Pricing and fit

AI Consulting Pricing and Engagement Models

Pricing is custom because production AI work depends on scope, risk, data readiness, latency needs, infrastructure, and the level of implementation support. The first step is a discovery call, followed by a scoped proposal.

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Project-Based

Best for a defined AI system, prototype-to-production build, ML infrastructure optimization, or computer vision implementation.

  • Typical duration: 1-6 months
  • Scoped milestones and deliverables
  • Architecture, implementation, documentation, and handoff

Monthly Retainer

Best for ongoing AI advisory, technical review, architecture decisions, model evaluation, and continuous improvement.

  • Typical duration: ongoing
  • Flexible advisory and implementation support
  • Useful for founders and SMB operators without a full AI team

Embedded Support

Best for larger technical efforts where Animikh acts as an embedded AI systems architect or senior ML engineer.

  • Typical duration: 3+ months
  • Part-time or full-time integration
  • Works alongside product, engineering, and leadership teams

Typical Service Windows

ML infrastructure optimization
1-3 months

LLM/RAG implementation
1-4 months

MLOps and production systems
2-4 months

Computer vision systems
2-6 months

Last updated: 2026-05-19. Exact prices are shared in proposals after scope, complexity, timeline, and engagement model are clear.