01
Start with a clear read on where gen AI fits. Advisory work scores your data, use cases, skills, and risk, then ranks the opportunities worth funding. You begin from facts, not hype, before any spend. The result is a short, ranked list of bets worth making.
02
Shape models to your business, not the other way around. Scoping covers fine-tuning, RAG, and prompt design on foundation models, so outputs reflect your data and voice while a human stays in control.
03
Put agents to work on real, multi-step tasks. Advisory design maps where AI agents and automation belong across your workflows, with human checkpoints, so the system acts within the limits you set.
04
Build trust in before you scale out. We align controls to responsible AI, the NIST AI RMF, and ISO 42001, covering bias, privacy, and oversight, so gen AI stays compliant and defensible.
05
Generative AI Proof of Concept and Pilot
Prove value fast on one real use case. Advisory scoping defines the pilot, success metrics, and guardrails, so you learn what works in weeks and decide on scaling from evidence, not a hunch.
06
Keep models accurate after launch. Advisory design adds monitoring for hallucination, model drift, and cost, so quality holds and spend stays in check as usage grows across your teams.