Generative AI consulting services built to deploy

The initial scoping and strategy phase typically takes three to four weeks. A proof of concept adds two to four weeks on top of that. Full deployment timelines depend on system complexity and your team's capacity but most engagements reach first production release within eight to twelve weeks of sign-off.

Every engagement closes with a documented AI roadmap, a prioritized use case registry, a model selection recommendation with cost modeling, a data readiness assessment, and a 90-day Sprint plan your engineering team can execute without further consulting support. You own everything delivered.

Yes. The default engagement model is advisory alongside your internal team. We scope what we own, what your team owns, and where the handover happens before Sprint 1 starts. Your engineers stay in the loop and leave the engagement more capable, not more dependent.

Governance is designed in at the architecture stage, not added as an afterthought. We build access controls, data residency requirements, audit logging, and model usage policies into the initial design. GDPR, SOC 2, and sector-specific requirements are mapped in the strategy phase so your compliance team has documentation from day one.

A generative AI consulting firm works at the model selection, prompt engineering, RAG architecture, and deployment pipeline layer. General technology consultants typically work at the project management, vendor selection, or enterprise IT layer. The difference shows up at the point of implementation: Redefine consultants write code, configure models, and validate outputs, not just scope and supervise.