Many pilots, little value
Use cases scatter across teams without portfolio criteria or a repeatable delivery path.
AI & GenAI Factory
Turn scattered pilots into a reusable delivery factory: shared evaluation, co-creation, engineering, and operations — so GenAI moves from demos to acceptable business capability.
Challenges
Where GenAI scale-up stalls
Model skill ≠ business capability
Prompts and demos do not replace workflow embedding, permissions, knowledge governance, and human–AI design.
Engineering and compliance pressure
Hallucination, data leakage, and audit needs demand observable, rollback-ready, acceptable delivery.
Approach
Factory approach
Prioritize with value diagnosis, define acceptance through co-creation, then industrialize templates and operating loops.
Value screening & portfolio
Rank scenarios by impact, data readiness, and risk — phased investment, not parallel scatter.
Co-create acceptance
Business and tech jointly design workflows, knowledge boundaries, and human roles — with observable metrics upfront.
Engineer & operate
Template retrieval/tools, evaluation, and monitoring; feed production feedback into continuous iteration.
Capabilities
What we deliver
GenAI factory blueprint
Scenario catalog, prioritization, guardrails, and delivery cadence.
Workflow-embedded apps
Q&A, document assist, decision support — inside existing systems and permissions.
Evaluation & ops
Quality checks, risk lists, on-call and iteration rhythms for scaled operation.
Start with factory delivery
Book Discovery with priority domains and current pilots — we converge on a scalable path.