: Cyaxios Workshop Expert

AI that helps explain our workshop methodology, built using the same scenario workshops as the other models.

The Challenge

Building effective scenario workshops requires understanding learning objectives, realistic situations, and decision points. This is specialized expertise we needed to scale to help clients build their own scenarios.

The Approach

We documented our own workshop development process:

  • How to identify learning outcomes from business challenges
  • Structuring scenarios that mirror real decision points
  • Creating trigger events that drive meaningful discussion
  • Designing debriefing questions that capture insights

The Result

Workshop Assistant guides clients through scenario development. It asks questions to understand their challenges, suggests scenario structures, and helps design effective learning experiences. Currently operational and helping organizations build their own expertise capture programs.

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Client Case Studies Coming Soon

We are currently working with clients in financial services, manufacturing, and healthcare. Their case studies will be published as projects complete in 2025.

Financial Services

Operations AI for trade processing and system migrations

Manufacturing

Quality Control AI capturing inspector expertise and decision patterns

Healthcare

Compliance AI for regulatory requirements and exception handling

Ready to Build Your Own?

These models prove the methodology works. Same process, but trained on YOUR expertise instead of generic knowledge.

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