Pricing Philosophy
AI infrastructure requires
strategic investment
Not one-time builds. Your AI system is a living architecture — it must be maintained, optimized, and evolved.
Why AI Requires Ongoing Optimization
- AI models are not 'set and forget.' They require continuous monitoring, testing, and refinement.
- Token costs fluctuate as models update. Without active optimization, costs can double overnight.
- User behavior evolves. Prompts that worked last month may underperform today.
- New models release frequently. Migration requires testing and validation.
- A/B testing is ongoing. Small prompt changes can improve conversion by 30%+
Why Memory Degrades Without Tuning
- Memory systems accumulate noise over time. Irrelevant context reduces model accuracy.
- Memory schemas must evolve as your product grows. Rigid schemas break at scale.
- Session continuity logic requires monitoring. Edge cases emerge in production that don't exist in testing.
- Without regular memory pruning, token costs increase while performance decreases.
- Users expect personalization to improve over time, not degrade.
Why Model Updates Require Management
- Anthropic and OpenAI update models without warning. Breaking changes happen.
- New models offer better performance but different behavior. Migration isn't automatic.
- Model version pinning prevents surprise breakage but locks you out of improvements.
- Hybrid model strategies (Claude for reasoning, GPT for speed) require ongoing balance.
- Your system must abstract the model layer to remain flexible.
Why Monetization Must Evolve
- AI feature usage patterns shift. What users found valuable last quarter may change.
- Token costs per feature vary. A profitable feature today may become expensive tomorrow.
- Subscription tiers must align with actual usage. Misalignment leads to churn or loss.
- Usage-based billing requires active monitoring. Overages and underpricing hurt profitability.
- Monetization strategy isn't static. It must adapt as your AI system evolves.
Partnership Model
Ongoing Retainer
$850 – $1,800 / month
Our retainer engagements ensure your AI infrastructure remains optimized, cost-effective, and competitive.
Continuous model optimization
Token cost monitoring & reduction
Memory system tuning
Prompt template A/B testing
Model migration management
Analytics & performance reports
Priority support & consultation
Strategic AI roadmap planning
One-Time Build vs. Strategic Partnership
One-Time Build
- Fixed implementation, no optimization
- Token costs increase over time
- Memory degrades with usage
- Model updates break features
- No analytics or monitoring
- No strategic guidance
Ongoing Partnership
- Continuous performance improvements
- Token costs actively managed
- Memory system stays optimized
- Seamless model migrations
- Full visibility & reporting
- Strategic AI roadmap planning